diff --git a/integrations/tensorflow/iree_tf_compiler/TF/LowerGlobalTensors.cpp b/integrations/tensorflow/iree_tf_compiler/TF/LowerGlobalTensors.cpp
index 7445215..3877007 100644
--- a/integrations/tensorflow/iree_tf_compiler/TF/LowerGlobalTensors.cpp
+++ b/integrations/tensorflow/iree_tf_compiler/TF/LowerGlobalTensors.cpp
@@ -33,13 +33,12 @@
                                                          Value flowPtr) {
   OpBuilder builder(&op);
   if (auto readVariable = dyn_cast<mlir::TF::ReadVariableOp>(op)) {
-    auto load =
-        builder.create<iree_compiler::IREE::Flow::VariableLoadIndirectOp>(
-            readVariable.getLoc(), readVariable.value().getType(), flowPtr);
+    auto load = builder.create<iree_compiler::IREE::Util::GlobalLoadIndirectOp>(
+        readVariable.getLoc(), readVariable.value().getType(), flowPtr);
     readVariable.value().replaceAllUsesWith(load.result());
     readVariable.erase();
   } else if (auto assignVariable = dyn_cast<mlir::TF::AssignVariableOp>(op)) {
-    builder.create<iree_compiler::IREE::Flow::VariableStoreIndirectOp>(
+    builder.create<iree_compiler::IREE::Util::GlobalStoreIndirectOp>(
         assignVariable.getLoc(), assignVariable.value(), flowPtr);
     assignVariable.erase();
   } else {
@@ -72,10 +71,9 @@
              << "Multiple exported names for global tensor not supported yet";
     }
     symNameToFlowSymName[globalTensor.sym_name()] = flowSymName;
-    auto variableOp =
-        globalBuilder.create<iree_compiler::IREE::Flow::VariableOp>(
-            globalTensor.getLoc(), flowSymName, globalTensor.is_mutable(),
-            globalTensor.type(), globalTensor.value());
+    auto variableOp = globalBuilder.create<iree_compiler::IREE::Util::GlobalOp>(
+        globalTensor.getLoc(), flowSymName, globalTensor.is_mutable(),
+        globalTensor.type(), globalTensor.value());
     variableOp.setPrivate();
   }
 
@@ -94,7 +92,7 @@
         continue;
       }
       auto variableAddressOp =
-          builder.create<iree_compiler::IREE::Flow::VariableAddressOp>(
+          builder.create<iree_compiler::IREE::Util::GlobalAddressOp>(
               globalTensor.getLoc(),
               iree_compiler::IREE::Util::PtrType::get(globalTensor.type()),
               builder.getSymbolRefAttr(
diff --git a/integrations/tensorflow/iree_tf_compiler/TF/Passes.h b/integrations/tensorflow/iree_tf_compiler/TF/Passes.h
index 5faec10..6601593 100644
--- a/integrations/tensorflow/iree_tf_compiler/TF/Passes.h
+++ b/integrations/tensorflow/iree_tf_compiler/TF/Passes.h
@@ -30,7 +30,7 @@
 std::unique_ptr<FunctionPass> createConvertToMHLOPass();
 
 // In a module tagged with `tf_saved_model.semantics`, lowers
-// `tf_saved_model.global_variable`'s to `flow.variable`'s.
+// `tf_saved_model.global_variable`'s to `util.global`'s.
 //
 // This pass should be run before adopting the exports, which transitions to
 // a module that does not have `tf_saved_model.semantics`.
diff --git a/integrations/tensorflow/iree_tf_compiler/TF/test/lower_global_tensors.mlir b/integrations/tensorflow/iree_tf_compiler/TF/test/lower_global_tensors.mlir
index b52ea64..d93da89 100644
--- a/integrations/tensorflow/iree_tf_compiler/TF/test/lower_global_tensors.mlir
+++ b/integrations/tensorflow/iree_tf_compiler/TF/test/lower_global_tensors.mlir
@@ -6,10 +6,10 @@
 // TODO(silvasean): Verify "type" handling.
 // I think when "type" is a partial type that flow will not model it correctly.
 
-// CHECK:       flow.variable [[V:@[a-zA-Z0-9$._-]+]] mutable dense<1.000000e+00> : tensor<1xf32>
+// CHECK:       util.global private mutable [[V:@[a-zA-Z0-9$._-]+]] = dense<1.000000e+00> : tensor<1xf32>
 // CHECK:       func @f() -> (tensor<?xf32> {tf_saved_model.index_path = []})
-// CHECK-NEXT:    [[PTR:%.+]] = flow.variable.address [[V]] : !util.ptr<tensor<?xf32>>
-// CHECK-NEXT:    [[T:%.+]] = flow.variable.load.indirect [[PTR]] : !util.ptr<tensor<?xf32>> -> tensor<?xf32>
+// CHECK-NEXT:    [[PTR:%.+]] = util.global.address [[V]] : !util.ptr<tensor<?xf32>>
+// CHECK-NEXT:    [[T:%.+]] = util.global.load.indirect [[PTR]] : !util.ptr<tensor<?xf32>> -> tensor<?xf32>
 // CHECK-NEXT:    return [[T]] : tensor<?xf32>
 
   "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v", type = tensor<?xf32>, value = dense<1.> : tensor<1xf32> } : () -> ()
@@ -26,10 +26,10 @@
 // CHECK-LABEL: module attributes {tf_saved_model.semantics}
 module attributes {tf_saved_model.semantics} {
 
-// CHECK:       flow.variable [[V:@[a-zA-Z0-9$._-]+]] mutable dense<1.000000e+00> : tensor<1xf32>
+// CHECK:       util.global private mutable [[V:@[a-zA-Z0-9$._-]+]] = dense<1.000000e+00> : tensor<1xf32>
 // CHECK:       func @f(%arg0: tensor<?xf32> {tf_saved_model.index_path = [0]})
-// CHECK-NEXT:    [[PTR:%.+]] = flow.variable.address @__iree_flow_v : !util.ptr<tensor<?xf32>>
-// CHECK-NEXT:    flow.variable.store.indirect %arg0, [[PTR]] : tensor<?xf32> -> !util.ptr<tensor<?xf32>>
+// CHECK-NEXT:    [[PTR:%.+]] = util.global.address @__iree_flow_v : !util.ptr<tensor<?xf32>>
+// CHECK-NEXT:    util.global.store.indirect %arg0, [[PTR]] : tensor<?xf32> -> !util.ptr<tensor<?xf32>>
 // CHECK-NEXT:    return
 
   "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v", type = tensor<?xf32>, value = dense<1.> : tensor<1xf32> } : () -> ()
diff --git a/integrations/tensorflow/iree_tf_compiler/TF/test/lower_global_tensors_complex.mlir b/integrations/tensorflow/iree_tf_compiler/TF/test/lower_global_tensors_complex.mlir
index 360bb56..6e65a12 100644
--- a/integrations/tensorflow/iree_tf_compiler/TF/test/lower_global_tensors_complex.mlir
+++ b/integrations/tensorflow/iree_tf_compiler/TF/test/lower_global_tensors_complex.mlir
@@ -5,12 +5,12 @@
 // CHECK-LABEL: module attributes {tf_saved_model.semantics}
 module attributes {tf_saved_model.semantics} {
 
-// CHECK:      flow.variable [[V:@.+]] mutable dense<1.000000e+00> : tensor<1xf32>
+// CHECK:      util.global private mutable [[V:@.+]] = dense<1.000000e+00> : tensor<1xf32>
 // CHECK:      func @f(%arg0: tensor<?xf32> {tf_saved_model.index_path = [0]}) attributes {tf_saved_model.exported_names = ["f"]} {
-// CHECK-NEXT:   [[PTR:%.+]] = flow.variable.address [[V]] : !util.ptr<tensor<?xf32>>
+// CHECK-NEXT:   [[PTR:%.+]] = util.global.address [[V]] : !util.ptr<tensor<?xf32>>
 // CHECK-NEXT:   br ^bb1([[PTR]] : !util.ptr<tensor<?xf32>>)
 // CHECK-NEXT: ^bb1([[PTR1:%.+]]: !util.ptr<tensor<?xf32>>):   // pred: ^bb0
-// CHECK-NEXT:   flow.variable.store.indirect %arg0, [[PTR1]] : tensor<?xf32> -> !util.ptr<tensor<?xf32>>
+// CHECK-NEXT:   util.global.store.indirect %arg0, [[PTR1]] : tensor<?xf32> -> !util.ptr<tensor<?xf32>>
 // CHECK-NEXT:   return
 
 
@@ -28,15 +28,15 @@
 // CHECK-LABEL: module attributes {tf_saved_model.semantics}
 module attributes {tf_saved_model.semantics} {
 
-// CHECK:      flow.variable [[V:@.+]] mutable dense<1.000000e+00> : tensor<1xf32>
-// CHECK:      flow.variable [[V1:@.+]] mutable dense<1.000000e+00> : tensor<1xf32>
+// CHECK:      util.global private mutable [[V:@.+]] = dense<1.000000e+00> : tensor<1xf32>
+// CHECK:      util.global private mutable [[V1:@.+]] = dense<1.000000e+00> : tensor<1xf32>
 // CHECK:      func @f(%arg0: tensor<?xf32> {tf_saved_model.index_path = [0]}) -> (tensor<?xf32> {tf_saved_model.index_path = [0]}) attributes {tf_saved_model.exported_names = ["f"]} {
-// CHECK-NEXT:   [[PTR0:%.+]] = flow.variable.address [[V]] : !util.ptr<tensor<?xf32>>
-// CHECK-NEXT:   [[PTR1:%.+]] = flow.variable.address [[V1]] : !util.ptr<tensor<?xf32>>
+// CHECK-NEXT:   [[PTR0:%.+]] = util.global.address [[V]] : !util.ptr<tensor<?xf32>>
+// CHECK-NEXT:   [[PTR1:%.+]] = util.global.address [[V1]] : !util.ptr<tensor<?xf32>>
 // CHECK-NEXT:   %[[FALSE:.+]] = constant false
 // CHECK-NEXT:   cond_br %[[FALSE]], ^bb1([[PTR0]] : !util.ptr<tensor<?xf32>>), ^bb1([[PTR1]] : !util.ptr<tensor<?xf32>>)
 // CHECK-NEXT: ^bb1([[PTR:%.+]]: !util.ptr<tensor<?xf32>>):   // 2 preds: ^bb0, ^bb0
-// CHECK-NEXT:   [[T:%.+]] = flow.variable.load.indirect [[PTR]] : !util.ptr<tensor<?xf32>> -> tensor<?xf32>
+// CHECK-NEXT:   [[T:%.+]] = util.global.load.indirect [[PTR]] : !util.ptr<tensor<?xf32>> -> tensor<?xf32>
 // CHECK-NEXT:   return [[T]] : tensor<?xf32>
 
   "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v", type = tensor<?xf32>, value = dense<1.> : tensor<1xf32> } : () -> ()
@@ -55,12 +55,12 @@
 // CHECK-LABEL: module attributes {tf_saved_model.semantics}
 module attributes {tf_saved_model.semantics} {
 
-// CHECK:      flow.variable [[V:@.+]] mutable dense<1.000000e+00> : tensor<1xf32>
+// CHECK:      util.global private mutable [[V:@.+]] = dense<1.000000e+00> : tensor<1xf32>
 // CHECK:      func @f(%arg0: tensor<?xf32> {tf_saved_model.index_path = [0]}) attributes {tf_saved_model.exported_names = ["f"]} {
-// CHECK-NEXT:   [[PTR:%.+]] = flow.variable.address [[V]] : !util.ptr<tensor<?xf32>>
+// CHECK-NEXT:   [[PTR:%.+]] = util.global.address [[V]] : !util.ptr<tensor<?xf32>>
 // CHECK-NEXT:   br ^bb1([[PTR]], [[PTR]], [[PTR]] : !util.ptr<tensor<?xf32>>, !util.ptr<tensor<?xf32>>, !util.ptr<tensor<?xf32>>)
 // CHECK-NEXT: ^bb1([[PTR0:%.+]]: !util.ptr<tensor<?xf32>>, [[PTR1:%.+]]: !util.ptr<tensor<?xf32>>, [[PTR2:%.+]]: !util.ptr<tensor<?xf32>>):       // 2 preds: ^bb0, ^bb1
-// CHECK-NEXT:   flow.variable.store.indirect %arg0, [[PTR0]] : tensor<?xf32> -> !util.ptr<tensor<?xf32>>
+// CHECK-NEXT:   util.global.store.indirect %arg0, [[PTR0]] : tensor<?xf32> -> !util.ptr<tensor<?xf32>>
 // CHECK-NEXT:   br ^bb1([[PTR1]], [[PTR2]], [[PTR0]] : !util.ptr<tensor<?xf32>>, !util.ptr<tensor<?xf32>>, !util.ptr<tensor<?xf32>>)
 
   "tf_saved_model.global_tensor"() { is_mutable, sym_name = "v", type = tensor<?xf32>, value = dense<1.> : tensor<1xf32> } : () -> ()
diff --git a/iree/compiler/Bindings/TFLite/Transforms/MaterializeShapeSupport.cpp b/iree/compiler/Bindings/TFLite/Transforms/MaterializeShapeSupport.cpp
index 3acb9a2..3ff5296 100644
--- a/iree/compiler/Bindings/TFLite/Transforms/MaterializeShapeSupport.cpp
+++ b/iree/compiler/Bindings/TFLite/Transforms/MaterializeShapeSupport.cpp
@@ -79,43 +79,43 @@
     // These variables may represent fully static shapes - in which case they'll
     // get constant propagated - or dynamic shapes that will eventually get
     // turned into dynamic runtime values.
-    SmallVector<IREE::Flow::VariableOp, 4> inputVarOps;
-    SmallVector<IREE::Flow::VariableOp, 4> outputVarOps;
-    createShapeVariables(loc, namePrefix, funcOp, inputVarOps, outputVarOps,
-                         moduleBuilder);
+    SmallVector<IREE::Util::GlobalOp, 4> inputGlobalOps;
+    SmallVector<IREE::Util::GlobalOp, 4> outputGlobalOps;
+    createShapeVariables(loc, namePrefix, funcOp, inputGlobalOps,
+                         outputGlobalOps, moduleBuilder);
 
     // Create internal shape calculation function that updates output shapes if
     // needed. This is only required if there are dynamic shapes.
-    auto dirtyVarOp = moduleBuilder.create<IREE::Flow::VariableOp>(
+    auto dirtyGlobalOp = moduleBuilder.create<IREE::Util::GlobalOp>(
         loc, funcOp.getName().str() + "_shapes_dirty",
         /*isMutable=*/true, moduleBuilder.getI1Type(),
         moduleBuilder.getIntegerAttr(moduleBuilder.getI1Type(), 1));
-    dirtyVarOp.setPrivate();
-    auto calculateShapeFuncOp =
-        createShapeCalculationFunc(loc, namePrefix, funcOp, inputVarOps,
-                                   outputVarOps, dirtyVarOp, moduleBuilder);
+    dirtyGlobalOp.setPrivate();
+    auto calculateShapeFuncOp = createShapeCalculationFunc(
+        loc, namePrefix, funcOp, inputGlobalOps, outputGlobalOps, dirtyGlobalOp,
+        moduleBuilder);
 
     // Create input query function (just reads variables).
-    createQueryInputShapeFunc(loc, namePrefix, inputVarOps, moduleBuilder);
+    createQueryInputShapeFunc(loc, namePrefix, inputGlobalOps, moduleBuilder);
 
     // Create input resize function (updates variables, set dirty flag).
-    createResizeInputShapeFunc(loc, namePrefix, inputVarOps, dirtyVarOp,
+    createResizeInputShapeFunc(loc, namePrefix, inputGlobalOps, dirtyGlobalOp,
                                moduleBuilder);
 
     // Create output query function (if dirty recalculates shapes).
-    createQueryOutputShapeFunc(loc, namePrefix, outputVarOps,
+    createQueryOutputShapeFunc(loc, namePrefix, outputGlobalOps,
                                calculateShapeFuncOp, moduleBuilder);
 
     return success();
   }
 
-  // Creates and initializes to default values one flow.variable for each I/O
-  // shape of the given |funcOp|. |inputVarOps| and |outputVarOps| will be
+  // Creates and initializes to default values one util.global for each I/O
+  // shape of the given |funcOp|. |inputGlobalOps| and |outputGlobalOps| will be
   // populated with the created variables.
   void createShapeVariables(
       Location loc, StringRef namePrefix, FuncOp funcOp,
-      SmallVectorImpl<IREE::Flow::VariableOp> &inputVarOps,
-      SmallVectorImpl<IREE::Flow::VariableOp> &outputVarOps,
+      SmallVectorImpl<IREE::Util::GlobalOp> &inputGlobalOps,
+      SmallVectorImpl<IREE::Util::GlobalOp> &outputGlobalOps,
       OpBuilder &moduleBuilder) {
     auto funcType = funcOp.getType();
 
@@ -148,7 +148,7 @@
       auto type = std::get<1>(input);
       auto tensorType = type.dyn_cast<TensorType>();
       assert(tensorType && "expecting only tensors in tflite function I/O");
-      inputVarOps.push_back(
+      inputGlobalOps.push_back(
           createShapeVariable(loc, name, tensorType, moduleBuilder));
     }
     for (auto output : llvm::zip(outputNames, funcType.getResults())) {
@@ -156,29 +156,29 @@
       auto type = std::get<1>(output);
       auto tensorType = type.dyn_cast<TensorType>();
       assert(tensorType && "expecting only tensors in tflite function I/O");
-      outputVarOps.push_back(
+      outputGlobalOps.push_back(
           createShapeVariable(loc, name, tensorType, moduleBuilder));
     }
   }
 
   // Declares a global variable that holds a shape for the given |tensorType|.
-  IREE::Flow::VariableOp createShapeVariable(Location loc, StringRef name,
-                                             TensorType tensorType,
-                                             OpBuilder &moduleBuilder) {
+  IREE::Util::GlobalOp createShapeVariable(Location loc, StringRef name,
+                                           TensorType tensorType,
+                                           OpBuilder &moduleBuilder) {
     auto shapeType = Shape::RankedShapeType::get(tensorType.getShape(),
                                                  moduleBuilder.getContext());
-    auto varOp = moduleBuilder.create<IREE::Flow::VariableOp>(
+    auto globalOp = moduleBuilder.create<IREE::Util::GlobalOp>(
         loc, name, /*isMutable=*/true, shapeType);
-    varOp.setPrivate();
-    return varOp;
+    globalOp.setPrivate();
+    return globalOp;
   }
 
   // Derives a shape calculation function from the given entry point |funcOp|.
   FuncOp createShapeCalculationFunc(
       Location loc, StringRef namePrefix, FuncOp funcOp,
-      ArrayRef<IREE::Flow::VariableOp> inputVarOps,
-      ArrayRef<IREE::Flow::VariableOp> outputVarOps,
-      IREE::Flow::VariableOp dirtyVarOp, OpBuilder &moduleBuilder) {
+      ArrayRef<IREE::Util::GlobalOp> inputGlobalOps,
+      ArrayRef<IREE::Util::GlobalOp> outputGlobalOps,
+      IREE::Util::GlobalOp dirtyGlobalOp, OpBuilder &moduleBuilder) {
     // Clone the entire entry function with all its IR.
     auto calcFuncOp = cast<FuncOp>(moduleBuilder.clone(*funcOp.getOperation()));
     calcFuncOp.setName(namePrefix.str() + "_calculate_shapes");
@@ -190,8 +190,8 @@
     auto entryBuilder = OpBuilder::atBlockBegin(&entryBlock);
 
     // Go back and insert a check for the dirty flag.
-    auto dirtyValue = entryBuilder.createOrFold<IREE::Flow::VariableLoadOp>(
-        loc, dirtyVarOp.type(), dirtyVarOp.getName());
+    auto dirtyValue = entryBuilder.createOrFold<IREE::Util::GlobalLoadOp>(
+        loc, dirtyGlobalOp.type(), dirtyGlobalOp.getName());
     auto *recalculateBlock = calcFuncOp.addBlock();
     auto *returnBlock = calcFuncOp.addBlock();
     entryBuilder.create<CondBranchOp>(loc, dirtyValue, recalculateBlock,
@@ -207,15 +207,15 @@
         recalculateBuilder.getFunctionType(/*inputs=*/TypeRange{},
                                            /*outputs=*/TypeRange{}));
     for (auto inputValueVar :
-         llvm::zip(entryBlock.getArguments(), inputVarOps)) {
+         llvm::zip(entryBlock.getArguments(), inputGlobalOps)) {
       auto inputValue = std::get<0>(inputValueVar);
-      auto inputVarOp = std::get<1>(inputValueVar);
+      auto inputGlobalOp = std::get<1>(inputValueVar);
       auto inputPlaceholder =
           recalculateBuilder.createOrFold<IREE::Util::NullOp>(
               loc, inputValue.getType());
       auto inputShapeValue =
-          recalculateBuilder.createOrFold<IREE::Flow::VariableLoadOp>(
-              loc, inputVarOp.type(), inputVarOp.getName());
+          recalculateBuilder.createOrFold<IREE::Util::GlobalLoadOp>(
+              loc, inputGlobalOp.type(), inputGlobalOp.getName());
       auto tiedValue = recalculateBuilder.create<Shape::TieShapeOp>(
           loc, inputPlaceholder, inputShapeValue);
       inputValue.replaceAllUsesWith(tiedValue);
@@ -236,20 +236,20 @@
       // We do this per exit-site so that if the function has multiple code
       // paths that may return different shape sizes we capture them all.
       for (auto outputValueVar :
-           llvm::zip(returnOp.getOperands(), outputVarOps)) {
+           llvm::zip(returnOp.getOperands(), outputGlobalOps)) {
         auto outputValue = std::get<0>(outputValueVar);
-        auto outputVarOp = std::get<1>(outputValueVar);
+        auto outputGlobalOp = std::get<1>(outputValueVar);
         auto outputShapeValue =
             exitBuilder.createOrFold<Shape::GetRankedShapeOp>(exitLoc,
                                                               outputValue);
-        exitBuilder.create<IREE::Flow::VariableStoreOp>(
-            exitLoc, outputShapeValue, outputVarOp.getName());
+        exitBuilder.create<IREE::Util::GlobalStoreOp>(exitLoc, outputShapeValue,
+                                                      outputGlobalOp.getName());
       }
 
       // Clear the dirty flag now that the shapes have been updated.
       auto falseValue = exitBuilder.createOrFold<ConstantIntOp>(exitLoc, 0, 1);
-      exitBuilder.create<IREE::Flow::VariableStoreOp>(exitLoc, falseValue,
-                                                      dirtyVarOp.getName());
+      exitBuilder.create<IREE::Util::GlobalStoreOp>(exitLoc, falseValue,
+                                                    dirtyGlobalOp.getName());
       exitBuilder.create<ReturnOp>(exitLoc);
       returnOp.erase();
     }
@@ -327,11 +327,12 @@
                                                           dynamicDims);
   }
 
-  // Creates a function to query the |inputVarOps| at runtime by the bindings.
+  // Creates a function to query the |inputGlobalOps| at runtime by the
+  // bindings.
   //
   // func @_query_input_shape(%index : index, %shape : !util.list<index>)
   void createQueryInputShapeFunc(Location loc, StringRef namePrefix,
-                                 ArrayRef<IREE::Flow::VariableOp> inputVarOps,
+                                 ArrayRef<IREE::Util::GlobalOp> inputGlobalOps,
                                  OpBuilder &moduleBuilder) {
     auto queryFuncOp = moduleBuilder.create<FuncOp>(
         loc, namePrefix.str() + "_query_input_shape",
@@ -348,13 +349,12 @@
     auto listValue = entryBlock->getArgument(1);
 
     auto *exitBlock = buildSwitch(
-        loc, entryBlock->getArgument(0), inputVarOps.size(),
+        loc, entryBlock->getArgument(0), inputGlobalOps.size(),
         [&](size_t i, OpBuilder &caseBuilder) {
-          auto inputVarOp = inputVarOps[i];
-          auto shapeType = inputVarOp.type().cast<Shape::RankedShapeType>();
-          auto shapeValue =
-              caseBuilder.createOrFold<IREE::Flow::VariableLoadOp>(
-                  loc, inputVarOp.type(), inputVarOp.getName());
+          auto inputGlobalOp = inputGlobalOps[i];
+          auto shapeType = inputGlobalOp.type().cast<Shape::RankedShapeType>();
+          auto shapeValue = caseBuilder.createOrFold<IREE::Util::GlobalLoadOp>(
+              loc, inputGlobalOp.type(), inputGlobalOp.getName());
           packShape(loc, shapeType, shapeValue, listValue, caseBuilder);
         },
         entryBuilder);
@@ -363,12 +363,13 @@
     exitBuilder.create<ReturnOp>(loc);
   }
 
-  // Creates a function to resize |inputVarOps| and sets the |dirtyVarOp| flag.
+  // Creates a function to resize |inputGlobalOps| and sets the |dirtyGlobalOp|
+  // flag.
   //
   // func @_resize_input_shape(%index : index, %shape : !util.list<index>)
   void createResizeInputShapeFunc(Location loc, StringRef namePrefix,
-                                  ArrayRef<IREE::Flow::VariableOp> inputVarOps,
-                                  IREE::Flow::VariableOp dirtyVarOp,
+                                  ArrayRef<IREE::Util::GlobalOp> inputGlobalOps,
+                                  IREE::Util::GlobalOp dirtyGlobalOp,
                                   OpBuilder &moduleBuilder) {
     auto resizeFuncOp = moduleBuilder.create<FuncOp>(
         loc, namePrefix.str() + "_resize_input_shape",
@@ -385,31 +386,32 @@
     auto listValue = entryBlock->getArgument(1);
 
     auto *exitBlock = buildSwitch(
-        loc, entryBlock->getArgument(0), inputVarOps.size(),
+        loc, entryBlock->getArgument(0), inputGlobalOps.size(),
         [&](size_t i, OpBuilder &caseBuilder) {
-          auto inputVarOp = inputVarOps[i];
-          auto shapeType = inputVarOp.type().cast<Shape::RankedShapeType>();
+          auto inputGlobalOp = inputGlobalOps[i];
+          auto shapeType = inputGlobalOp.type().cast<Shape::RankedShapeType>();
           auto shapeValue = unpackShape(loc, shapeType, listValue, caseBuilder);
-          caseBuilder.create<IREE::Flow::VariableStoreOp>(loc, shapeValue,
-                                                          inputVarOp.getName());
+          caseBuilder.create<IREE::Util::GlobalStoreOp>(
+              loc, shapeValue, inputGlobalOp.getName());
         },
         entryBuilder);
 
     // Set the dirty flag so that shapes get recalculated as needed.
     auto exitBuilder = OpBuilder::atBlockBegin(exitBlock);
     auto trueValue = exitBuilder.createOrFold<ConstantIntOp>(loc, 1, 1);
-    exitBuilder.create<IREE::Flow::VariableStoreOp>(loc, trueValue,
-                                                    dirtyVarOp.getName());
+    exitBuilder.create<IREE::Util::GlobalStoreOp>(loc, trueValue,
+                                                  dirtyGlobalOp.getName());
     exitBuilder.create<ReturnOp>(loc);
   }
 
-  // Creates a function to query the |outputVarOps| at runtime by the bindings.
+  // Creates a function to query the |outputGlobalOps| at runtime by the
+  // bindings.
   //
   // func @_query_output_shape(%index : index, %shape : !util.list<index>)
-  void createQueryOutputShapeFunc(Location loc, StringRef namePrefix,
-                                  ArrayRef<IREE::Flow::VariableOp> outputVarOps,
-                                  FuncOp calculateShapeFuncOp,
-                                  OpBuilder &moduleBuilder) {
+  void createQueryOutputShapeFunc(
+      Location loc, StringRef namePrefix,
+      ArrayRef<IREE::Util::GlobalOp> outputGlobalOps,
+      FuncOp calculateShapeFuncOp, OpBuilder &moduleBuilder) {
     auto queryFuncOp = moduleBuilder.create<FuncOp>(
         loc, namePrefix.str() + "_query_output_shape",
         moduleBuilder.getFunctionType(/*inputs=*/
@@ -429,13 +431,12 @@
     entryBuilder.create<CallOp>(loc, calculateShapeFuncOp);
 
     auto *exitBlock = buildSwitch(
-        loc, entryBlock->getArgument(0), outputVarOps.size(),
+        loc, entryBlock->getArgument(0), outputGlobalOps.size(),
         [&](size_t i, OpBuilder &caseBuilder) {
-          auto outputVarOp = outputVarOps[i];
-          auto shapeType = outputVarOp.type().cast<Shape::RankedShapeType>();
-          auto shapeValue =
-              caseBuilder.createOrFold<IREE::Flow::VariableLoadOp>(
-                  loc, outputVarOp.type(), outputVarOp.getName());
+          auto outputGlobalOp = outputGlobalOps[i];
+          auto shapeType = outputGlobalOp.type().cast<Shape::RankedShapeType>();
+          auto shapeValue = caseBuilder.createOrFold<IREE::Util::GlobalLoadOp>(
+              loc, outputGlobalOp.type(), outputGlobalOp.getName());
           packShape(loc, shapeType, shapeValue, listValue, caseBuilder);
         },
         entryBuilder);
diff --git a/iree/compiler/Bindings/TFLite/Transforms/test/materialize_shape_support.mlir b/iree/compiler/Bindings/TFLite/Transforms/test/materialize_shape_support.mlir
index 94ab7f5..c2f0006 100644
--- a/iree/compiler/Bindings/TFLite/Transforms/test/materialize_shape_support.mlir
+++ b/iree/compiler/Bindings/TFLite/Transforms/test/materialize_shape_support.mlir
@@ -2,29 +2,29 @@
 
 // NOTE: canonicalization is run because otherwise there's just way too much IR.
 
-// CHECK-DAG: flow.variable @_tflite_dynamicEntry_input0_shape mutable : !shapex.ranked_shape<[?,8,8,3]>
-// CHECK-DAG: flow.variable @_tflite_dynamicEntry_input1_shape mutable : !shapex.ranked_shape<[?,8,8,3]>
-// CHECK-DAG: flow.variable @_tflite_dynamicEntry_output0_shape mutable : !shapex.ranked_shape<[?,8,8,3]>
-// CHECK-DAG: flow.variable @_tflite_dynamicEntry_output1_shape mutable : !shapex.ranked_shape<[?,8,8,3]>
-// CHECK-DAG: flow.variable @_tflite_dynamicEntry_shapes_dirty mutable true
+// CHECK-DAG: util.global private mutable @_tflite_dynamicEntry_input0_shape : !shapex.ranked_shape<[?,8,8,3]>
+// CHECK-DAG: util.global private mutable @_tflite_dynamicEntry_input1_shape : !shapex.ranked_shape<[?,8,8,3]>
+// CHECK-DAG: util.global private mutable @_tflite_dynamicEntry_output0_shape : !shapex.ranked_shape<[?,8,8,3]>
+// CHECK-DAG: util.global private mutable @_tflite_dynamicEntry_output1_shape : !shapex.ranked_shape<[?,8,8,3]>
+// CHECK-DAG: util.global private mutable @_tflite_dynamicEntry_shapes_dirty = true
 
 // CHECK-LABEL: func private @_tflite_dynamicEntry_calculate_shapes() {
 //  CHECK-NEXT:   %false = constant false
-//  CHECK-NEXT:   %[[IS_DIRTY:.+]] = flow.variable.load @_tflite_dynamicEntry_shapes_dirty : i1
+//  CHECK-NEXT:   %[[IS_DIRTY:.+]] = util.global.load @_tflite_dynamicEntry_shapes_dirty : i1
 //  CHECK-NEXT:   cond_br %[[IS_DIRTY]], ^bb1, ^bb2
 //  CHECK-NEXT: ^bb1:
 //  CHECK-NEXT:   %[[IN0_NULL:.+]] = util.null : tensor<?x8x8x3xf32>
-//  CHECK-NEXT:   %[[IN0_SHAPE:.+]] = flow.variable.load @_tflite_dynamicEntry_input0_shape : !shapex.ranked_shape<[?,8,8,3]>
+//  CHECK-NEXT:   %[[IN0_SHAPE:.+]] = util.global.load @_tflite_dynamicEntry_input0_shape : !shapex.ranked_shape<[?,8,8,3]>
 //  CHECK-NEXT:   %[[IN0:.+]] = shapex.tie_shape %[[IN0_NULL]], %[[IN0_SHAPE]] : tensor<?x8x8x3xf32>, !shapex.ranked_shape<[?,8,8,3]>
 //  CHECK-NEXT:   %[[IN1_NULL:.+]] = util.null : tensor<?x8x8x3xf32>
-//  CHECK-NEXT:   %[[IN1_SHAPE:.+]] = flow.variable.load @_tflite_dynamicEntry_input1_shape : !shapex.ranked_shape<[?,8,8,3]>
+//  CHECK-NEXT:   %[[IN1_SHAPE:.+]] = util.global.load @_tflite_dynamicEntry_input1_shape : !shapex.ranked_shape<[?,8,8,3]>
 //  CHECK-NEXT:   %[[IN1:.+]] = shapex.tie_shape %[[IN1_NULL]], %[[IN1_SHAPE]] : tensor<?x8x8x3xf32>, !shapex.ranked_shape<[?,8,8,3]>
 //  CHECK-NEXT:   %[[TMP:.+]]:2 = call @dynamicEntry(%[[IN0]], %[[IN1]])
 //  CHECK-NEXT:   %[[OUT0_SHAPE:.+]] = shapex.get_ranked_shape %[[TMP]]#0 : tensor<?x8x8x3xf32> -> !shapex.ranked_shape<[?,8,8,3]>
-//  CHECK-NEXT:   flow.variable.store %[[OUT0_SHAPE]], @_tflite_dynamicEntry_output0_shape : !shapex.ranked_shape<[?,8,8,3]>
+//  CHECK-NEXT:   util.global.store %[[OUT0_SHAPE]], @_tflite_dynamicEntry_output0_shape : !shapex.ranked_shape<[?,8,8,3]>
 //  CHECK-NEXT:   %[[OUT1_SHAPE:.+]] = shapex.get_ranked_shape %[[TMP]]#1 : tensor<?x8x8x3xf32> -> !shapex.ranked_shape<[?,8,8,3]>
-//  CHECK-NEXT:   flow.variable.store %[[OUT1_SHAPE]], @_tflite_dynamicEntry_output1_shape : !shapex.ranked_shape<[?,8,8,3]>
-//  CHECK-NEXT:   flow.variable.store %false, @_tflite_dynamicEntry_shapes_dirty : i1
+//  CHECK-NEXT:   util.global.store %[[OUT1_SHAPE]], @_tflite_dynamicEntry_output1_shape : !shapex.ranked_shape<[?,8,8,3]>
+//  CHECK-NEXT:   util.global.store %false, @_tflite_dynamicEntry_shapes_dirty : i1
 //  CHECK-NEXT:   return
 //  CHECK-NEXT: ^bb2:
 //  CHECK-NEXT:   return
@@ -35,7 +35,7 @@
 //       CHECK:   %[[IS_0:.+]] = cmpi eq, %[[INDEX]], %c0 : index
 //  CHECK-NEXT:   cond_br %[[IS_0]], ^bb1, ^bb2
 //  CHECK-NEXT: ^bb1:
-//  CHECK-NEXT:   %[[IN0_SHAPE:.+]] = flow.variable.load @_tflite_dynamicEntry_input0_shape : !shapex.ranked_shape<[?,8,8,3]>
+//  CHECK-NEXT:   %[[IN0_SHAPE:.+]] = util.global.load @_tflite_dynamicEntry_input0_shape : !shapex.ranked_shape<[?,8,8,3]>
 //  CHECK-NEXT:   util.list.resize %[[LIST]], %c4 : !util.list<index>
 //  CHECK-NEXT:   %[[IN0_D0:.+]] = shapex.ranked_dim %[[IN0_SHAPE]][0] : !shapex.ranked_shape<[?,8,8,3]> -> index
 //  CHECK-NEXT:   util.list.set %[[LIST]][%c0], %[[IN0_D0]] : !util.list<index>
@@ -47,7 +47,7 @@
 //  CHECK-NEXT:   %[[IS_1:.+]] = cmpi eq, %[[INDEX]], %c1 : index
 //  CHECK-NEXT:   cond_br %[[IS_1]], ^bb3, ^bb4
 //  CHECK-NEXT: ^bb3:
-//  CHECK-NEXT:   %[[IN1_SHAPE:.+]] = flow.variable.load @_tflite_dynamicEntry_input1_shape : !shapex.ranked_shape<[?,8,8,3]>
+//  CHECK-NEXT:   %[[IN1_SHAPE:.+]] = util.global.load @_tflite_dynamicEntry_input1_shape : !shapex.ranked_shape<[?,8,8,3]>
 //  CHECK-NEXT:   util.list.resize %[[LIST]], %c4 : !util.list<index>
 //  CHECK-NEXT:   %[[IN1_D0:.+]] = shapex.ranked_dim %[[IN1_SHAPE]][0] : !shapex.ranked_shape<[?,8,8,3]> -> index
 //  CHECK-NEXT:   util.list.set %[[LIST]][%c0], %[[IN1_D0]] : !util.list<index>
@@ -66,7 +66,7 @@
 //  CHECK-NEXT: ^bb1:
 //  CHECK-NEXT:   %[[IN0_D0:.+]] = util.list.get %[[LIST]][%c0] : !util.list<index>
 //  CHECK-NEXT:   %[[IN0_SHAPE:.+]] = shapex.make_ranked_shape %[[IN0_D0]] : (index) -> !shapex.ranked_shape<[?,8,8,3]>
-//  CHECK-NEXT:   flow.variable.store %[[IN0_SHAPE]], @_tflite_dynamicEntry_input0_shape : !shapex.ranked_shape<[?,8,8,3]>
+//  CHECK-NEXT:   util.global.store %[[IN0_SHAPE]], @_tflite_dynamicEntry_input0_shape : !shapex.ranked_shape<[?,8,8,3]>
 //  CHECK-NEXT:   br ^bb4
 //  CHECK-NEXT: ^bb2:
 //  CHECK-NEXT:   %[[IS_1:.+]] = cmpi eq, %[[INDEX]], %c1 : index
@@ -74,10 +74,10 @@
 //  CHECK-NEXT: ^bb3:
 //  CHECK-NEXT:   %[[IN1_D0:.+]] = util.list.get %[[LIST]][%c0] : !util.list<index>
 //  CHECK-NEXT:   %[[IN1_SHAPE:.+]] = shapex.make_ranked_shape %[[IN1_D0]] : (index) -> !shapex.ranked_shape<[?,8,8,3]>
-//  CHECK-NEXT:   flow.variable.store %[[IN1_SHAPE]], @_tflite_dynamicEntry_input1_shape : !shapex.ranked_shape<[?,8,8,3]>
+//  CHECK-NEXT:   util.global.store %[[IN1_SHAPE]], @_tflite_dynamicEntry_input1_shape : !shapex.ranked_shape<[?,8,8,3]>
 //  CHECK-NEXT:   br ^bb4
 //  CHECK-NEXT: ^bb4:
-//  CHECK-NEXT:   flow.variable.store %true, @_tflite_dynamicEntry_shapes_dirty : i1
+//  CHECK-NEXT:   util.global.store %true, @_tflite_dynamicEntry_shapes_dirty : i1
 //  CHECK-NEXT:   return
 //  CHECK-NEXT: }
 
@@ -87,7 +87,7 @@
 //  CHECK-NEXT:   %[[IS_0:.+]] = cmpi eq, %[[INDEX]], %c0 : index
 //  CHECK-NEXT:   cond_br %[[IS_0]], ^bb1, ^bb2
 //  CHECK-NEXT: ^bb1:
-//  CHECK-NEXT:   %[[OUT0_SHAPE:.+]] = flow.variable.load @_tflite_dynamicEntry_output0_shape : !shapex.ranked_shape<[?,8,8,3]>
+//  CHECK-NEXT:   %[[OUT0_SHAPE:.+]] = util.global.load @_tflite_dynamicEntry_output0_shape : !shapex.ranked_shape<[?,8,8,3]>
 //  CHECK-NEXT:   util.list.resize %[[LIST]], %c4 : !util.list<index>
 //  CHECK-NEXT:   %[[OUT0_D0:.+]] = shapex.ranked_dim %[[OUT0_SHAPE]][0] : !shapex.ranked_shape<[?,8,8,3]> -> index
 //  CHECK-NEXT:   util.list.set %[[LIST]][%c0], %[[OUT0_D0]] : !util.list<index>
@@ -99,7 +99,7 @@
 //  CHECK-NEXT:   %[[IS_1:.+]] = cmpi eq, %[[INDEX]], %c1 : index
 //  CHECK-NEXT:   cond_br %[[IS_1]], ^bb3, ^bb4
 //  CHECK-NEXT: ^bb3:
-//  CHECK-NEXT:   %[[OUT1_SHAPE:.+]] = flow.variable.load @_tflite_dynamicEntry_output1_shape : !shapex.ranked_shape<[?,8,8,3]>
+//  CHECK-NEXT:   %[[OUT1_SHAPE:.+]] = util.global.load @_tflite_dynamicEntry_output1_shape : !shapex.ranked_shape<[?,8,8,3]>
 //  CHECK-NEXT:   util.list.resize %[[LIST]], %c4 : !util.list<index>
 //  CHECK-NEXT:   %[[OUT1_D0:.+]] = shapex.ranked_dim %[[OUT1_SHAPE]][0] : !shapex.ranked_shape<[?,8,8,3]> -> index
 //  CHECK-NEXT:   util.list.set %[[LIST]][%c0], %[[OUT1_D0]] : !util.list<index>
diff --git a/iree/compiler/Codegen/Common/DemoteF32ToF16.cpp b/iree/compiler/Codegen/Common/DemoteF32ToF16.cpp
index 55bebcb..39f17cf 100644
--- a/iree/compiler/Codegen/Common/DemoteF32ToF16.cpp
+++ b/iree/compiler/Codegen/Common/DemoteF32ToF16.cpp
@@ -9,7 +9,7 @@
 
 #include "iree/compiler/Codegen/PassDetail.h"
 #include "iree/compiler/Codegen/Passes.h"
-#include "iree/compiler/Dialect/Flow/IR/FlowOps.h"
+#include "iree/compiler/Dialect/Util/IR/UtilOps.h"
 #include "iree/compiler/Dialect/Util/IR/UtilTypes.h"
 #include "llvm/ADT/APFloat.h"
 #include "llvm/ADT/STLExtras.h"
@@ -138,8 +138,8 @@
     ConversionTarget target(*context);
     // Operations are legal if they don't contain any illegal type.
     target.markUnknownOpDynamicallyLegal([](Operation *op) {
-      if (auto varOp = dyn_cast<IREE::Flow::VariableOp>(op)) {
-        return !isIllegalType(varOp.type());
+      if (auto globalOp = dyn_cast<IREE::Util::GlobalOp>(op)) {
+        return !isIllegalType(globalOp.type());
       }
       if (auto funcOp = dyn_cast<FuncOp>(op)) {
         for (Type type : funcOp.getType().getInputs()) {
diff --git a/iree/compiler/Codegen/Common/test/f32Tof16.mlir b/iree/compiler/Codegen/Common/test/f32Tof16.mlir
index 32bec08..d938cb5 100644
--- a/iree/compiler/Codegen/Common/test/f32Tof16.mlir
+++ b/iree/compiler/Codegen/Common/test/f32Tof16.mlir
@@ -1,31 +1,31 @@
 // RUN: iree-opt -split-input-file -iree-convert-f32-to-f16 %s | IreeFileCheck %s
 
-//       CHECK: flow.variable {{.*}} : tensor<4xf16>
+//       CHECK: util.global {{.*}} : tensor<4xf16>
 // CHECK-LABEL: func @simple_f32() -> tensor<4xf16>
-//  CHECK-NEXT: %{{.*}} = flow.variable.address @__global : !util.ptr<tensor<4xf16>>
-//  CHECK-NEXT: %{{.*}} = flow.variable.load.indirect %{{.*}} : !util.ptr<tensor<4xf16>> -> tensor<4xf16>
+//  CHECK-NEXT: %{{.*}} = util.global.address @__global : !util.ptr<tensor<4xf16>>
+//  CHECK-NEXT: %{{.*}} = util.global.load.indirect %{{.*}} : !util.ptr<tensor<4xf16>> -> tensor<4xf16>
 //  CHECK-NEXT: return %{{.*}} : tensor<4xf16>
 module {
-  flow.variable @"__global" dense<"0x000020410000A040000020410000A040"> : tensor<4xf32> attributes {sym_visibility = "private"}
+  util.global private @"__global" = dense<"0x000020410000A040000020410000A040"> : tensor<4xf32>
   func @simple_f32() -> (tensor<4xf32>) {
-    %0 = flow.variable.address @"__global" : !util.ptr<tensor<4xf32>>
-    %1 = flow.variable.load.indirect %0 : !util.ptr<tensor<4xf32>> -> tensor<4xf32>
+    %0 = util.global.address @"__global" : !util.ptr<tensor<4xf32>>
+    %1 = util.global.load.indirect %0 : !util.ptr<tensor<4xf32>> -> tensor<4xf32>
     return %1 : tensor<4xf32>
   }
 }
 
 // -----
 
-// CHECK: flow.variable
+// CHECK: util.global
 // CHECK-NOT: f32
 // CHECK-LABEL: func @nested_region_f32()
 // CHECK-NOT: f32
 // CHECK: return %{{.*}} : tensor<4xf16>
 module {
-  flow.variable @"__global" dense<"0x000020410000A040000020410000A040"> : tensor<4xf32> attributes {sym_visibility = "private"}
+  util.global private @"__global" = dense<"0x000020410000A040000020410000A040"> : tensor<4xf32>
   func @nested_region_f32() -> (tensor<4xf32>) {
-    %0 = flow.variable.address @"__iree_flow_bert/embeddings/FakeLayerNorm/beta" : !util.ptr<tensor<4xf32>>
-    %1 = flow.variable.load.indirect %0 : !util.ptr<tensor<4xf32>> -> tensor<4xf32>
+    %0 = util.global.address @"__global" : !util.ptr<tensor<4xf32>>
+    %1 = util.global.load.indirect %0 : !util.ptr<tensor<4xf32>> -> tensor<4xf32>
     %2 = "mhlo.broadcast_in_dim"(%1) {broadcast_dimensions = dense<0> : tensor<1xi64>} : (tensor<4xf32>) -> tensor<4x4xf32>
     %4 = mhlo.constant dense<0xFF800000> : tensor<f32>
     %3 = "mhlo.reduce"(%2, %4) ( {
diff --git a/iree/compiler/Dialect/Flow/IR/FlowBase.td b/iree/compiler/Dialect/Flow/IR/FlowBase.td
index df488d2..5bcb8e4 100644
--- a/iree/compiler/Dialect/Flow/IR/FlowBase.td
+++ b/iree/compiler/Dialect/Flow/IR/FlowBase.td
@@ -84,8 +84,8 @@
 def FLOW_Tensor : TypeAlias<AnyRankedTensor>;
 
 def FLOW_ExecutableRefAttr : AliasedSymbolRefAttr;
-def FLOW_VariableRefAttr : AliasedSymbolRefAttr;
-def FLOW_VariablePtr : AnyPtrOf<[FLOW_Tensor, FLOW_PrimitiveType]>;
+def FLOW_GlobalRefAttr : AliasedSymbolRefAttr;
+def FLOW_GlobalPtr : Util_AnyPtrOf<[FLOW_Tensor, FLOW_PrimitiveType]>;
 
 def FLOW_TensorAccessCanReadPred : CPred<[{
   $_self.cast<IREE::Flow::DispatchTensorType>().getAccess() ==
diff --git a/iree/compiler/Dialect/Flow/IR/FlowOpFolders.cpp b/iree/compiler/Dialect/Flow/IR/FlowOpFolders.cpp
index 4b4680d..c4c8b5f 100644
--- a/iree/compiler/Dialect/Flow/IR/FlowOpFolders.cpp
+++ b/iree/compiler/Dialect/Flow/IR/FlowOpFolders.cpp
@@ -111,8 +111,8 @@
 
   // For loaded variables, check whether it's mutable. Immutable variables will
   // be aggregated into one read-only buffer.
-  if (auto varLoadOp = operand.getDefiningOp<VariableLoadOp>()) {
-    return !varLoadOp.getLoadedVariable().is_mutable();
+  if (auto loadOp = operand.getDefiningOp<IREE::Util::GlobalLoadOp>()) {
+    return loadOp.isGlobalImmutable();
   }
 
   return false;
@@ -235,147 +235,6 @@
 }
 
 //===----------------------------------------------------------------------===//
-// Variables
-//===----------------------------------------------------------------------===//
-
-namespace {
-
-/// Converts variable initializer functions that evaluate to a constant to a
-/// specified initial value.
-struct InlineConstVariableOpInitializer : public OpRewritePattern<VariableOp> {
-  using OpRewritePattern<VariableOp>::OpRewritePattern;
-
-  LogicalResult matchAndRewrite(VariableOp op,
-                                PatternRewriter &rewriter) const override {
-    if (!op.initializer()) return failure();
-    auto *symbolOp =
-        SymbolTable::lookupNearestSymbolFrom(op, op.initializer().getValue());
-    auto initializer = cast<mlir::FuncOp>(symbolOp);
-    if (initializer.getBlocks().size() == 1 &&
-        initializer.getBlocks().front().getOperations().size() == 2 &&
-        isa<mlir::ReturnOp>(
-            initializer.getBlocks().front().getOperations().back())) {
-      auto &primaryOp = initializer.getBlocks().front().getOperations().front();
-      Attribute constResult;
-      if (matchPattern(primaryOp.getResult(0), m_Constant(&constResult))) {
-        rewriter.replaceOpWithNewOp<VariableOp>(
-            op, op.sym_name(), op.is_mutable(), op.type(), constResult);
-        return success();
-      }
-    }
-    return failure();
-  }
-};
-
-}  // namespace
-
-void VariableOp::getCanonicalizationPatterns(OwningRewritePatternList &results,
-                                             MLIRContext *context) {
-  results.insert<InlineConstVariableOpInitializer>(context);
-}
-
-OpFoldResult VariableLoadOp::fold(ArrayRef<Attribute> operands) {
-  auto variableOp = dyn_cast_or_null<VariableOp>(
-      SymbolTable::lookupNearestSymbolFrom(*this, variable()));
-  if (!variableOp) return {};
-  if (variableOp->getAttr("noinline")) {
-    // Inlining of the constant has been disabled.
-    return {};
-  } else if (variableOp.is_mutable()) {
-    // We can't inline mutable variables as they may be changed at any time.
-    // There may still be other folders/canonicalizers that can help (such as
-    // store-forwarding).
-    return {};
-  } else if (!variableOp.initial_value()) {
-    // Uninitialized variables (or those with initializers) can't be folded as
-    // we don't yet know the value. InlineConstVariableOpInitializer may help.
-    return {};
-  }
-  return variableOp.initial_value().getValue();
-}
-
-namespace {
-
-class PropagateVariableLoadAddress
-    : public OpRewritePattern<VariableLoadIndirectOp> {
-  using OpRewritePattern::OpRewritePattern;
-
- public:
-  LogicalResult matchAndRewrite(VariableLoadIndirectOp op,
-                                PatternRewriter &rewriter) const override {
-    if (auto addressOp = dyn_cast_or_null<VariableAddressOp>(
-            op.variable().getDefiningOp())) {
-      rewriter.replaceOpWithNewOp<VariableLoadOp>(op, op.result().getType(),
-                                                  addressOp.variable());
-      return success();
-    }
-    return failure();
-  }
-};
-
-}  // namespace
-
-void VariableLoadIndirectOp::getCanonicalizationPatterns(
-    OwningRewritePatternList &results, MLIRContext *context) {
-  results.insert<PropagateVariableLoadAddress>(context);
-}
-
-namespace {
-
-/// Erases flow.variable.store ops that are no-ops.
-/// This can happen if there was a variable load, some DCE'd usage, and a
-/// store back to the same variable: we want to be able to elide the entire load
-/// and store.
-struct EraseUnusedVariableStoreOp : public OpRewritePattern<VariableStoreOp> {
-  using OpRewritePattern<VariableStoreOp>::OpRewritePattern;
-
-  LogicalResult matchAndRewrite(VariableStoreOp op,
-                                PatternRewriter &rewriter) const override {
-    if (auto loadOp =
-            dyn_cast_or_null<VariableLoadOp>(op.value().getDefiningOp())) {
-      if (loadOp.variable() == op.variable()) {
-        rewriter.eraseOp(op);
-        return success();
-      }
-    }
-    return failure();
-  }
-};
-
-}  // namespace
-
-void VariableStoreOp::getCanonicalizationPatterns(
-    OwningRewritePatternList &results, MLIRContext *context) {
-  results.insert<EraseUnusedVariableStoreOp>(context);
-}
-
-namespace {
-
-class PropagateVariableStoreAddress
-    : public OpRewritePattern<VariableStoreIndirectOp> {
-  using OpRewritePattern::OpRewritePattern;
-
- public:
-  LogicalResult matchAndRewrite(VariableStoreIndirectOp op,
-                                PatternRewriter &rewriter) const override {
-    if (auto addressOp = dyn_cast_or_null<VariableAddressOp>(
-            op.variable().getDefiningOp())) {
-      rewriter.replaceOpWithNewOp<VariableStoreOp>(op, op.value(),
-                                                   addressOp.variable());
-      return success();
-    }
-    return failure();
-  }
-};
-
-}  // namespace
-
-void VariableStoreIndirectOp::getCanonicalizationPatterns(
-    OwningRewritePatternList &results, MLIRContext *context) {
-  results.insert<PropagateVariableStoreAddress>(context);
-}
-
-//===----------------------------------------------------------------------===//
 // Dispatch ops
 //===----------------------------------------------------------------------===//
 
diff --git a/iree/compiler/Dialect/Flow/IR/FlowOpUtils.cpp b/iree/compiler/Dialect/Flow/IR/FlowOpUtils.cpp
index 9279c94..16dd347 100644
--- a/iree/compiler/Dialect/Flow/IR/FlowOpUtils.cpp
+++ b/iree/compiler/Dialect/Flow/IR/FlowOpUtils.cpp
@@ -149,11 +149,9 @@
   if (auto constantOp = dyn_cast<ConstantOp>(definingOp)) {
     // Constants are perfect!
     return isConstantSmall(constantOp);
-  } else if (auto variableLoadOp =
-                 dyn_cast<IREE::Flow::VariableLoadOp>(definingOp)) {
+  } else if (auto loadOp = dyn_cast<IREE::Util::GlobalLoadOp>(definingOp)) {
     // If the variable is immutable then we can inline the reference to it.
-    auto variableOp = variableLoadOp.getLoadedVariable();
-    return !variableOp.is_mutable();
+    return loadOp.isGlobalImmutable();
   }
   return false;
 }
diff --git a/iree/compiler/Dialect/Flow/IR/FlowOps.cpp b/iree/compiler/Dialect/Flow/IR/FlowOps.cpp
index 050e163..501ad88 100644
--- a/iree/compiler/Dialect/Flow/IR/FlowOps.cpp
+++ b/iree/compiler/Dialect/Flow/IR/FlowOps.cpp
@@ -303,251 +303,6 @@
 }
 
 //===----------------------------------------------------------------------===//
-// flow.variable
-//===----------------------------------------------------------------------===//
-
-static ParseResult parseVariableOp(OpAsmParser &parser,
-                                   OperationState *result) {
-  StringAttr nameAttr;
-  if (failed(parser.parseSymbolName(nameAttr,
-                                    mlir::SymbolTable::getSymbolAttrName(),
-                                    result->attributes))) {
-    return failure();
-  }
-
-  if (succeeded(parser.parseOptionalKeyword("mutable"))) {
-    result->addAttribute("is_mutable", UnitAttr::get(result->getContext()));
-  }
-
-  if (succeeded(parser.parseOptionalKeyword("init"))) {
-    FlatSymbolRefAttr initializerAttr;
-    if (failed(parser.parseLParen()) ||
-        failed(parser.parseAttribute(initializerAttr, "initializer",
-                                     result->attributes)) ||
-        failed(parser.parseRParen())) {
-      return failure();
-    }
-  }
-
-  if (failed(parser.parseOptionalColon())) {
-    Attribute initialValueAttr;
-    if (failed(parser.parseAttribute(initialValueAttr, "initial_value",
-                                     result->attributes))) {
-      return failure();
-    }
-    result->addAttribute("type", TypeAttr::get(initialValueAttr.getType()));
-  } else {
-    Type type;
-    if (failed(parser.parseType(type))) {
-      return failure();
-    }
-    result->addAttribute("type", TypeAttr::get(type));
-  }
-
-  if (failed(parser.parseOptionalAttrDictWithKeyword(result->attributes))) {
-    return failure();
-  }
-
-  return success();
-}
-
-static void printVariableOp(OpAsmPrinter &p, VariableOp op) {
-  p << op.getOperationName() << ' ';
-  p.printSymbolName(op.sym_name());
-  if (op.is_mutable()) {
-    p << " mutable";
-  }
-  if (op.initializer().hasValue()) {
-    p << " init(";
-    p.printSymbolName(op.initializer().getValue());
-    p << ')';
-  }
-  if (op.initial_value().hasValue()) {
-    p << ' ';
-    p.printAttribute(op.initial_value().getValue());
-  } else {
-    p << " : ";
-    p.printType(op.type());
-  }
-  p.printOptionalAttrDictWithKeyword(op->getAttrs(), /*elidedAttrs=*/{
-                                         "sym_name",
-                                         "type",
-                                         "is_mutable",
-                                         "initializer",
-                                         "initial_value",
-                                     });
-}
-
-static LogicalResult verifyVariableOp(VariableOp op) {
-  if (op.initializer().hasValue() && op.initial_value().hasValue()) {
-    return op.emitOpError()
-           << "variables can have either an initializer or an initial value";
-  } else if (op.initializer().hasValue()) {
-    // Ensure initializer returns the same type as the variable.
-    auto *symbolOp =
-        SymbolTable::lookupNearestSymbolFrom(op, op.initializer().getValue());
-    if (!symbolOp) {
-      return op.emitOpError() << "initializer function "
-                              << op.initializer().getValue() << " not found";
-    }
-    auto initializerOp = dyn_cast<mlir::FuncOp>(symbolOp);
-    if (initializerOp.getNumArguments() != 0 ||
-        initializerOp.getNumResults() != 1 ||
-        initializerOp.getType().getResult(0) != op.type()) {
-      return op.emitOpError()
-             << "initializer type mismatch; variable " << op.sym_name()
-             << " is " << op.type() << " but initializer function "
-             << initializerOp.getName() << " is " << initializerOp.getType();
-    }
-  } else if (op.initial_value().hasValue()) {
-    // Ensure the value is something we can store in the variable
-    if (!isVariableTypeCompatible(op.type(), op.initial_value()->getType())) {
-      return op.emitOpError()
-             << "initial value type mismatch; variable " << op.sym_name()
-             << " is " << op.type() << " but initial value provided is "
-             << op.initial_value()->getType();
-    }
-  }
-  return success();
-}
-
-void VariableOp::build(OpBuilder &builder, OperationState &state,
-                       StringRef name, bool isMutable, FuncOp initializer,
-                       ArrayRef<NamedAttribute> attrs) {
-  state.addAttribute(SymbolTable::getSymbolAttrName(),
-                     builder.getStringAttr(name));
-  if (isMutable) {
-    state.addAttribute("is_mutable", builder.getUnitAttr());
-  }
-  state.addAttribute("initializer", builder.getSymbolRefAttr(initializer));
-  state.addAttribute("type", TypeAttr::get(initializer.getType().getResult(0)));
-  state.attributes.append(attrs.begin(), attrs.end());
-}
-
-void VariableOp::build(OpBuilder &builder, OperationState &result,
-                       StringRef name, bool isMutable, Type type,
-                       Attribute initialValue, ArrayRef<NamedAttribute> attrs) {
-  result.addAttribute(SymbolTable::getSymbolAttrName(),
-                      builder.getStringAttr(name));
-  if (isMutable) {
-    result.addAttribute("is_mutable", builder.getUnitAttr());
-  }
-  result.addAttribute("initial_value", initialValue);
-  result.addAttribute("type", TypeAttr::get(type));
-  result.attributes.append(attrs.begin(), attrs.end());
-}
-
-void VariableOp::build(OpBuilder &builder, OperationState &result,
-                       StringRef name, bool isMutable, Type type,
-                       ArrayRef<NamedAttribute> attrs) {
-  result.addAttribute(SymbolTable::getSymbolAttrName(),
-                      builder.getStringAttr(name));
-  if (isMutable) {
-    result.addAttribute("is_mutable", builder.getUnitAttr());
-  }
-  result.addAttribute("type", TypeAttr::get(type));
-  result.attributes.append(attrs.begin(), attrs.end());
-}
-
-//===----------------------------------------------------------------------===//
-// flow.variable.load
-//===----------------------------------------------------------------------===//
-
-void VariableLoadOp::build(OpBuilder &builder, OperationState &state,
-                           VariableOp variableOp,
-                           ArrayRef<NamedAttribute> attrs) {
-  state.addTypes({variableOp.type()});
-  state.addAttribute("variable", builder.getSymbolRefAttr(variableOp));
-  state.attributes.append(attrs.begin(), attrs.end());
-}
-
-void VariableLoadOp::getEffects(
-    SmallVectorImpl<MemoryEffects::EffectInstance> &effects) {
-  // HACK: works around the lack of symbol side effects in mlir by only saying
-  // we have a side-effect if the variable we are loading is mutable.
-  auto *symbolOp = SymbolTable::lookupNearestSymbolFrom(*this, variable());
-  assert(symbolOp);
-  auto variableOp = dyn_cast<VariableOp>(symbolOp);
-  if (variableOp.is_mutable()) {
-    effects.emplace_back(MemoryEffects::Read::get());
-  }
-}
-
-static LogicalResult verifyVariableLoadOp(VariableLoadOp &op) {
-  auto *symbolOp = SymbolTable::lookupNearestSymbolFrom(op, op.variable());
-  if (!symbolOp) {
-    return op.emitOpError() << "undefined variable: " << op.variable();
-  }
-  auto variableOp = dyn_cast<VariableOp>(symbolOp);
-  auto loadType = op.result().getType();
-  if (!isVariableTypeCompatible(variableOp.type(), loadType)) {
-    return op.emitOpError()
-           << "variable type mismatch; variable " << op.variable() << " is "
-           << variableOp.type() << " but load is " << loadType;
-  }
-  return success();
-}
-
-VariableOp VariableLoadOp::getLoadedVariable() {
-  return SymbolTable::lookupNearestSymbolFrom<IREE::Flow::VariableOp>(
-      getOperation()->getParentOp(), variable());
-}
-
-//===----------------------------------------------------------------------===//
-// flow.variable.load.indirect
-//===----------------------------------------------------------------------===//
-
-static LogicalResult verifyVariableLoadIndirectOp(VariableLoadIndirectOp &op) {
-  auto variableType =
-      op.variable().getType().cast<IREE::Util::PtrType>().getTargetType();
-  auto loadType = op.result().getType();
-  if (!isVariableTypeCompatible(variableType, loadType)) {
-    return op.emitOpError() << "variable type mismatch; variable pointer is "
-                            << variableType << " but load is " << loadType;
-  }
-  return success();
-}
-
-//===----------------------------------------------------------------------===//
-// flow.variable.store
-//===----------------------------------------------------------------------===//
-
-static LogicalResult verifyVariableStoreOp(VariableStoreOp &op) {
-  auto *symbolOp = SymbolTable::lookupNearestSymbolFrom(op, op.variable());
-  if (!symbolOp) {
-    return op.emitOpError() << "undefined variable: " << op.variable();
-  }
-  auto variableOp = dyn_cast<VariableOp>(symbolOp);
-  auto storeType = op.value().getType();
-  if (!isVariableTypeCompatible(variableOp.type(), storeType)) {
-    return op.emitOpError()
-           << "variable type mismatch; variable " << op.variable() << " is "
-           << variableOp.type() << " but store is " << storeType;
-  }
-  if (!variableOp.is_mutable()) {
-    return op.emitOpError() << "variable " << op.variable()
-                            << " is not mutable and cannot be stored to";
-  }
-  return success();
-}
-
-//===----------------------------------------------------------------------===//
-// flow.variable.store.indirect
-//===----------------------------------------------------------------------===//
-
-static LogicalResult verifyVariableStoreIndirectOp(
-    VariableStoreIndirectOp &op) {
-  auto variableType =
-      op.variable().getType().cast<IREE::Util::PtrType>().getTargetType();
-  auto storeType = op.value().getType();
-  if (!isVariableTypeCompatible(variableType, storeType)) {
-    return op.emitOpError() << "variable type mismatch; variable pointer is "
-                            << variableType << " but store is " << storeType;
-  }
-  return success();
-}
-
-//===----------------------------------------------------------------------===//
 // flow.dispatch.tensor.load
 //===----------------------------------------------------------------------===//
 
@@ -1383,7 +1138,7 @@
   if (auto constantOp = dyn_cast<ConstantOp>(op)) {
     return constantOp.getType().isIntOrIndexOrFloat();
   }
-  if (auto loadOp = dyn_cast<VariableLoadOp>(op)) {
+  if (auto loadOp = dyn_cast<IREE::Util::GlobalLoadOp>(op)) {
     // Only allow loads of immutable variables to move into the stream.
     // As they are immutable it's always safe to do so as no synchronization at
     // the stream entry/exit boundary is required.
@@ -1391,9 +1146,7 @@
     // Loads of mutable variables may sometimes be safe to move in as well
     // however that is best done when we have better cross-stream
     // synchronization support and can make those guarantees structurally.
-    auto variableOp =
-        SymbolTable::lookupNearestSymbolFrom<VariableOp>(op, loadOp.variable());
-    return variableOp.is_mutable() == false;
+    return loadOp.isGlobalImmutable();
   }
   return false;
 }
diff --git a/iree/compiler/Dialect/Flow/IR/FlowOps.h b/iree/compiler/Dialect/Flow/IR/FlowOps.h
index 1da0eb9..e1d1230 100644
--- a/iree/compiler/Dialect/Flow/IR/FlowOps.h
+++ b/iree/compiler/Dialect/Flow/IR/FlowOps.h
@@ -13,6 +13,7 @@
 #include "iree/compiler/Dialect/Flow/IR/FlowTypes.h"
 #include "iree/compiler/Dialect/Shape/IR/ShapeDialect.h"
 #include "iree/compiler/Dialect/Shape/IR/ShapeTypes.h"
+#include "iree/compiler/Dialect/Util/IR/UtilOps.h"
 #include "iree/compiler/Dialect/Util/IR/UtilTraits.h"
 #include "iree/compiler/Dialect/Util/IR/UtilTypes.h"
 #include "mlir/IR/Attributes.h"
diff --git a/iree/compiler/Dialect/Flow/IR/FlowOps.td b/iree/compiler/Dialect/Flow/IR/FlowOps.td
index feb024c..3f5e724 100644
--- a/iree/compiler/Dialect/Flow/IR/FlowOps.td
+++ b/iree/compiler/Dialect/Flow/IR/FlowOps.td
@@ -21,153 +21,6 @@
     FLOW_Op<mnemonic, !listconcat(traits, [NoSideEffect])>;
 
 //===----------------------------------------------------------------------===//
-// Variables
-//===----------------------------------------------------------------------===//
-
-def FLOW_VariableOp : FLOW_Op<"variable", [
-  Symbol,
-]> {
-  let summary = [{stateful variable declaration}];
-  let description = [{
-    Declares a persistent variable that maintains its value.
-  }];
-
-  let arguments = (ins
-    StrAttr:$sym_name,
-    // TODO(benvanik): verify AnyRankedTensor.
-    TypeAttr:$type,
-    UnitAttr:$is_mutable,
-    // TODO(benvanik): verify matches $type.
-    OptionalAttr<FlatSymbolRefAttr>:$initializer,
-    // TODO(benvanik): verify matches $type.
-    OptionalAttr<AnyAttr>:$initial_value
-  );
-
-  let skipDefaultBuilders = 1;
-  let builders = [
-    OpBuilder<(ins "StringRef":$name, "bool":$isMutable,
-      "mlir::FuncOp":$initializer,
-      CArg<"ArrayRef<NamedAttribute>", "{}">:$attrs)>,
-    OpBuilder<(ins "StringRef":$name, "bool":$isMutable, "Type":$type,
-      "Attribute":$initialValue,
-      CArg<"ArrayRef<NamedAttribute>", "{}">:$attrs)>,
-    OpBuilder<(ins "StringRef":$name, "bool":$isMutable, "Type":$type,
-      CArg<"ArrayRef<NamedAttribute>", "{}">:$attrs)>,
-  ];
-
-  let verifier = [{ return verifyVariableOp(*this); }];
-
-  let hasCanonicalizer = 1;
-}
-
-def FLOW_VariableAddressOp : FLOW_PureOp<"variable.address"> {
-  let summary = [{returns an address reference to a variable}];
-  let description = [{
-    Returns the address of a variable as a typed reference. Can be used with the
-    variable load and store indirect ops.
-  }];
-
-  let arguments = (ins
-    FLOW_VariableRefAttr:$variable
-  );
-  let results = (outs
-    FLOW_VariablePtr:$result
-  );
-
-  let assemblyFormat = "$variable attr-dict `:` type($result)";
-}
-
-def FLOW_VariableLoadOp : FLOW_Op<"variable.load", [
-  // HACK: works around the lack of symbol side effects in C++.
-  DeclareOpInterfaceMethods<MemoryEffectsOpInterface>,
-]> {
-  let summary = [{loads a value from a global variable}];
-  let description = [{
-    Returns a copy of the variable value.
-  }];
-
-  let arguments = (ins
-    Arg<FLOW_VariableRefAttr, "", [MemRead]>:$variable
-  );
-  let results = (outs
-    AnyType:$result
-  );
-
-  let assemblyFormat = "$variable attr-dict `:` type($result)";
-
-  let builders = [
-    OpBuilder<(ins "IREE::Flow::VariableOp":$variableOp,
-                   CArg<"ArrayRef<NamedAttribute>", "{}">:$attributes)>,
-  ];
-
-  let verifier = [{ return verifyVariableLoadOp(*this); }];
-
-  let hasFolder = 1;
-
-  let extraClassDeclaration = [{
-    IREE::Flow::VariableOp getLoadedVariable();
-  }];
-}
-
-def FLOW_VariableLoadIndirectOp : FLOW_Op<"variable.load.indirect"> {
-  let summary = [{loads a value from a global variable}];
-  let description = [{
-    Returns a copy of the variable value.
-  }];
-
-  let arguments = (ins
-    FLOW_VariablePtr:$variable
-  );
-  let results = (outs
-    AnyType:$result
-  );
-
-  let assemblyFormat = "$variable attr-dict `:` type($variable) `->` type($result)";
-
-  let verifier = [{ return verifyVariableLoadIndirectOp(*this); }];
-
-  let hasCanonicalizer = 1;
-}
-
-def FLOW_VariableStoreOp : FLOW_Op<"variable.store"> {
-  let summary = [{stores a value into a global variable}];
-  let description = [{
-    Stores a copy of the value into a variable.
-  }];
-
-  let arguments = (ins
-    AnyType:$value,
-    Arg<FLOW_VariableRefAttr, "", [MemWrite]>:$variable
-  );
-
-  let assemblyFormat = "$value `,` $variable attr-dict `:` type($value)";
-
-  let verifier = [{ return verifyVariableStoreOp(*this); }];
-
-  let hasCanonicalizer = 1;
-}
-
-def FLOW_VariableStoreIndirectOp : FLOW_Op<"variable.store.indirect"> {
-  let summary = [{stores a value into a global variable}];
-  let description = [{
-    Stores a copy of the value into a variable.
-  }];
-
-  let arguments = (ins
-    AnyType:$value,
-    FLOW_VariablePtr:$variable
-  );
-
-  let assemblyFormat = "$value `,` $variable attr-dict `:` type($value) `->` type($variable)";
-
-  let verifier = [{ return verifyVariableStoreIndirectOp(*this); }];
-
-  let hasCanonicalizer = 1;
-}
-
-// TODO(benvanik): additional resource variable ops (like scatter/gather).
-
-//===----------------------------------------------------------------------===//
 // Partitioned regions
 //===----------------------------------------------------------------------===//
 
diff --git a/iree/compiler/Dialect/Flow/IR/test/BUILD b/iree/compiler/Dialect/Flow/IR/test/BUILD
index ec80291..e1fded1 100644
--- a/iree/compiler/Dialect/Flow/IR/test/BUILD
+++ b/iree/compiler/Dialect/Flow/IR/test/BUILD
@@ -27,8 +27,6 @@
             "tensor_folding.mlir",
             "tensor_ops.mlir",
             "types.mlir",
-            "variable_folding.mlir",
-            "variable_ops.mlir",
         ],
         include = ["*.mlir"],
     ),
diff --git a/iree/compiler/Dialect/Flow/IR/test/CMakeLists.txt b/iree/compiler/Dialect/Flow/IR/test/CMakeLists.txt
index 7ad3dd3..4f591ac 100644
--- a/iree/compiler/Dialect/Flow/IR/test/CMakeLists.txt
+++ b/iree/compiler/Dialect/Flow/IR/test/CMakeLists.txt
@@ -24,8 +24,6 @@
     "tensor_folding.mlir"
     "tensor_ops.mlir"
     "types.mlir"
-    "variable_folding.mlir"
-    "variable_ops.mlir"
   DATA
     iree::tools::IreeFileCheck
     iree::tools::iree-opt
diff --git a/iree/compiler/Dialect/Flow/IR/test/stream_folding.mlir b/iree/compiler/Dialect/Flow/IR/test/stream_folding.mlir
index b357d60..4b177ac 100644
--- a/iree/compiler/Dialect/Flow/IR/test/stream_folding.mlir
+++ b/iree/compiler/Dialect/Flow/IR/test/stream_folding.mlir
@@ -142,8 +142,8 @@
       (%arg0: tensor<2x2xi32>) -> tensor<4x4xi32> {
     %c4 = constant 4 : index
     %c1 = constant 1 : index
-    // CHECK: %[[LOAD:.+]] = flow.variable.load @_large_const
-    %5 = flow.variable.load @_large_const : tensor<4x4xi32>
+    // CHECK: %[[LOAD:.+]] = util.global.load @_large_const
+    %5 = util.global.load @_large_const : tensor<4x4xi32>
     // CHECK: %[[CLONE:.+]] = flow.tensor.clone %[[LOAD]]
     // CHECK: flow.dispatch @pad_dispatch::@pad_dispatch[{{.+}}](%{{.+}}, %[[CLONE]])
     %6 = flow.dispatch @pad_dispatch::@pad_dispatch[%c4, %c4, %c1](%arg0, %5) : (tensor<2x2xi32>, tensor<4x4xi32>) -> %5
@@ -152,7 +152,7 @@
   return %4 : tensor<4x4xi32>
 }
 
-flow.variable @_large_const dense<0> : tensor<4x4xi32> attributes {noinline, sym_visibility = "private"}
+util.global private @_large_const {noinline} = dense<0> : tensor<4x4xi32>
 
 // -----
 
@@ -161,8 +161,8 @@
   %4 = flow.ex.stream.fragment(%input) : (tensor<2xi32>) -> tensor<7xi32> =
       (%arg0: tensor<2xi32>) -> tensor<7xi32> {
     %c3 = constant 3 : index
-    // CHECK: %[[LOAD:.+]] = flow.variable.load @_large_const
-    %5 = flow.variable.load @_large_const : tensor<7xi32>
+    // CHECK: %[[LOAD:.+]] = util.global.load @_large_const
+    %5 = util.global.load @_large_const : tensor<7xi32>
     // CHECK: %[[CLONE:.+]] = flow.tensor.clone %[[LOAD]]
     // CHECK: flow.tensor.update %{{.+}}, %[[CLONE]]
     %6 = flow.tensor.update %arg0, %5[%c3] : tensor<2xi32> -> tensor<7xi32>
@@ -171,4 +171,4 @@
   return %4 : tensor<7xi32>
 }
 
-flow.variable @_large_const dense<0> : tensor<7xi32> attributes {noinline, sym_visibility = "private"}
+util.global private @_large_const {noinline} = dense<0> : tensor<7xi32>
diff --git a/iree/compiler/Dialect/Flow/IR/test/variable_folding.mlir b/iree/compiler/Dialect/Flow/IR/test/variable_folding.mlir
deleted file mode 100644
index 3482898..0000000
--- a/iree/compiler/Dialect/Flow/IR/test/variable_folding.mlir
+++ /dev/null
@@ -1,74 +0,0 @@
-// Tests folding and canonicalization of variable ops.
-
-// RUN: iree-opt -split-input-file -canonicalize %s | iree-opt -split-input-file | IreeFileCheck %s
-
-// CHECK: flow.variable @v_initialized dense<4> : tensor<4xi32>
-flow.variable @v_initialized init(@initializer) : tensor<4xi32>
-func @initializer() -> tensor<4xi32> {
-  %0 = constant dense<4> : tensor<4xi32>
-  return %0 : tensor<4xi32>
-}
-
-// -----
-
-flow.variable @v_unused : tensor<4xi32>
-// CHECK-LABEL: @unused_load
-func @unused_load() {
-  // CHECK-NEXT: return
-  %0 = flow.variable.load @v_unused : tensor<4xi32>
-  return
-}
-
-// -----
-
-flow.variable @v_const dense<1.0> : tensor<8xf32>
-// CHECK-LABEL: @fold_immutable_const
-func @fold_immutable_const() -> tensor<8xf32> {
-  // CHECK-NEXT: %[[CONST:.+]] = constant dense<1.{{.+}}> : tensor<8xf32>
-  %0 = flow.variable.load @v_const : tensor<8xf32>
-  // CHECK-NEXT: return %[[CONST]] : tensor<8xf32>
-  return %0 : tensor<8xf32>
-}
-
-// -----
-
-flow.variable @v_const dense<1.0> : tensor<8xf32> attributes {noinline}
-// CHECK-LABEL: @no_fold_noinline_immutable_const
-func @no_fold_noinline_immutable_const() -> tensor<8xf32> {
-  // CHECK-NEXT: = flow.variable.load @v_const : tensor<8xf32>
-  %0 = flow.variable.load @v_const : tensor<8xf32>
-  return %0 : tensor<8xf32>
-}
-
-// -----
-
-flow.variable @v_nop mutable : tensor<4xi32>
-// CHECK-LABEL: @nop_load_store
-func @nop_load_store() {
-  // CHECK-NEXT: return
-  %0 = flow.variable.load @v_nop : tensor<4xi32>
-  flow.variable.store %0, @v_nop : tensor<4xi32>
-  return
-}
-
-// -----
-
-flow.variable @v : tensor<4xf32>
-// CHECK-LABEL: @fold_load_indirect
-func @fold_load_indirect() -> tensor<4xf32> {
-  %0 = flow.variable.address @v : !util.ptr<tensor<4xf32>>
-  // CHECK-NEXT: = flow.variable.load @v
-  %1 = flow.variable.load.indirect %0 : !util.ptr<tensor<4xf32>> -> tensor<4xf32>
-  return %1 : tensor<4xf32>
-}
-
-// -----
-
-flow.variable @v mutable : tensor<4xf32>
-// CHECK-LABEL: @fold_store_indirect
-func @fold_store_indirect(%arg0 : tensor<4xf32>) {
-  %0 = flow.variable.address @v : !util.ptr<tensor<4xf32>>
-  // CHECK-NEXT: flow.variable.store %arg0, @v
-  flow.variable.store.indirect %arg0, %0 : tensor<4xf32> -> !util.ptr<tensor<4xf32>>
-  return
-}
diff --git a/iree/compiler/Dialect/Flow/IR/test/variable_ops.mlir b/iree/compiler/Dialect/Flow/IR/test/variable_ops.mlir
deleted file mode 100644
index 7b9fe83..0000000
--- a/iree/compiler/Dialect/Flow/IR/test/variable_ops.mlir
+++ /dev/null
@@ -1,67 +0,0 @@
-// Tests printing and parsing of variable ops.
-
-// RUN: iree-opt -allow-unregistered-dialect -split-input-file %s | iree-opt -allow-unregistered-dialect -split-input-file | IreeFileCheck %s
-
-// CHECK: flow.variable @v_immutable : tensor<i32>
-flow.variable @v_immutable : tensor<i32>
-// CHECK: flow.variable @v_mutable mutable : tensor<i32>
-flow.variable @v_mutable mutable : tensor<i32>
-
-// -----
-
-// CHECK: flow.variable @v_initialized_const dense<4> : tensor<4xi32>
-flow.variable @v_initialized_const dense<4> : tensor<4xi32>
-
-// -----
-
-// CHECK: flow.variable @v_initialized init(@initializer) : tensor<4xi32>
-flow.variable @v_initialized init(@initializer) : tensor<4xi32>
-func private @initializer() -> tensor<4xi32>
-
-// -----
-
-flow.variable @v_loaded : tensor<4xi32>
-// CHECK-LABEL: @loaded
-func @loaded() {
-  // CHECK-NEXT: = flow.variable.load @v_loaded : tensor<4xi32>
-  %0 = flow.variable.load @v_loaded : tensor<4xi32>
-  return
-}
-
-// -----
-
-flow.variable @v_stored mutable : tensor<4xi32>
-// CHECK-LABEL: @stored
-func @stored() {
-  // CHECK-NEXT: %[[VAL:.+]] = constant
-  %cst = constant dense<5> : tensor<4xi32>
-  // CHECK-NEXT: flow.variable.store %[[VAL]], @v_stored : tensor<4xi32>
-  flow.variable.store %cst, @v_stored : tensor<4xi32>
-  return
-}
-
-// -----
-
-flow.variable @v_loaded : tensor<4xf32>
-// CHECK-LABEL: @loaded_indirect
-func @loaded_indirect() {
-  // CHECK-NEXT: %[[ADDR:.+]] = flow.variable.address @v_loaded
-  %0 = flow.variable.address @v_loaded : !util.ptr<tensor<4xf32>>
-  // CHECK-NEXT: = flow.variable.load.indirect %[[ADDR]]
-  %1 = flow.variable.load.indirect %0 : !util.ptr<tensor<4xf32>> -> tensor<4xf32>
-  return
-}
-
-// -----
-
-flow.variable @v_stored mutable : tensor<4xf32>
-// CHECK-LABEL: @stored_indirect
-func @stored_indirect() {
-  // CHECK-NEXT: %[[VALUE:.+]] = "test_flow.tensor"
-  %0 = "test_flow.tensor"() : () -> tensor<4xf32>
-  // CHECK-NEXT: %[[ADDR:.+]] = flow.variable.address @v_stored
-  %1 = flow.variable.address @v_stored : !util.ptr<tensor<4xf32>>
-  // CHECK-NEXT: flow.variable.store.indirect %[[VALUE]], %[[ADDR]]
-  flow.variable.store.indirect %0, %1 : tensor<4xf32> -> !util.ptr<tensor<4xf32>>
-  return
-}
diff --git a/iree/compiler/Dialect/Flow/Transforms/BUILD b/iree/compiler/Dialect/Flow/Transforms/BUILD
index 55ecddb..40bb2ed 100644
--- a/iree/compiler/Dialect/Flow/Transforms/BUILD
+++ b/iree/compiler/Dialect/Flow/Transforms/BUILD
@@ -38,7 +38,7 @@
         "DeduplicateExecutables.cpp",
         "DestructiveUpdateUtils.cpp",
         "DispatchLinalgOnTensors.cpp",
-        "ExpandVariableDynamicDims.cpp",
+        "ExpandGlobalDynamicDims.cpp",
         "ExportBenchmarkFuncs.cpp",
         "FormStreams.cpp",
         "FusionOfTensorOps.cpp",
@@ -55,7 +55,6 @@
         "Passes.cpp",
         "PromoteI1ToI8Pass.cpp",
         "PromoteTensorLoads.cpp",
-        "SimplifyVariableAccesses.cpp",
         "StripAndSplatConstantVariables.cpp",
         "TypeConverter.cpp",
         "VerifyInputLegality.cpp",
@@ -77,6 +76,7 @@
         "//iree/compiler/Dialect/Shape/Transforms",
         "//iree/compiler/Dialect/Shape/Utils:TypeConversion",
         "//iree/compiler/Dialect/Util/IR",
+        "//iree/compiler/Dialect/Util/Transforms",
         "//iree/compiler/Utils",
         "@llvm-project//llvm:Support",
         "@llvm-project//mlir:Affine",
diff --git a/iree/compiler/Dialect/Flow/Transforms/CMakeLists.txt b/iree/compiler/Dialect/Flow/Transforms/CMakeLists.txt
index 78c08dd..167839f 100644
--- a/iree/compiler/Dialect/Flow/Transforms/CMakeLists.txt
+++ b/iree/compiler/Dialect/Flow/Transforms/CMakeLists.txt
@@ -35,7 +35,7 @@
     "DeduplicateExecutables.cpp"
     "DestructiveUpdateUtils.cpp"
     "DispatchLinalgOnTensors.cpp"
-    "ExpandVariableDynamicDims.cpp"
+    "ExpandGlobalDynamicDims.cpp"
     "ExportBenchmarkFuncs.cpp"
     "FormStreams.cpp"
     "FusionOfTensorOps.cpp"
@@ -52,7 +52,6 @@
     "Passes.cpp"
     "PromoteI1ToI8Pass.cpp"
     "PromoteTensorLoads.cpp"
-    "SimplifyVariableAccesses.cpp"
     "StripAndSplatConstantVariables.cpp"
     "TypeConverter.cpp"
     "VerifyInputLegality.cpp"
@@ -81,6 +80,7 @@
     iree::compiler::Dialect::Shape::Transforms
     iree::compiler::Dialect::Shape::Utils::TypeConversion
     iree::compiler::Dialect::Util::IR
+    iree::compiler::Dialect::Util::Transforms
     iree::compiler::Utils
   PUBLIC
 )
diff --git a/iree/compiler/Dialect/Flow/Transforms/ExpandGlobalDynamicDims.cpp b/iree/compiler/Dialect/Flow/Transforms/ExpandGlobalDynamicDims.cpp
new file mode 100644
index 0000000..42bbdd6
--- /dev/null
+++ b/iree/compiler/Dialect/Flow/Transforms/ExpandGlobalDynamicDims.cpp
@@ -0,0 +1,144 @@
+// Copyright 2021 The IREE Authors
+//
+// Licensed under the Apache License v2.0 with LLVM Exceptions.
+// See https://llvm.org/LICENSE.txt for license information.
+// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+
+#include <utility>
+
+#include "iree/compiler/Dialect/Flow/IR/FlowDialect.h"
+#include "iree/compiler/Dialect/Flow/IR/FlowOps.h"
+#include "iree/compiler/Dialect/Flow/Transforms/PassDetail.h"
+#include "iree/compiler/Dialect/Flow/Transforms/Passes.h"
+#include "iree/compiler/Dialect/Shape/IR/ShapeDialect.h"
+#include "iree/compiler/Dialect/Shape/IR/ShapeOps.h"
+#include "iree/compiler/Dialect/Util/IR/UtilDialect.h"
+#include "iree/compiler/Dialect/Util/IR/UtilOps.h"
+#include "mlir/IR/Attributes.h"
+#include "mlir/IR/Builders.h"
+#include "mlir/Pass/Pass.h"
+
+namespace mlir {
+namespace iree_compiler {
+namespace IREE {
+namespace Flow {
+
+class ExpandGlobalDynamicDimsPass
+    : public ExpandGlobalDynamicDimsBase<ExpandGlobalDynamicDimsPass> {
+ public:
+  ExpandGlobalDynamicDimsPass() = default;
+
+  void getDependentDialects(DialectRegistry &registry) const override {
+    registry.insert<IREE::Flow::FlowDialect, IREE::Util::UtilDialect>();
+    registry.insert<ShapeDialect>();
+  }
+
+  void runOnOperation() override {
+    auto moduleOp = getOperation();
+
+    // Gathers all of the util.globals containing shapes.
+    SmallVector<IREE::Util::GlobalOp, 4> shapeGlobalOps;
+    moduleOp.walk([&](IREE::Util::GlobalOp op) {
+      if (op.type().isa<Shape::RankedShapeType>()) {
+        shapeGlobalOps.push_back(op);
+      }
+    });
+
+    // Split each global into one global per dimension.
+    for (auto shapeGlobalOp : shapeGlobalOps) {
+      expandShapeGlobal(moduleOp, shapeGlobalOp);
+    }
+  }
+
+ private:
+  // Expands a util.global representing a shape with one global per dim.
+  // Uses of the global will be replaced with the per-dim ones.
+  void expandShapeGlobal(mlir::ModuleOp moduleOp,
+                         IREE::Util::GlobalOp shapeGlobalOp) {
+    // Create one util.global per dimension (static or dynamic).
+    OpBuilder moduleBuilder(shapeGlobalOp);
+    auto shapeType = shapeGlobalOp.type().cast<Shape::RankedShapeType>();
+    SmallVector<IREE::Util::GlobalOp, 4> dimGlobalOps;
+    for (int i = 0; i < shapeType.getRank(); ++i) {
+      Attribute initialDimValue;
+      if (shapeType.isDimDynamic(i)) {
+        // Right now we choose zero for initial dynamic dim values but this
+        // needs to agree with bindings that may have expectations on query.
+        // 0 is at least easier to gracefully bail on when values are never
+        // overridden.
+        initialDimValue = moduleBuilder.getIndexAttr(0);
+      } else {
+        initialDimValue = moduleBuilder.getIndexAttr(shapeType.getStaticDim(i));
+      }
+      auto dimGlobalOp = moduleBuilder.create<IREE::Util::GlobalOp>(
+          shapeGlobalOp.getLoc(),
+          (shapeGlobalOp.getName() + "_d" + std::to_string(i)).str(),
+          /*isMutable=*/shapeType.isDimDynamic(i), moduleBuilder.getIndexType(),
+          initialDimValue);
+      dimGlobalOp.setPrivate();
+      dimGlobalOps.push_back(dimGlobalOp);
+    }
+
+    // Replace all uses of the single global with the split ones.
+    replaceShapeGlobalUses(moduleOp, shapeType, shapeGlobalOp, dimGlobalOps);
+
+    // Erase the original global.
+    shapeGlobalOp.erase();
+  }
+
+  // Replaces uses of |shapeGlobalOp| in |moduleOp| with the expanded
+  // |dimGlobalOps|.
+  void replaceShapeGlobalUses(mlir::ModuleOp moduleOp,
+                              Shape::RankedShapeType shapeType,
+                              IREE::Util::GlobalOp shapeGlobalOp,
+                              ArrayRef<IREE::Util::GlobalOp> dimGlobalOps) {
+    auto allUses = SymbolTable::getSymbolUses(shapeGlobalOp, moduleOp)
+                       .getValueOr(SymbolTable::UseRange({}));
+    for (auto use : allUses) {
+      if (auto loadOp = dyn_cast<IREE::Util::GlobalLoadOp>(use.getUser())) {
+        OpBuilder builder(loadOp);
+        SmallVector<Value, 4> dynamicDimValues;
+        for (int i = 0; i < shapeType.getRank(); ++i) {
+          if (!shapeType.isDimDynamic(i)) continue;
+          IREE::Util::GlobalOp dimGlobalOp = dimGlobalOps[i];
+          dynamicDimValues.push_back(builder.create<IREE::Util::GlobalLoadOp>(
+              loadOp.getLoc(), builder.getIndexType(), dimGlobalOp.getName()));
+        }
+        auto shapeValue = builder.create<Shape::MakeRankedShapeOp>(
+            loadOp.getLoc(), shapeType, dynamicDimValues);
+        loadOp->replaceAllUsesWith(shapeValue);
+        loadOp.erase();
+      } else if (auto storeOp =
+                     dyn_cast<IREE::Util::GlobalStoreOp>(use.getUser())) {
+        OpBuilder builder(storeOp);
+        auto shapeValue = storeOp.value();
+        for (int i = 0; i < shapeType.getRank(); ++i) {
+          if (!shapeType.isDimDynamic(i)) continue;
+          IREE::Util::GlobalOp dimGlobalOp = dimGlobalOps[i];
+          auto dynamicDimValue = builder.createOrFold<Shape::RankedDimOp>(
+              storeOp.getLoc(), shapeValue, i);
+          builder.create<IREE::Util::GlobalStoreOp>(
+              storeOp.getLoc(), dynamicDimValue, dimGlobalOp.getName());
+        }
+        storeOp.erase();
+      } else {
+        // TODO(benvanik): support indirection/addressing - should be fairly
+        // easy to do by splitting the address ops to each dim.
+        use.getUser()->emitError()
+            << "global action on shape is not yet supported";
+        signalPassFailure();
+        return;
+      }
+    }
+  }
+};
+
+std::unique_ptr<OperationPass<mlir::ModuleOp>>
+createExpandGlobalDynamicDimsPass() {
+  return std::make_unique<ExpandGlobalDynamicDimsPass>();
+}
+
+}  // namespace Flow
+}  // namespace IREE
+}  // namespace iree_compiler
+}  // namespace mlir
diff --git a/iree/compiler/Dialect/Flow/Transforms/ExpandVariableDynamicDims.cpp b/iree/compiler/Dialect/Flow/Transforms/ExpandVariableDynamicDims.cpp
deleted file mode 100644
index 7a5d6f3..0000000
--- a/iree/compiler/Dialect/Flow/Transforms/ExpandVariableDynamicDims.cpp
+++ /dev/null
@@ -1,139 +0,0 @@
-// Copyright 2021 The IREE Authors
-//
-// Licensed under the Apache License v2.0 with LLVM Exceptions.
-// See https://llvm.org/LICENSE.txt for license information.
-// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
-
-#include <utility>
-
-#include "iree/compiler/Dialect/Flow/IR/FlowDialect.h"
-#include "iree/compiler/Dialect/Flow/IR/FlowOps.h"
-#include "iree/compiler/Dialect/Flow/Transforms/PassDetail.h"
-#include "iree/compiler/Dialect/Flow/Transforms/Passes.h"
-#include "iree/compiler/Dialect/Shape/IR/ShapeDialect.h"
-#include "iree/compiler/Dialect/Shape/IR/ShapeOps.h"
-#include "mlir/IR/Attributes.h"
-#include "mlir/IR/Builders.h"
-#include "mlir/Pass/Pass.h"
-
-namespace mlir {
-namespace iree_compiler {
-namespace IREE {
-namespace Flow {
-
-class ExpandVariableDynamicDimsPass
-    : public ExpandVariableDynamicDimsBase<ExpandVariableDynamicDimsPass> {
- public:
-  ExpandVariableDynamicDimsPass() = default;
-
-  void getDependentDialects(DialectRegistry &registry) const override {
-    registry.insert<IREE::Flow::FlowDialect>();
-    registry.insert<ShapeDialect>();
-  }
-
-  void runOnOperation() override {
-    auto moduleOp = getOperation();
-
-    // Gathers all of the flow.variables containing shapes.
-    SmallVector<VariableOp, 4> shapeVarOps;
-    moduleOp.walk([&](VariableOp op) {
-      if (op.type().isa<Shape::RankedShapeType>()) {
-        shapeVarOps.push_back(op);
-      }
-    });
-
-    // Split each variable into one variable per dimension.
-    for (auto shapeVarOp : shapeVarOps) {
-      expandShapeVariable(moduleOp, shapeVarOp);
-    }
-  }
-
- private:
-  // Expands a flow.variable representing a shape with one variable per dim.
-  // Uses of the variable will be replaced with the per-dim ones.
-  void expandShapeVariable(mlir::ModuleOp moduleOp, VariableOp shapeVarOp) {
-    // Create one flow.variable per dimension (static or dynamic).
-    OpBuilder moduleBuilder(shapeVarOp);
-    auto shapeType = shapeVarOp.type().cast<Shape::RankedShapeType>();
-    SmallVector<VariableOp, 4> dimVarOps;
-    for (int i = 0; i < shapeType.getRank(); ++i) {
-      Attribute initialDimValue;
-      if (shapeType.isDimDynamic(i)) {
-        // Right now we choose zero for initial dynamic dim values but this
-        // needs to agree with bindings that may have expectations on query.
-        // 0 is at least easier to gracefully bail on when values are never
-        // overridden.
-        initialDimValue = moduleBuilder.getIndexAttr(0);
-      } else {
-        initialDimValue = moduleBuilder.getIndexAttr(shapeType.getStaticDim(i));
-      }
-      auto dimVarOp = moduleBuilder.create<VariableOp>(
-          shapeVarOp.getLoc(),
-          (shapeVarOp.getName() + "_d" + std::to_string(i)).str(),
-          /*isMutable=*/shapeType.isDimDynamic(i), moduleBuilder.getIndexType(),
-          initialDimValue);
-      dimVarOp.setPrivate();
-      dimVarOps.push_back(dimVarOp);
-    }
-
-    // Replace all uses of the single variable with the split ones.
-    replaceShapeVariableUses(moduleOp, shapeType, shapeVarOp, dimVarOps);
-
-    // Erase the original variable.
-    shapeVarOp.erase();
-  }
-
-  // Replaces uses of |shapeVarOp| in |moduleOp| with the expanded |dimVarOps|.
-  void replaceShapeVariableUses(mlir::ModuleOp moduleOp,
-                                Shape::RankedShapeType shapeType,
-                                VariableOp shapeVarOp,
-                                ArrayRef<VariableOp> dimVarOps) {
-    auto allUses = SymbolTable::getSymbolUses(shapeVarOp, moduleOp)
-                       .getValueOr(SymbolTable::UseRange({}));
-    for (auto use : allUses) {
-      if (auto loadOp = dyn_cast<VariableLoadOp>(use.getUser())) {
-        OpBuilder builder(loadOp);
-        SmallVector<Value, 4> dynamicDimValues;
-        for (int i = 0; i < shapeType.getRank(); ++i) {
-          if (!shapeType.isDimDynamic(i)) continue;
-          VariableOp dimVarOp = dimVarOps[i];
-          dynamicDimValues.push_back(builder.create<VariableLoadOp>(
-              loadOp.getLoc(), builder.getIndexType(), dimVarOp.getName()));
-        }
-        auto shapeValue = builder.create<Shape::MakeRankedShapeOp>(
-            loadOp.getLoc(), shapeType, dynamicDimValues);
-        loadOp->replaceAllUsesWith(shapeValue);
-        loadOp.erase();
-      } else if (auto storeOp = dyn_cast<VariableStoreOp>(use.getUser())) {
-        OpBuilder builder(storeOp);
-        auto shapeValue = storeOp.value();
-        for (int i = 0; i < shapeType.getRank(); ++i) {
-          if (!shapeType.isDimDynamic(i)) continue;
-          VariableOp dimVarOp = dimVarOps[i];
-          auto dynamicDimValue = builder.createOrFold<Shape::RankedDimOp>(
-              storeOp.getLoc(), shapeValue, i);
-          builder.create<VariableStoreOp>(storeOp.getLoc(), dynamicDimValue,
-                                          dimVarOp.getName());
-        }
-        storeOp.erase();
-      } else {
-        // TODO(benvanik): support indirection/addressing - should be fairly
-        // easy to do by splitting the address ops to each dim.
-        use.getUser()->emitError()
-            << "variable action on shape is not yet supported";
-        signalPassFailure();
-        return;
-      }
-    }
-  }
-};
-
-std::unique_ptr<OperationPass<mlir::ModuleOp>>
-createExpandVariableDynamicDimsPass() {
-  return std::make_unique<ExpandVariableDynamicDimsPass>();
-}
-
-}  // namespace Flow
-}  // namespace IREE
-}  // namespace iree_compiler
-}  // namespace mlir
diff --git a/iree/compiler/Dialect/Flow/Transforms/ExportBenchmarkFuncs.cpp b/iree/compiler/Dialect/Flow/Transforms/ExportBenchmarkFuncs.cpp
index 929415a..c27dceb 100644
--- a/iree/compiler/Dialect/Flow/Transforms/ExportBenchmarkFuncs.cpp
+++ b/iree/compiler/Dialect/Flow/Transforms/ExportBenchmarkFuncs.cpp
@@ -23,7 +23,7 @@
 // Clones each exported functions (including those just created) with
 // placeholder constant inputs instead of arguments and removes the exported
 // attribute from the old functions.
-// The input are provided using flow.variables.
+// The input are provided using util.globals.
 class ExportBenchmarkFuncsPass
     : public ExportBenchmarkFuncsBase<ExportBenchmarkFuncsPass> {
  public:
@@ -52,9 +52,8 @@
   }
 
  private:
-  IREE::Flow::VariableOp createDummyInputVariableOp(Location loc,
-                                                    Type inputType,
-                                                    OpBuilder& moduleBuilder) {
+  IREE::Util::GlobalOp createDummyInputVariableOp(Location loc, Type inputType,
+                                                  OpBuilder& moduleBuilder) {
     std::string baseName = "_benchmark_input_";
     std::string name = baseName + std::to_string(uniqueId++);
     auto initialValue = moduleBuilder.getZeroAttr(inputType);
@@ -63,12 +62,12 @@
                            << inputType;
       return {};
     }
-    auto variableOp = moduleBuilder.create<IREE::Flow::VariableOp>(
+    auto globalOp = moduleBuilder.create<IREE::Util::GlobalOp>(
         loc, name,
         /*isMutable=*/false, inputType, initialValue);
-    variableOp.setPrivate();
-    variableOp->setAttr("noinline", UnitAttr::get(moduleBuilder.getContext()));
-    return variableOp;
+    globalOp.setPrivate();
+    globalOp->setAttr("noinline", UnitAttr::get(moduleBuilder.getContext()));
+    return globalOp;
   }
 
   LogicalResult createEntryPointBenchmarkFunc(mlir::ModuleOp moduleOp,
@@ -78,7 +77,7 @@
 
     // Create one dummy input variable per input.
     Location loc = entryFuncOp.getLoc();
-    SmallVector<IREE::Flow::VariableOp, 4> dummyInputVariableOps;
+    SmallVector<IREE::Util::GlobalOp, 4> dummyInputVariableOps;
     for (auto inputType : entryFuncOp.getType().getInputs()) {
       auto dummyVar = createDummyInputVariableOp(loc, inputType, moduleBuilder);
       if (!dummyVar) return failure();
@@ -103,7 +102,7 @@
     auto blockBuilder = OpBuilder::atBlockBegin(block);
     SmallVector<Value, 4> args;
     for (int i = 0, e = entryFuncOp.getNumArguments(); i < e; ++i) {
-      args.push_back(blockBuilder.createOrFold<IREE::Flow::VariableLoadOp>(
+      args.push_back(blockBuilder.createOrFold<IREE::Util::GlobalLoadOp>(
           loc, dummyInputVariableOps[i]));
     }
     auto callOp = blockBuilder.create<mlir::CallOp>(loc, entryFuncOp, args);
diff --git a/iree/compiler/Dialect/Flow/Transforms/InsertConstantClones.cpp b/iree/compiler/Dialect/Flow/Transforms/InsertConstantClones.cpp
index ef02f75..46f2d64 100644
--- a/iree/compiler/Dialect/Flow/Transforms/InsertConstantClones.cpp
+++ b/iree/compiler/Dialect/Flow/Transforms/InsertConstantClones.cpp
@@ -62,9 +62,9 @@
     if (op->hasTrait<OpTrait::ConstantLike>() ||
         isa<IREE::Util::UnfoldableConstantOp>(op)) {
       return true;
-    } else if (auto loadOp = dyn_cast<IREE::Flow::VariableLoadOp>(op)) {
-      return !loadOp.getLoadedVariable().is_mutable();
-    } else if (auto loadOp = dyn_cast<IREE::Flow::VariableLoadIndirectOp>(op)) {
+    } else if (auto loadOp = dyn_cast<IREE::Util::GlobalLoadOp>(op)) {
+      return loadOp.isGlobalImmutable();
+    } else if (auto loadOp = dyn_cast<IREE::Util::GlobalLoadIndirectOp>(op)) {
       return true;  // can't know indirect variable behavior (without DFA)
     } else if (auto sliceOp = dyn_cast<IREE::Flow::TensorSliceOp>(op)) {
       return isLikelyConstant(sliceOp.source());
diff --git a/iree/compiler/Dialect/Flow/Transforms/OutlineLargeConstants.cpp b/iree/compiler/Dialect/Flow/Transforms/OutlineLargeConstants.cpp
index e469855..674397c 100644
--- a/iree/compiler/Dialect/Flow/Transforms/OutlineLargeConstants.cpp
+++ b/iree/compiler/Dialect/Flow/Transforms/OutlineLargeConstants.cpp
@@ -10,6 +10,8 @@
 #include "iree/compiler/Dialect/Flow/IR/FlowOps.h"
 #include "iree/compiler/Dialect/Flow/Transforms/PassDetail.h"
 #include "iree/compiler/Dialect/Flow/Transforms/Passes.h"
+#include "iree/compiler/Dialect/Util/IR/UtilDialect.h"
+#include "iree/compiler/Dialect/Util/IR/UtilOps.h"
 #include "mlir/Dialect/StandardOps/IR/Ops.h"
 #include "mlir/IR/Attributes.h"
 #include "mlir/IR/Builders.h"
@@ -64,7 +66,7 @@
       : minLargeConstantSize(minLargeConstantSize){};
 
   void getDependentDialects(DialectRegistry &registry) const override {
-    registry.insert<IREE::Flow::FlowDialect>();
+    registry.insert<IREE::Flow::FlowDialect, IREE::Util::UtilDialect>();
   }
 
   void runOnOperation() override {
@@ -76,36 +78,36 @@
     std::string baseName = "_large_const_";
     int uniqueId = 0;
 
-    // Create all top-level flow.variables from large constants in the module.
+    // Create all top-level util.globals from large constants in the module.
     OpBuilder moduleBuilder(&moduleOp.getBody()->front());
-    std::vector<std::pair<ConstantOp, IREE::Flow::VariableOp>> replacements;
+    std::vector<std::pair<ConstantOp, IREE::Util::GlobalOp>> replacements;
     for (auto &largeConstantOp :
          findLargeConstantsInModule(moduleOp, minLargeConstantSize)) {
       std::string name;
       do {
         name = baseName + std::to_string(uniqueId++);
       } while (moduleSymbols.lookup(name) != nullptr);
-      auto variableOp = moduleBuilder.create<IREE::Flow::VariableOp>(
+      auto globalOp = moduleBuilder.create<IREE::Util::GlobalOp>(
           largeConstantOp.getLoc(), name, /*isMutable=*/false,
           largeConstantOp.getType(), largeConstantOp.getValue());
-      variableOp.setPrivate();
-      replacements.emplace_back(largeConstantOp, variableOp);
+      globalOp.setPrivate();
+      replacements.emplace_back(largeConstantOp, globalOp);
 
       // Prevent the variable from being re-inlined if the canonicalizer runs.
       // By the time we've outlined things here we are sure we want them
       // outlined even if the user runs an arbitrary number of passes between
       // now and when we may use that information (HAL constant pooling, etc).
-      variableOp->setAttr("noinline", moduleBuilder.getUnitAttr());
+      globalOp->setAttr("noinline", moduleBuilder.getUnitAttr());
     }
 
     // Replace all of the constants with lookups for the new variables.
     for (auto pair : replacements) {
       auto constantOp = pair.first;
-      auto variableOp = pair.second;
+      auto globalOp = pair.second;
       OpBuilder builder(moduleOp.getContext());
       builder.setInsertionPoint(constantOp);
-      auto lookupOp = builder.create<IREE::Flow::VariableLoadOp>(
-          constantOp.getLoc(), constantOp.getType(), variableOp.getName());
+      auto lookupOp = builder.create<IREE::Util::GlobalLoadOp>(
+          constantOp.getLoc(), constantOp.getType(), globalOp.getName());
       constantOp.getResult().replaceAllUsesWith(lookupOp);
       constantOp.erase();
     }
diff --git a/iree/compiler/Dialect/Flow/Transforms/Passes.cpp b/iree/compiler/Dialect/Flow/Transforms/Passes.cpp
index 8cc9152..47685da 100644
--- a/iree/compiler/Dialect/Flow/Transforms/Passes.cpp
+++ b/iree/compiler/Dialect/Flow/Transforms/Passes.cpp
@@ -9,6 +9,7 @@
 #include <memory>
 
 #include "iree/compiler/Dialect/Shape/Transforms/Passes.h"
+#include "iree/compiler/Dialect/Util/Transforms/Passes.h"
 #include "mlir/Dialect/Linalg/Passes.h"
 #include "mlir/Dialect/MemRef/Transforms/Passes.h"
 #include "mlir/Pass/PassOptions.h"
@@ -77,10 +78,10 @@
 namespace Flow {
 
 void buildFlowTransformPassPipeline(OpPassManager &passManager) {
-  // Simplify flow.variable accesses early on; this can help with dispatch
+  // Simplify util.global accesses early on; this can help with dispatch
   // region formation as redundant store-loads are removed.
   passManager.addNestedPass<mlir::FuncOp>(
-      IREE::Flow::createSimplifyVariableAccessesPass());
+      IREE::Util::createSimplifyGlobalAccessesPass());
 
   // Perform cleanup after variable simplification as more canonicalizers may be
   // able to kick in.
@@ -90,7 +91,7 @@
   // Replaces variables with !shapex.ranked_shape types with individual
   // variables for each dimension. This allows for constant dimensions to be
   // DCE'd in following passes.
-  passManager.addPass(IREE::Flow::createExpandVariableDynamicDimsPass());
+  passManager.addPass(IREE::Flow::createExpandGlobalDynamicDimsPass());
 
   // Materialize dynamic shapes in the IR, also expanding function signatures
   // such that:
diff --git a/iree/compiler/Dialect/Flow/Transforms/Passes.h b/iree/compiler/Dialect/Flow/Transforms/Passes.h
index 733d4b5..e35210c 100644
--- a/iree/compiler/Dialect/Flow/Transforms/Passes.h
+++ b/iree/compiler/Dialect/Flow/Transforms/Passes.h
@@ -93,7 +93,7 @@
 
 // Expands dynamic !shapex.ranked_shape dimensions in variables.
 std::unique_ptr<OperationPass<mlir::ModuleOp>>
-createExpandVariableDynamicDimsPass();
+createExpandGlobalDynamicDimsPass();
 
 /// Verified if the input to the Flow transformation passes has operations from
 /// dialects that are expected to be legalized before this pass.
@@ -130,7 +130,7 @@
 // Optimizations
 //===----------------------------------------------------------------------===//
 
-// Outlines large tensor constants into flow.variables at the module level.
+// Outlines large tensor constants into util.globals at the module level.
 //
 // TODO(#5493): implement the support for inlining constants into the command
 // buffer and raise this value to one that is measured to be good.
@@ -152,11 +152,6 @@
 // Reorders blocks to hoist ops that cannot be put into streams.
 std::unique_ptr<OperationPass<mlir::FuncOp>> createHoistUnstreamableOpsPass();
 
-// Hoists loads and sinks stores to variables to decrease data dependency
-// regions.
-std::unique_ptr<OperationPass<mlir::FuncOp>>
-createSimplifyVariableAccessesPass();
-
 // TODO(benvanik): cross-function stream flows.
 
 // Inserts clones of constant values where they may be required.
@@ -170,7 +165,7 @@
 // Simplification and Development Tools
 //===----------------------------------------------------------------------===//
 
-// Strips constant flow.variables and replaces them with splats.
+// Strips constant util.globals and replaces them with splats.
 // This destructively removes data (often model weights and other parameters)
 // and is intended for use as a development tool.
 // TODO(scotttodd): pass pipeline with this and other development passes to
diff --git a/iree/compiler/Dialect/Flow/Transforms/Passes.td b/iree/compiler/Dialect/Flow/Transforms/Passes.td
index d03eb63..8a349e4 100644
--- a/iree/compiler/Dialect/Flow/Transforms/Passes.td
+++ b/iree/compiler/Dialect/Flow/Transforms/Passes.td
@@ -49,10 +49,10 @@
   let constructor = "mlir::iree_compiler::IREE::Flow::createDispatchLinalgOnTensorsPass()";
 }
 
-def ExpandVariableDynamicDims :
-    Pass<"iree-flow-expand-variable-dynamic-dims", "mlir::ModuleOp"> {
+def ExpandGlobalDynamicDims :
+    Pass<"iree-flow-expand-global-dynamic-dims", "mlir::ModuleOp"> {
   let summary = "Expands !shapex.ranked_shape dynamic dimensions stored in variables.";
-  let constructor = "mlir::iree_compiler::IREE::Flow::createExpandVariableDynamicDimsPass()";
+  let constructor = "mlir::iree_compiler::IREE::Flow::createExpandGlobalDynamicDimsPass()";
 }
 
 def ExportBenchmarkFuncs :
@@ -105,7 +105,7 @@
 
 def OutlineLargeConstants :
     Pass<"iree-flow-outline-large-constants", "mlir::ModuleOp"> {
-  let summary = "Outlines large tensor constants into flow.variables at the module level.";
+  let summary = "Outlines large tensor constants into util.globals at the module level.";
   // TODO(#5493): add a flag for this.
   let constructor = "mlir::iree_compiler::IREE::Flow::createOutlineLargeConstantsPass(25)";
 }
@@ -141,15 +141,9 @@
   let constructor = "mlir::iree_compiler::IREE::Flow::createPromoteTensorLoadsPass()";
 }
 
-def SimplifyVariableAccesses :
-    Pass<"iree-flow-simplify-variable-accesses", "mlir::FuncOp"> {
-  let summary = "Hoist loads and sinks stores to variables to decrease data dependency regions.";
-  let constructor = "mlir::iree_compiler::IREE::Flow::createSimplifyVariableAccessesPass()";
-}
-
 def StripAndSplatConstantVariables :
     Pass<"iree-flow-strip-and-splat-constant-variables", "mlir::ModuleOp"> {
-  let summary = "Strips constant flow.variables and replaces them with splats.";
+  let summary = "Strips constant util.globals and replaces them with splats.";
   let constructor = "mlir::iree_compiler::IREE::Flow::createStripAndSplatConstantVariablesPass()";
 }
 
diff --git a/iree/compiler/Dialect/Flow/Transforms/StripAndSplatConstantVariables.cpp b/iree/compiler/Dialect/Flow/Transforms/StripAndSplatConstantVariables.cpp
index c5f7510..b0c4c10 100644
--- a/iree/compiler/Dialect/Flow/Transforms/StripAndSplatConstantVariables.cpp
+++ b/iree/compiler/Dialect/Flow/Transforms/StripAndSplatConstantVariables.cpp
@@ -10,6 +10,8 @@
 #include "iree/compiler/Dialect/Flow/IR/FlowOps.h"
 #include "iree/compiler/Dialect/Flow/Transforms/PassDetail.h"
 #include "iree/compiler/Dialect/Flow/Transforms/Passes.h"
+#include "iree/compiler/Dialect/Util/IR/UtilDialect.h"
+#include "iree/compiler/Dialect/Util/IR/UtilOps.h"
 #include "mlir/IR/Attributes.h"
 #include "mlir/IR/Builders.h"
 #include "mlir/Pass/Pass.h"
@@ -26,7 +28,7 @@
   StripAndSplatConstantVariablesPass() = default;
 
   void getDependentDialects(DialectRegistry &registry) const override {
-    registry.insert<IREE::Flow::FlowDialect>();
+    registry.insert<IREE::Flow::FlowDialect, IREE::Util::UtilDialect>();
   }
 
   void runOnOperation() override {
@@ -40,7 +42,7 @@
     // TODO(scotttodd): flags to control numbers used (all 0, all 1, increasing)
     int replaceIndex = 1;
 
-    moduleOp.walk([&](VariableOp op) {
+    moduleOp.walk([&](IREE::Util::GlobalOp op) {
       // Only strip constant variables.
       if (op.is_mutable()) {
         return;
@@ -63,7 +65,7 @@
       }
 
       builder.setInsertionPointAfter(op);
-      auto newOp = builder.create<VariableOp>(
+      auto newOp = builder.create<IREE::Util::GlobalOp>(
           op.getLoc(), op.sym_name(), op.is_mutable(), op.type(), newValue);
       newOp.setVisibility(op.getVisibility());
       newOp->setAttr("noinline", UnitAttr::get(builder.getContext()));
diff --git a/iree/compiler/Dialect/Flow/Transforms/test/BUILD b/iree/compiler/Dialect/Flow/Transforms/test/BUILD
index f8d85c8..7872f95 100644
--- a/iree/compiler/Dialect/Flow/Transforms/test/BUILD
+++ b/iree/compiler/Dialect/Flow/Transforms/test/BUILD
@@ -25,7 +25,7 @@
             "dispatch_linalg_on_tensors.mlir",
             "dispatch_linalg_on_tensors_elementwise.mlir",
             "dispatch_linalg_on_tensors_fusion.mlir",
-            "expand_variable_dynamic_dims.mlir",
+            "expand_global_shape_dims.mlir",
             "export_benchmark_funcs.mlir",
             "form_streams.mlir",
             "hoist_unstreamable_ops.mlir",
@@ -39,7 +39,6 @@
             "pad_tensor_to_tensor.mlir",
             "promote_i1_to_i8.mlir",
             "promote_tensor_loads.mlir",
-            "simplify_variable_accesses.mlir",
             "strip_and_splat_constant_variables.mlir",
             "transformation.mlir",
             "verify_input_ir.mlir",
diff --git a/iree/compiler/Dialect/Flow/Transforms/test/CMakeLists.txt b/iree/compiler/Dialect/Flow/Transforms/test/CMakeLists.txt
index 3cf4f4e..fe71d4c 100644
--- a/iree/compiler/Dialect/Flow/Transforms/test/CMakeLists.txt
+++ b/iree/compiler/Dialect/Flow/Transforms/test/CMakeLists.txt
@@ -22,7 +22,7 @@
     "dispatch_linalg_on_tensors.mlir"
     "dispatch_linalg_on_tensors_elementwise.mlir"
     "dispatch_linalg_on_tensors_fusion.mlir"
-    "expand_variable_dynamic_dims.mlir"
+    "expand_global_shape_dims.mlir"
     "export_benchmark_funcs.mlir"
     "form_streams.mlir"
     "hoist_unstreamable_ops.mlir"
@@ -36,7 +36,6 @@
     "pad_tensor_to_tensor.mlir"
     "promote_i1_to_i8.mlir"
     "promote_tensor_loads.mlir"
-    "simplify_variable_accesses.mlir"
     "strip_and_splat_constant_variables.mlir"
     "transformation.mlir"
     "verify_input_ir.mlir"
diff --git a/iree/compiler/Dialect/Flow/Transforms/test/expand_variable_dynamic_dims.mlir b/iree/compiler/Dialect/Flow/Transforms/test/expand_global_shape_dims.mlir
similarity index 64%
rename from iree/compiler/Dialect/Flow/Transforms/test/expand_variable_dynamic_dims.mlir
rename to iree/compiler/Dialect/Flow/Transforms/test/expand_global_shape_dims.mlir
index 2588b9a..4c9497b 100644
--- a/iree/compiler/Dialect/Flow/Transforms/test/expand_variable_dynamic_dims.mlir
+++ b/iree/compiler/Dialect/Flow/Transforms/test/expand_global_shape_dims.mlir
@@ -1,16 +1,16 @@
-// RUN: iree-opt -split-input-file -iree-flow-expand-variable-dynamic-dims %s | IreeFileCheck %s
+// RUN: iree-opt -split-input-file -iree-flow-expand-global-dynamic-dims %s | IreeFileCheck %s
 
-// CHECK-NOT: flow.variable @static_var mutable
-// CHECK: flow.variable @static_var_d0 1 : index
-// CHECK: flow.variable @static_var_d1 2 : index
-// CHECK: flow.variable @static_var_d2 3 : index
-// CHECK: flow.variable @static_var_d3 4 : index
-flow.variable @static_var mutable : !shapex.ranked_shape<[1,2,3,4]>
+// CHECK-NOT: util.global mutable @static_var
+// CHECK: util.global private @static_var_d0 = 1 : index
+// CHECK: util.global private @static_var_d1 = 2 : index
+// CHECK: util.global private @static_var_d2 = 3 : index
+// CHECK: util.global private @static_var_d3 = 4 : index
+util.global mutable @static_var : !shapex.ranked_shape<[1,2,3,4]>
 // CHECK-LABEL: func @static_loads
 func @static_loads() -> (index, index, index, index) {
-  // CHECK-NOT: flow.variable.load
+  // CHECK-NOT: util.global.load
   // CHECK-NEXT: %[[SHAPE:.+]] = shapex.make_ranked_shape
-  %0 = flow.variable.load @static_var : !shapex.ranked_shape<[1,2,3,4]>
+  %0 = util.global.load @static_var : !shapex.ranked_shape<[1,2,3,4]>
   // CHECK-DAG: %[[D0:.+]] = shapex.ranked_dim %[[SHAPE]][0]
   %1 = shapex.ranked_dim %0[0] : !shapex.ranked_shape<[1,2,3,4]> -> index
   // CHECK-DAG: %[[D1:.+]] = shapex.ranked_dim %[[SHAPE]][1]
@@ -26,27 +26,27 @@
 func @static_stores(%arg0 : index, %arg1 : index) {
   // CHECK-NEXT: %[[SHAPE:.+]] = shapex.const_ranked_shape
   %0 = shapex.const_ranked_shape : !shapex.ranked_shape<[1,2,3,4]>
-  // CHECK-NOT: flow.variable.store
-  flow.variable.store %0, @static_var : !shapex.ranked_shape<[1,2,3,4]>
+  // CHECK-NOT: util.global.store
+  util.global.store %0, @static_var : !shapex.ranked_shape<[1,2,3,4]>
   // CHECK-NEXT: return
   return
 }
 
 // -----
 
-// CHECK-NOT: flow.variable @dynamic_var mutable
-// CHECK: flow.variable @dynamic_var_d0 1 : index
-// CHECK: flow.variable @dynamic_var_d1 mutable 0 : index
-// CHECK: flow.variable @dynamic_var_d2 mutable 0 : index
-// CHECK: flow.variable @dynamic_var_d3 4 : index
-flow.variable @dynamic_var mutable : !shapex.ranked_shape<[1,?,?,4]>
+// CHECK-NOT: util.global mutable @dynamic_var
+// CHECK: util.global private @dynamic_var_d0 = 1 : index
+// CHECK: util.global private mutable @dynamic_var_d1 = 0 : index
+// CHECK: util.global private mutable @dynamic_var_d2 = 0 : index
+// CHECK: util.global private @dynamic_var_d3 = 4 : index
+util.global mutable @dynamic_var : !shapex.ranked_shape<[1,?,?,4]>
 // CHECK-LABEL: func @dynamic_loads
 func @dynamic_loads() -> (index, index, index, index) {
-  // CHECK-NOT: flow.variable.load @dynamic_var
-  // CHECK-DAG: %[[D1:.+]] = flow.variable.load @dynamic_var_d1 : index
-  // CHECK-DAG: %[[D2:.+]] = flow.variable.load @dynamic_var_d2 : index
+  // CHECK-NOT: util.global.load @dynamic_var
+  // CHECK-DAG: %[[D1:.+]] = util.global.load @dynamic_var_d1 : index
+  // CHECK-DAG: %[[D2:.+]] = util.global.load @dynamic_var_d2 : index
   // CHECK-NEXT: %[[SHAPE:.+]] = shapex.make_ranked_shape %[[D1]], %[[D2]] : (index, index) -> !shapex.ranked_shape<[1,?,?,4]>
-  %0 = flow.variable.load @dynamic_var : !shapex.ranked_shape<[1,?,?,4]>
+  %0 = util.global.load @dynamic_var : !shapex.ranked_shape<[1,?,?,4]>
   // CHECK-DAG: = shapex.ranked_dim %[[SHAPE]][0] : !shapex.ranked_shape<[1,?,?,4]> -> index
   %1 = shapex.ranked_dim %0[0] : !shapex.ranked_shape<[1,?,?,4]> -> index
   // CHECK-DAG: = shapex.ranked_dim %[[SHAPE]][1] : !shapex.ranked_shape<[1,?,?,4]> -> index
@@ -64,10 +64,10 @@
   // CHECK-NEXT: %[[SHAPE:.+]] = shapex.make_ranked_shape %arg0, %arg1
   %0 = shapex.make_ranked_shape %arg0, %arg1 : (index, index) -> !shapex.ranked_shape<[1,?,?,4]>
   // CHECK-NEXT: %[[D1:.+]] = shapex.ranked_dim %[[SHAPE]][1] : !shapex.ranked_shape<[1,?,?,4]> -> index
-  // CHECK-NEXT: flow.variable.store %[[D1]], @dynamic_var_d1 : index
+  // CHECK-NEXT: util.global.store %[[D1]], @dynamic_var_d1 : index
   // CHECK-NEXT: %[[D2:.+]] = shapex.ranked_dim %[[SHAPE]][2] : !shapex.ranked_shape<[1,?,?,4]> -> index
-  // CHECK-NEXT: flow.variable.store %[[D2]], @dynamic_var_d2 : index
-  flow.variable.store %0, @dynamic_var : !shapex.ranked_shape<[1,?,?,4]>
+  // CHECK-NEXT: util.global.store %[[D2]], @dynamic_var_d2 : index
+  util.global.store %0, @dynamic_var : !shapex.ranked_shape<[1,?,?,4]>
   // CHECK-NEXT: return
   return
 }
diff --git a/iree/compiler/Dialect/Flow/Transforms/test/export_benchmark_funcs.mlir b/iree/compiler/Dialect/Flow/Transforms/test/export_benchmark_funcs.mlir
index 687c3ad..d6b1108 100644
--- a/iree/compiler/Dialect/Flow/Transforms/test/export_benchmark_funcs.mlir
+++ b/iree/compiler/Dialect/Flow/Transforms/test/export_benchmark_funcs.mlir
@@ -8,11 +8,11 @@
   }
 }
 
-// CHECK-DAG: flow.variable @[[MAIN_IN_0:.+]] dense<{{.*}}> : tensor<5x3xf32>
-// CHECK-DAG: flow.variable @[[MAIN_IN_1:.+]] dense<{{.*}}> : tensor<3x5xf32>
+// CHECK-DAG: util.global private @[[MAIN_IN_0:.+]] {noinline} = dense<{{.*}}> : tensor<5x3xf32>
+// CHECK-DAG: util.global private @[[MAIN_IN_1:.+]] {noinline} = dense<{{.*}}> : tensor<3x5xf32>
 //     CHECK: func @two_dispatch_benchmark()
-// CHECK-DAG: %[[ARG0:.+]] = flow.variable.load @[[MAIN_IN_0]] : tensor<5x3xf32>
-// CHECK-DAG: %[[ARG1:.+]] = flow.variable.load @[[MAIN_IN_1]] : tensor<3x5xf32>
+// CHECK-DAG: %[[ARG0:.+]] = util.global.load @[[MAIN_IN_0]] : tensor<5x3xf32>
+// CHECK-DAG: %[[ARG1:.+]] = util.global.load @[[MAIN_IN_1]] : tensor<3x5xf32>
 //     CHECK: %[[RET:.+]]:2 = call @two_dispatch(%[[ARG0]], %[[ARG1]])
 // CHECK-DAG: util.do_not_optimize(%[[RET]]#0) : tensor<5x5xf32>
 // CHECK-DAG: util.do_not_optimize(%[[RET]]#1) : tensor<3x5xf32>
@@ -32,11 +32,11 @@
   return %5 : tensor<i32>
 }
 
-//     CHECK: flow.variable @_benchmark_input_0 dense<0> : tensor<i32> attributes {noinline, sym_visibility = "private"}
-//     CHECK: flow.variable @_benchmark_input_1 dense<0> : tensor<i32> attributes {noinline, sym_visibility = "private"}
+//     CHECK: util.global private @_benchmark_input_0 {noinline} = dense<0> : tensor<i32>
+//     CHECK: util.global private @_benchmark_input_1 {noinline} = dense<0> : tensor<i32>
 //     CHECK: func @while_benchmark() attributes {iree.abi.stub, iree.reflection = {benchmark = "entry"}} {
-// CHECK-DAG:   %[[ARG0:.+]] = flow.variable.load @_benchmark_input_0 : tensor<i32>
-// CHECK-DAG:   %[[ARG1:.+]] = flow.variable.load @_benchmark_input_1 : tensor<i32>
+// CHECK-DAG:   %[[ARG0:.+]] = util.global.load @_benchmark_input_0 : tensor<i32>
+// CHECK-DAG:   %[[ARG1:.+]] = util.global.load @_benchmark_input_1 : tensor<i32>
 //     CHECK:   %[[RET0:.+]] = call @while(%[[ARG0]], %[[ARG1]])
 //     CHECK:   util.do_not_optimize(%[[RET0]]) : tensor<i32>
 //     CHECK:   return
diff --git a/iree/compiler/Dialect/Flow/Transforms/test/insert_constant_clones.mlir b/iree/compiler/Dialect/Flow/Transforms/test/insert_constant_clones.mlir
index b05fed4..06f8b78 100644
--- a/iree/compiler/Dialect/Flow/Transforms/test/insert_constant_clones.mlir
+++ b/iree/compiler/Dialect/Flow/Transforms/test/insert_constant_clones.mlir
@@ -52,10 +52,10 @@
 // -----
 
 // CHECK-LABEL: @constant_variable
-flow.variable @constant_variable dense<1.200000e+00> : tensor<8xf32>
+util.global private @constant_variable = dense<1.200000e+00> : tensor<8xf32>
 func @constant_load() -> (tensor<8xf32>) {
-  // CHECK: %[[VAR:.+]] = flow.variable.load @constant_variable
-  %0 = flow.variable.load @constant_variable : tensor<8xf32>
+  // CHECK: %[[VAR:.+]] = util.global.load @constant_variable
+  %0 = util.global.load @constant_variable : tensor<8xf32>
   // CHECK-NEXT: %[[CLONE:.+]] = flow.tensor.clone %[[VAR]] : tensor<8xf32>
   // CHECK-NEXT: return %[[CLONE]]
   return %0 : tensor<8xf32>
diff --git a/iree/compiler/Dialect/Flow/Transforms/test/outline_large_constants.mlir b/iree/compiler/Dialect/Flow/Transforms/test/outline_large_constants.mlir
index e08392f..3d749dc 100644
--- a/iree/compiler/Dialect/Flow/Transforms/test/outline_large_constants.mlir
+++ b/iree/compiler/Dialect/Flow/Transforms/test/outline_large_constants.mlir
@@ -1,10 +1,10 @@
 // RUN: iree-opt -split-input-file -iree-flow-outline-large-constants %s | IreeFileCheck %s
 
-// CHECK: flow.variable @[[LARGE_VARIABLE:.+]] dense<1.200000e+00> : tensor<512x128xf32>
+// CHECK: util.global private @[[LARGE_VARIABLE:.+]] {noinline} = dense<1.200000e+00> : tensor<512x128xf32>
 func @fn1() -> (tensor<2xf32>, tensor<512x128xf32>) {
   // CHECK-DAG: %[[SMALL_VALUE:.+]] = constant dense<{{.+}}> : tensor<2xf32>
   %cst_0 = constant dense<[0.0287729427, 0.0297581609]> : tensor<2xf32>
-  // CHECK-DAG: %[[LARGE_VALUE:.+]] = flow.variable.load @[[LARGE_VARIABLE]] : tensor<512x128xf32>
+  // CHECK-DAG: %[[LARGE_VALUE:.+]] = util.global.load @[[LARGE_VARIABLE]] : tensor<512x128xf32>
   %cst_1 = constant dense<1.2> : tensor<512x128xf32>
   return %cst_0, %cst_1 : tensor<2xf32>, tensor<512x128xf32>
 }
diff --git a/iree/compiler/Dialect/Flow/Transforms/test/simplify_variable_accesses.mlir b/iree/compiler/Dialect/Flow/Transforms/test/simplify_variable_accesses.mlir
deleted file mode 100644
index 927d193..0000000
--- a/iree/compiler/Dialect/Flow/Transforms/test/simplify_variable_accesses.mlir
+++ /dev/null
@@ -1,136 +0,0 @@
-// RUN: iree-opt -split-input-file -iree-flow-simplify-variable-accesses %s | IreeFileCheck %s
-
-flow.variable @varA dense<1> : tensor<2xi32> attributes {sym_visibility = "private"}
-flow.variable @varB dense<3> : tensor<2x4xi32> attributes {sym_visibility = "private"}
-
-// CHECK-LABEL: @constants()
-func @constants() {
-  // CHECK-NEXT: %[[VAR_A:.+]] = flow.variable.load @varA : tensor<2xi32>
-  // CHECK-NEXT: %[[VAR_B:.+]] = flow.variable.load @varB : tensor<2x4xi32>
-  // CHECK-NEXT: constant 10
-  %w = constant 10 : index
-  %varA = flow.variable.load @varA : tensor<2xi32>
-  // CHECK-NEXT: %[[T:.+]] = flow.dispatch @ex::@dispatch0{{.+}}(%[[VAR_A]])
-  %d0 = flow.dispatch @ex::@dispatch0[%w](%varA) : (tensor<2xi32>) -> tensor<2xi32>
-  %varB = flow.variable.load @varB : tensor<2x4xi32>
-  // CHECK-NEXT: flow.dispatch @ex::@dispatch1{{.+}}(%[[T]], %[[VAR_B]])
-  %d1 = flow.dispatch @ex::@dispatch1[%w](%d0, %varB) : (tensor<2xi32>, tensor<2x4xi32>) -> tensor<2xi32>
-  return
-}
-
-// -----
-
-flow.variable @varA 1 : i32 attributes {sym_visibility = "private"}
-flow.variable @varB 2 : i32 attributes {sym_visibility = "private"}
-
-// CHECK-LABEL: @constants_in_cfg
-func @constants_in_cfg(%start: i32, %bound: i32) -> i32 {
-  // CHECK-NEXT: %[[VAR_A:.+]] = flow.variable.load @varA : i32
-  // CHECK-NEXT: %[[VAR_B:.+]] = flow.variable.load @varB : i32
-  // CHECK-NEXT: br ^bb1
-  br ^bb1(%start : i32)
-// CHECK: ^bb1(%[[BB1_ARG:.+]]: i32):
-^bb1(%2: i32):
-  %cmp = cmpi slt, %2, %bound : i32
-  cond_br %cmp, ^bb2(%2 : i32), ^bb3(%2 : i32)
-// CHECK: ^bb2(%[[BB2_ARG:.+]]: i32):
-^bb2(%5: i32):
-  %6 = flow.variable.load @varA : i32
-  // CHECK-NEXT: = addi %[[BB2_ARG]], %[[VAR_A]] : i32
-  %7 = addi %5, %6 : i32
-  br ^bb1(%7 : i32)
-// CHECK: ^bb3(%[[BB3_ARG:.+]]: i32):
-^bb3(%8: i32):
-  %9 = flow.variable.load @varA : i32
-  // CHECK-NEXT: %[[T0:.+]] = muli %[[BB3_ARG]], %[[VAR_A]] : i32
-  %10 = muli %8, %9 : i32
-  %11 = flow.variable.load @varB : i32
-  // CHECK-NEXT: %[[T1:.+]] = subi %[[T0]], %[[VAR_B]]
-  %12 = subi %10, %11 : i32
-  // CHECK-NEXT: return %[[T1]]
-  return %12 : i32
-}
-
-// -----
-
-flow.variable @varA mutable dense<1> : tensor<2xi32> attributes {sym_visibility = "private"}
-flow.variable @varB dense<3> : tensor<2x4xi32> attributes {sym_visibility = "private"}
-
-// CHECK-LABEL: @mixed_mutability
-func @mixed_mutability() {
-  // CHECK-DAG: %[[VAR_A:.+]] = flow.variable.load @varA : tensor<2xi32>
-  // CHECK-DAG: %[[VAR_B:.+]] = flow.variable.load @varB : tensor<2x4xi32>
-  // CHECK-NEXT: constant 10
-  %w = constant 10 : index
-  %varA = flow.variable.load @varA : tensor<2xi32>
-  // CHECK-NEXT: %[[T0:.+]] = flow.dispatch @ex::@dispatch0{{.+}}(%[[VAR_A]])
-  %d0 = flow.dispatch @ex::@dispatch0[%w](%varA) : (tensor<2xi32>) -> tensor<2xi32>
-  %varB = flow.variable.load @varB : tensor<2x4xi32>
-  // CHECK-NEXT: %[[T1:.+]] = flow.dispatch @ex::@dispatch1{{.+}}(%[[T0]], %[[VAR_B]])
-  %d1 = flow.dispatch @ex::@dispatch1[%w](%d0, %varB) : (tensor<2xi32>, tensor<2x4xi32>) -> tensor<2xi32>
-  // CHECK-NEXT: flow.variable.store %[[T1]], @varA : tensor<2xi32>
-  flow.variable.store %d1, @varA : tensor<2xi32>
-  return
-}
-
-// -----
-
-flow.variable @varA mutable dense<1> : tensor<2xi32> attributes {sym_visibility = "private"}
-
-// CHECK-LABEL: @raw
-func @raw() {
-  // CHECK: %[[T:.+]] = flow.variable.load @varA {id = 0
-  %varA_0 = flow.variable.load @varA {id = 0} : tensor<2xi32>
-  flow.variable.store %varA_0, @varA {id = 0} : tensor<2xi32>
-  %varA_1 = flow.variable.load @varA {id = 1} : tensor<2xi32>
-  // CHECK-NEXT: flow.variable.store %[[T]], @varA {id = 1
-  flow.variable.store %varA_1, @varA {id = 1} : tensor<2xi32>
-  return
-}
-
-// -----
-
-flow.variable @varA mutable dense<1> : tensor<2xi32> attributes {sym_visibility = "private"}
-
-// CHECK-LABEL: @rar
-func @rar() -> (tensor<2xi32>, tensor<2xi32>) {
-  // CHECK: %[[T:.+]] = flow.variable.load @varA {id = 0
-  %varA_0 = flow.variable.load @varA {id = 0} : tensor<2xi32>
-  %varA_1 = flow.variable.load @varA {id = 1} : tensor<2xi32>
-  // CHECK-NEXT: return %[[T]], %[[T]]
-  return %varA_0, %varA_1 : tensor<2xi32>, tensor<2xi32>
-}
-
-// -----
-
-flow.variable @varA mutable dense<1> : tensor<2xi32> attributes {sym_visibility = "private"}
-
-// CHECK-LABEL: @waw
-// CHECK-SAME: (%[[ARG0:.+]]: tensor<2xi32>, %[[ARG1:.+]]: tensor<2xi32>)
-func @waw(%varA_0: tensor<2xi32>, %varA_1: tensor<2xi32>) {
-  flow.variable.store %varA_0, @varA : tensor<2xi32>
-  // CHECK-NEXT: flow.variable.store %[[ARG1]], @varA
-  flow.variable.store %varA_1, @varA : tensor<2xi32>
-  return
-}
-
-// -----
-
-flow.variable @varA mutable dense<1> : tensor<2xi32> attributes {sym_visibility = "private"}
-
-// CHECK-LABEL: @side_effects(
-func @side_effects() {
-  // CHECK-NEXT: %[[T0:.+]] = flow.variable.load @varA
-  %varA_0 = flow.variable.load @varA : tensor<2xi32>
-  // CHECK-NEXT: flow.variable.store %[[T0]], @varA
-  flow.variable.store %varA_0, @varA : tensor<2xi32>
-  // CHECK-NEXT: call @other_fn()
-  call @other_fn() : () -> ()
-  // CHECK-NEXT: %[[T1:.+]] = flow.variable.load @varA
-  %varA_1 = flow.variable.load @varA : tensor<2xi32>
-  // CHECK-NEXT: flow.variable.store %[[T1]], @varA
-  flow.variable.store %varA_1, @varA : tensor<2xi32>
-  return
-}
-
-func private @other_fn()
diff --git a/iree/compiler/Dialect/Flow/Transforms/test/strip_and_splat_constant_variables.mlir b/iree/compiler/Dialect/Flow/Transforms/test/strip_and_splat_constant_variables.mlir
index a703a54..247a351 100644
--- a/iree/compiler/Dialect/Flow/Transforms/test/strip_and_splat_constant_variables.mlir
+++ b/iree/compiler/Dialect/Flow/Transforms/test/strip_and_splat_constant_variables.mlir
@@ -1,11 +1,11 @@
 // RUN: iree-opt -split-input-file -iree-flow-strip-and-splat-constant-variables %s | IreeFileCheck %s
 
 func @fn() -> () {
-  // CHECK: flow.variable @float_0 dense<1.000000e+00> : tensor<3xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @float_0 dense<"0x012345670123456701234567"> : tensor<3xf32> attributes {sym_visibility = "private"}
-  // CHECK: flow.variable @float_1 dense<5.000000e-01> : tensor<3xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @float_1 dense<"0x89ABCDEF89ABCDEF89ABCDEF"> : tensor<3xf32> attributes {sym_visibility = "private"}
-  // CHECK: flow.variable @int_1 dense<3> : tensor<3xi32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @int_1 dense<"0x89ABCDEF89ABCDEF89ABCDEF"> : tensor<3xi32> attributes {sym_visibility = "private"}
+  // CHECK: util.global private @float_0 {noinline} = dense<1.000000e+00> : tensor<3xf32>
+  util.global private @float_0 = dense<"0x012345670123456701234567"> : tensor<3xf32>
+  // CHECK: util.global private @float_1 {noinline} = dense<5.000000e-01> : tensor<3xf32>
+  util.global private @float_1 = dense<"0x89ABCDEF89ABCDEF89ABCDEF"> : tensor<3xf32>
+  // CHECK: util.global private @int_1 {noinline} = dense<3> : tensor<3xi32>
+  util.global private @int_1 = dense<"0x89ABCDEF89ABCDEF89ABCDEF"> : tensor<3xi32>
   return
 }
diff --git a/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/BUILD b/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/BUILD
index be111b6..7410c46 100644
--- a/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/BUILD
+++ b/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/BUILD
@@ -14,9 +14,9 @@
     name = "FlowToHAL",
     srcs = [
         "ConvertFlowToHAL.cpp",
+        "ConvertGlobalOps.cpp",
         "ConvertStreamOps.cpp",
         "ConvertTensorOps.cpp",
-        "ConvertVariableOps.cpp",
     ],
     hdrs = [
         "ConvertFlowToHAL.h",
diff --git a/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/CMakeLists.txt b/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/CMakeLists.txt
index 18ad2ca..d55849b 100644
--- a/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/CMakeLists.txt
+++ b/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/CMakeLists.txt
@@ -17,9 +17,9 @@
     "ConvertFlowToHAL.h"
   SRCS
     "ConvertFlowToHAL.cpp"
+    "ConvertGlobalOps.cpp"
     "ConvertStreamOps.cpp"
     "ConvertTensorOps.cpp"
-    "ConvertVariableOps.cpp"
   DEPS
     LLVMSupport
     MLIRAnalysis
diff --git a/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/ConvertFlowToHAL.cpp b/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/ConvertFlowToHAL.cpp
index 1c89d6c..e78385e 100644
--- a/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/ConvertFlowToHAL.cpp
+++ b/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/ConvertFlowToHAL.cpp
@@ -13,6 +13,11 @@
 namespace mlir {
 namespace iree_compiler {
 
+// Populates only the util.global.* conversion patterns.
+void populateFlowGlobalToHALPatterns(MLIRContext *context,
+                                     OwningRewritePatternList &patterns,
+                                     TypeConverter &converter);
+
 // Populates only the flow.stream.* conversion patterns.
 void populateFlowStreamToHALPatterns(MLIRContext *context,
                                      OwningRewritePatternList &patterns,
@@ -23,11 +28,6 @@
                                      OwningRewritePatternList &patterns,
                                      TypeConverter &converter);
 
-// Populates only the flow.variable.* conversion patterns.
-void populateFlowVariableToHALPatterns(MLIRContext *context,
-                                       OwningRewritePatternList &patterns,
-                                       TypeConverter &converter);
-
 void setupFlowToHALLegality(MLIRContext *context,
                             ConversionTarget &conversionTarget,
                             TypeConverter &typeConverter) {
@@ -38,9 +38,9 @@
 void populateFlowToHALPatterns(MLIRContext *context,
                                OwningRewritePatternList &patterns,
                                TypeConverter &typeConverter) {
+  populateFlowGlobalToHALPatterns(context, patterns, typeConverter);
   populateFlowStreamToHALPatterns(context, patterns, typeConverter);
   populateFlowTensorToHALPatterns(context, patterns, typeConverter);
-  populateFlowVariableToHALPatterns(context, patterns, typeConverter);
 }
 
 }  // namespace iree_compiler
diff --git a/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/ConvertGlobalOps.cpp b/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/ConvertGlobalOps.cpp
new file mode 100644
index 0000000..7bf6d47
--- /dev/null
+++ b/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/ConvertGlobalOps.cpp
@@ -0,0 +1,239 @@
+// Copyright 2019 The IREE Authors
+//
+// Licensed under the Apache License v2.0 with LLVM Exceptions.
+// See https://llvm.org/LICENSE.txt for license information.
+// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+
+#include "iree/compiler/Dialect/Flow/IR/FlowOps.h"
+#include "iree/compiler/Dialect/HAL/Conversion/FlowToHAL/ConvertFlowToHAL.h"
+#include "iree/compiler/Dialect/HAL/IR/HALOps.h"
+#include "iree/compiler/Dialect/HAL/IR/HALTypes.h"
+#include "iree/compiler/Dialect/HAL/Utils/TypeUtils.h"
+#include "iree/compiler/Dialect/Util/IR/UtilTypes.h"
+#include "llvm/ADT/DenseMap.h"
+#include "mlir/Dialect/StandardOps/IR/Ops.h"
+#include "mlir/IR/Attributes.h"
+#include "mlir/IR/BlockAndValueMapping.h"
+#include "mlir/IR/Builders.h"
+#include "mlir/IR/BuiltinOps.h"
+#include "mlir/IR/Matchers.h"
+#include "mlir/Transforms/DialectConversion.h"
+
+namespace mlir {
+namespace iree_compiler {
+namespace {
+
+static FuncOp createInitializerFromImmediate(
+    IREE::Util::GlobalOp globalOp, ElementsAttr immediateElements,
+    ConversionPatternRewriter &rewriter) {
+  auto loc = globalOp.getLoc();
+  auto initializerType = FunctionType::get(rewriter.getContext(), {},
+                                           {immediateElements.getType()});
+  // TODO(b/145839814): It is presently possible to collide with user
+  // provided symbols and it seems like it shouldn't be.
+  auto uniqueName = (Twine("__") + globalOp.getName() + "_initializer").str();
+  auto initializerFuncOp =
+      rewriter.create<FuncOp>(globalOp.getLoc(), uniqueName, initializerType);
+  rewriter.createBlock(&initializerFuncOp.getBody(), initializerFuncOp.begin(),
+                       initializerType.getInputs());
+
+  // Create const and return ops.
+  auto constValue = rewriter.create<ConstantOp>(loc, immediateElements);
+  rewriter.create<mlir::ReturnOp>(loc, constValue.getResult());
+  return initializerFuncOp;
+}
+
+class GlobalOpConversion : public OpConversionPattern<IREE::Util::GlobalOp> {
+ public:
+  GlobalOpConversion(MLIRContext *ctx, TypeConverter &converter)
+      : OpConversionPattern(ctx), converter(converter) {}
+
+  LogicalResult matchAndRewrite(
+      IREE::Util::GlobalOp globalOp, llvm::ArrayRef<Value> newOperands,
+      ConversionPatternRewriter &rewriter) const override {
+    // TODO(benvanik): multiple converted type results to multiple globals.
+    Optional<StringRef> initializer = globalOp.initializer();
+    Optional<Attribute> initialValue = globalOp.initial_value();
+
+    // Hoist any immediate initial_value elements to an initializer function
+    // that returns it. This will then be converted by the framework to
+    // an appropriate HAL Buffer-based initializer.
+    if (auto initialValueElements =
+            globalOp.initial_valueAttr().dyn_cast_or_null<ElementsAttr>()) {
+      rewriter.setInsertionPointAfter(globalOp);
+      auto initializerFunc = createInitializerFromImmediate(
+          globalOp, initialValueElements, rewriter);
+      initializer = initializerFunc.getName();
+      initialValue = llvm::None;
+    }
+
+    rewriter.setInsertionPoint(globalOp);
+    auto newOp = rewriter.create<IREE::Util::GlobalOp>(
+        globalOp.getLoc(), globalOp.sym_name(), globalOp.is_mutable(),
+        converter.convertType(globalOp.type()), initializer, initialValue,
+        llvm::to_vector<4>(globalOp->getDialectAttrs()));
+    newOp.setVisibility(globalOp.getVisibility());
+    rewriter.replaceOp(globalOp, {});
+    return success();
+  }
+
+ private:
+  TypeConverter &converter;
+};
+
+class GlobalAddressOpConversion
+    : public OpConversionPattern<IREE::Util::GlobalAddressOp> {
+ public:
+  GlobalAddressOpConversion(MLIRContext *ctx, TypeConverter &converter)
+      : OpConversionPattern(ctx), converter(converter) {}
+
+  LogicalResult matchAndRewrite(
+      IREE::Util::GlobalAddressOp addressOp, llvm::ArrayRef<Value> newOperands,
+      ConversionPatternRewriter &rewriter) const override {
+    // TODO(benvanik): multiple converted type results to multiple globals.
+    rewriter.replaceOpWithNewOp<IREE::Util::GlobalAddressOp>(
+        addressOp, converter.convertType(addressOp.result().getType()),
+        addressOp.global());
+    return success();
+  }
+
+ private:
+  TypeConverter &converter;
+};
+
+class GlobalLoadOpConversion
+    : public OpConversionPattern<IREE::Util::GlobalLoadOp> {
+ public:
+  GlobalLoadOpConversion(MLIRContext *ctx, TypeConverter &converter)
+      : OpConversionPattern(ctx), converter(converter) {}
+
+  LogicalResult matchAndRewrite(
+      IREE::Util::GlobalLoadOp loadOp, llvm::ArrayRef<Value> newOperands,
+      ConversionPatternRewriter &rewriter) const override {
+    // TODO(benvanik): multiple converted type results to multiple globals.
+    rewriter.replaceOpWithNewOp<IREE::Util::GlobalLoadOp>(
+        loadOp, converter.convertType(loadOp.result().getType()),
+        rewriter.getSymbolRefAttr(loadOp.global()));
+    return success();
+  }
+
+ private:
+  TypeConverter &converter;
+};
+
+class GlobalLoadIndirectOpConversion
+    : public OpConversionPattern<IREE::Util::GlobalLoadIndirectOp> {
+ public:
+  GlobalLoadIndirectOpConversion(MLIRContext *ctx, TypeConverter &converter)
+      : OpConversionPattern(ctx), converter(converter) {}
+
+  LogicalResult matchAndRewrite(
+      IREE::Util::GlobalLoadIndirectOp loadOp,
+      llvm::ArrayRef<Value> newOperands,
+      ConversionPatternRewriter &rewriter) const override {
+    IREE::Util::GlobalLoadIndirectOp::Adaptor operands(newOperands);
+    // TODO(benvanik): multiple converted type results to multiple globals.
+    rewriter.replaceOpWithNewOp<IREE::Util::GlobalLoadIndirectOp>(
+        loadOp, converter.convertType(loadOp.result().getType()),
+        operands.global());
+    return success();
+  }
+
+ private:
+  TypeConverter &converter;
+};
+
+namespace {
+
+Value implicitCastGlobalStore(Location loc, Value storeValue, Type globalType,
+                              ConversionPatternRewriter &rewriter) {
+  Type storeType = storeValue.getType();
+
+  // A limited number of implicit conversions on store are allowed.
+  if (globalType != storeType) {
+    if (storeType.isa<IREE::HAL::BufferViewType>() &&
+        globalType.isa<IREE::HAL::BufferType>()) {
+      return rewriter.create<IREE::HAL::BufferViewBufferOp>(loc, globalType,
+                                                            storeValue);
+    } else {
+      return nullptr;
+    }
+  }
+  return storeValue;
+}
+
+}  // namespace
+
+class GlobalStoreOpConversion
+    : public OpConversionPattern<IREE::Util::GlobalStoreOp> {
+ public:
+  GlobalStoreOpConversion(MLIRContext *ctx, TypeConverter &converter)
+      : OpConversionPattern(ctx), converter(converter) {}
+
+  LogicalResult matchAndRewrite(
+      IREE::Util::GlobalStoreOp storeOp, llvm::ArrayRef<Value> newOperands,
+      ConversionPatternRewriter &rewriter) const override {
+    IREE::Util::GlobalStoreOp::Adaptor operands(newOperands);
+    auto globalOp = storeOp.getGlobalOp();
+    if (!globalOp) return failure();
+
+    Type globalType = converter.convertType(globalOp.type());
+    if (!globalType) {
+      return rewriter.notifyMatchFailure(storeOp, "illegal global op type");
+    }
+    Value storeValue = implicitCastGlobalStore(
+        storeOp.getLoc(), operands.value(), globalType, rewriter);
+    if (!storeValue) {
+      return rewriter.notifyMatchFailure(storeOp,
+                                         "mismatched store and global type");
+    }
+    // TODO(benvanik): multiple converted type results to multiple globals.
+    rewriter.replaceOpWithNewOp<IREE::Util::GlobalStoreOp>(
+        storeOp, storeValue, rewriter.getSymbolRefAttr(storeOp.global()));
+    return success();
+  }
+
+  TypeConverter &converter;
+};
+
+class GlobalStoreIndirectOpConversion
+    : public OpConversionPattern<IREE::Util::GlobalStoreIndirectOp> {
+ public:
+  GlobalStoreIndirectOpConversion(MLIRContext *ctx, TypeConverter &converter)
+      : OpConversionPattern(ctx) {}
+
+  LogicalResult matchAndRewrite(
+      IREE::Util::GlobalStoreIndirectOp storeOp,
+      llvm::ArrayRef<Value> newOperands,
+      ConversionPatternRewriter &rewriter) const override {
+    IREE::Util::GlobalStoreIndirectOp::Adaptor operands(newOperands);
+
+    Type globalType =
+        operands.global().getType().cast<IREE::Util::PtrType>().getTargetType();
+    Value storeValue = implicitCastGlobalStore(
+        storeOp.getLoc(), operands.value(), globalType, rewriter);
+    if (!storeValue) {
+      return rewriter.notifyMatchFailure(storeOp,
+                                         "mismatched store and global type");
+    }
+
+    // TODO(benvanik): multiple converted type results to multiple globals.
+    rewriter.replaceOpWithNewOp<IREE::Util::GlobalStoreIndirectOp>(
+        storeOp, storeValue, operands.global());
+    return success();
+  }
+};
+
+}  // namespace
+
+void populateFlowGlobalToHALPatterns(MLIRContext *context,
+                                     OwningRewritePatternList &patterns,
+                                     TypeConverter &converter) {
+  patterns.insert<GlobalOpConversion, GlobalAddressOpConversion,
+                  GlobalLoadOpConversion, GlobalLoadIndirectOpConversion,
+                  GlobalStoreOpConversion, GlobalStoreIndirectOpConversion>(
+      context, converter);
+}
+
+}  // namespace iree_compiler
+}  // namespace mlir
diff --git a/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/ConvertStreamOps.cpp b/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/ConvertStreamOps.cpp
index dc56b79..83d6d35 100644
--- a/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/ConvertStreamOps.cpp
+++ b/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/ConvertStreamOps.cpp
@@ -274,15 +274,15 @@
   }
 
   // Loads a variable with the given |symName|.
-  Value loadVariable(Type resultType, StringRef symName, OpBuilder &builder) {
-    auto it = loadedVariableMap.find(symName);
-    if (it != loadedVariableMap.end()) {
+  Value loadGlobal(Type resultType, StringRef symName, OpBuilder &builder) {
+    auto it = loadedGlobalMap.find(symName);
+    if (it != loadedGlobalMap.end()) {
       assert(it->second.getType() == resultType && "variable type mismatch");
       return it->second;
     }
-    auto value = builder.createOrFold<IREE::HAL::VariableLoadOp>(
-        loc, resultType, symName);
-    loadedVariableMap.insert(std::make_pair(symName, value));
+    auto value = builder.createOrFold<IREE::Util::GlobalLoadOp>(loc, resultType,
+                                                                symName);
+    loadedGlobalMap.insert(std::make_pair(symName, value));
     return value;
   }
 
@@ -420,8 +420,8 @@
   // Index value -> std.constant index value.
   DenseMap<int64_t, Value> indexConstantMap;
 
-  // Variable sym name -> loaded value.
-  DenseMap<StringRef, Value> loadedVariableMap;
+  // Global sym name -> loaded value.
+  DenseMap<StringRef, Value> loadedGlobalMap;
 
   // Key of [push constants, set layouts] -> loaded value.
   DenseMap<Attribute, Value> executableLayoutMap;
@@ -556,7 +556,7 @@
   SmallPtrSet<Value, 16> coveredValues;
   auto walkResult = streamOp.walk([&](IREE::HAL::ConstantSubspanOp subspanOp) {
     auto tensorValue = subspanOp.result();
-    auto bufferValue = schedulingState.loadVariable(
+    auto bufferValue = schedulingState.loadGlobal(
         IREE::HAL::BufferType::get(rewriter.getContext()),
         subspanOp.runtime_buffer().getLeafReference(), rewriter);
     auto offsetValue = schedulingState.lookupOrCreateIndex(
@@ -722,7 +722,7 @@
           constantStorageAttr.binding());
       assert(bindingOp);
       assert(bindingOp.set().getSExtValue() == setOrdinal);
-      auto storageBuffer = schedulingState.loadVariable(
+      auto storageBuffer = schedulingState.loadGlobal(
           IREE::HAL::BufferType::get(builder.getContext()),
           constantStorageAttr.storage(), rewriter);
       bindings.push_back(std::make_tuple(
diff --git a/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/ConvertVariableOps.cpp b/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/ConvertVariableOps.cpp
deleted file mode 100644
index 169f86a..0000000
--- a/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/ConvertVariableOps.cpp
+++ /dev/null
@@ -1,257 +0,0 @@
-// Copyright 2019 The IREE Authors
-//
-// Licensed under the Apache License v2.0 with LLVM Exceptions.
-// See https://llvm.org/LICENSE.txt for license information.
-// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
-
-#include "iree/compiler/Dialect/Flow/IR/FlowOps.h"
-#include "iree/compiler/Dialect/HAL/Conversion/FlowToHAL/ConvertFlowToHAL.h"
-#include "iree/compiler/Dialect/HAL/IR/HALOps.h"
-#include "iree/compiler/Dialect/HAL/IR/HALTypes.h"
-#include "iree/compiler/Dialect/HAL/Utils/TypeUtils.h"
-#include "iree/compiler/Dialect/Util/IR/UtilTypes.h"
-#include "llvm/ADT/DenseMap.h"
-#include "mlir/Dialect/StandardOps/IR/Ops.h"
-#include "mlir/IR/Attributes.h"
-#include "mlir/IR/BlockAndValueMapping.h"
-#include "mlir/IR/Builders.h"
-#include "mlir/IR/BuiltinOps.h"
-#include "mlir/IR/Matchers.h"
-#include "mlir/Transforms/DialectConversion.h"
-
-namespace mlir {
-namespace iree_compiler {
-namespace {
-
-static FuncOp createInitializerFromImmediate(
-    IREE::Flow::VariableOp variableOp, ElementsAttr immediateElements,
-    ConversionPatternRewriter &rewriter) {
-  auto loc = variableOp.getLoc();
-  auto initializerType = FunctionType::get(rewriter.getContext(), {},
-                                           {immediateElements.getType()});
-  // TODO(b/145839814): It is presently possible to collide with user
-  // provided symbols and it seems like it shouldn't be.
-  auto uniqueName = (Twine("__") + variableOp.getName() + "_initializer").str();
-  auto initializerFuncOp =
-      rewriter.create<FuncOp>(variableOp.getLoc(), uniqueName, initializerType);
-  rewriter.createBlock(&initializerFuncOp.getBody(), initializerFuncOp.begin(),
-                       initializerType.getInputs());
-
-  // Create const and return ops.
-  auto constValue = rewriter.create<ConstantOp>(loc, immediateElements);
-  rewriter.create<mlir::ReturnOp>(loc, constValue.getResult());
-  return initializerFuncOp;
-}
-
-class VariableOpConversion
-    : public OpConversionPattern<IREE::Flow::VariableOp> {
- public:
-  VariableOpConversion(MLIRContext *ctx, TypeConverter &converter)
-      : OpConversionPattern(ctx), converter(converter) {}
-
-  LogicalResult matchAndRewrite(
-      IREE::Flow::VariableOp variableOp, llvm::ArrayRef<Value> newOperands,
-      ConversionPatternRewriter &rewriter) const override {
-    // TODO(benvanik): multiple converted type results to multiple variables.
-    Optional<StringRef> initializer = variableOp.initializer();
-    Optional<Attribute> initialValue = variableOp.initial_value();
-
-    // Hoist any immediate initial_value elements to an initializer function
-    // that returns it. This will then be converted by the framework to
-    // an appropriate HAL Buffer-based initializer.
-    if (auto initialValueElements =
-            variableOp.initial_valueAttr().dyn_cast_or_null<ElementsAttr>()) {
-      rewriter.setInsertionPointAfter(variableOp);
-      auto initializerFunc = createInitializerFromImmediate(
-          variableOp, initialValueElements, rewriter);
-      initializer = initializerFunc.getName();
-      initialValue = llvm::None;
-    }
-
-    rewriter.setInsertionPoint(variableOp);
-    auto newOp = rewriter.create<IREE::HAL::VariableOp>(
-        variableOp.getLoc(), variableOp.sym_name(), variableOp.is_mutable(),
-        converter.convertType(variableOp.type()), initializer, initialValue,
-        llvm::to_vector<4>(variableOp->getDialectAttrs()));
-    newOp.setVisibility(variableOp.getVisibility());
-    rewriter.replaceOp(variableOp, {});
-    return success();
-  }
-
- private:
-  TypeConverter &converter;
-};
-
-class VariableAddressOpConversion
-    : public OpConversionPattern<IREE::Flow::VariableAddressOp> {
- public:
-  VariableAddressOpConversion(MLIRContext *ctx, TypeConverter &converter)
-      : OpConversionPattern(ctx), converter(converter) {}
-
-  LogicalResult matchAndRewrite(
-      IREE::Flow::VariableAddressOp addressOp,
-      llvm::ArrayRef<Value> newOperands,
-      ConversionPatternRewriter &rewriter) const override {
-    // TODO(benvanik): multiple converted type results to multiple variables.
-    rewriter.replaceOpWithNewOp<IREE::HAL::VariableAddressOp>(
-        addressOp, converter.convertType(addressOp.result().getType()),
-        addressOp.variable());
-    return success();
-  }
-
- private:
-  TypeConverter &converter;
-};
-
-class VariableLoadOpConversion
-    : public OpConversionPattern<IREE::Flow::VariableLoadOp> {
- public:
-  VariableLoadOpConversion(MLIRContext *ctx, TypeConverter &converter)
-      : OpConversionPattern(ctx), converter(converter) {}
-
-  LogicalResult matchAndRewrite(
-      IREE::Flow::VariableLoadOp loadOp, llvm::ArrayRef<Value> newOperands,
-      ConversionPatternRewriter &rewriter) const override {
-    // TODO(benvanik): multiple converted type results to multiple variables.
-    rewriter.replaceOpWithNewOp<IREE::HAL::VariableLoadOp>(
-        loadOp, converter.convertType(loadOp.result().getType()),
-        rewriter.getSymbolRefAttr(loadOp.variable()));
-    return success();
-  }
-
- private:
-  TypeConverter &converter;
-};
-
-class VariableLoadIndirectOpConversion
-    : public OpConversionPattern<IREE::Flow::VariableLoadIndirectOp> {
- public:
-  VariableLoadIndirectOpConversion(MLIRContext *ctx, TypeConverter &converter)
-      : OpConversionPattern(ctx), converter(converter) {}
-
-  LogicalResult matchAndRewrite(
-      IREE::Flow::VariableLoadIndirectOp loadOp,
-      llvm::ArrayRef<Value> newOperands,
-      ConversionPatternRewriter &rewriter) const override {
-    // TODO(benvanik): multiple converted type results to multiple variables.
-    rewriter.replaceOpWithNewOp<IREE::HAL::VariableLoadIndirectOp>(
-        loadOp, converter.convertType(loadOp.result().getType()),
-        loadOp.variable());
-    return success();
-  }
-
- private:
-  TypeConverter &converter;
-};
-
-namespace {
-
-Value implicitCastVariableStore(Location loc, Value storeValue,
-                                Type variableType,
-                                ConversionPatternRewriter &rewriter) {
-  Type storeType = storeValue.getType();
-
-  // A limited number of implicit conversions on store are allowed.
-  if (variableType != storeType) {
-    if (storeType.isa<IREE::HAL::BufferViewType>() &&
-        variableType.isa<IREE::HAL::BufferType>()) {
-      return rewriter.create<IREE::HAL::BufferViewBufferOp>(loc, variableType,
-                                                            storeValue);
-    } else {
-      return nullptr;
-    }
-  }
-  return storeValue;
-}
-
-}  // namespace
-
-class VariableStoreOpConversion
-    : public OpConversionPattern<IREE::Flow::VariableStoreOp> {
- public:
-  VariableStoreOpConversion(MLIRContext *ctx, TypeConverter &converter)
-      : OpConversionPattern(ctx), converter(converter) {}
-
-  LogicalResult matchAndRewrite(
-      IREE::Flow::VariableStoreOp storeOp, llvm::ArrayRef<Value> newOperands,
-      ConversionPatternRewriter &rewriter) const override {
-    IREE::Flow::VariableStoreOp::Adaptor operands(newOperands);
-    auto *variableOp =
-        SymbolTable::lookupNearestSymbolFrom(storeOp, storeOp.variable());
-    if (!variableOp) return failure();
-
-    Type variableType = getVariableType(variableOp);
-    if (!variableType) {
-      return rewriter.notifyMatchFailure(storeOp, "illegal variable op type");
-    }
-    Value storeValue = implicitCastVariableStore(
-        storeOp.getLoc(), operands.value(), variableType, rewriter);
-    if (!storeValue) {
-      return rewriter.notifyMatchFailure(storeOp,
-                                         "mismatched store and variable type");
-    }
-    // TODO(benvanik): multiple converted type results to multiple variables.
-    rewriter.replaceOpWithNewOp<IREE::HAL::VariableStoreOp>(
-        storeOp, storeValue, rewriter.getSymbolRefAttr(storeOp.variable()));
-    return success();
-  }
-
-  Type getVariableType(Operation *variableOp) const {
-    if (auto halVariableOp = dyn_cast<IREE::HAL::VariableOp>(variableOp)) {
-      return halVariableOp.type();
-    } else if (auto flowVariableOp =
-                   dyn_cast<IREE::Flow::VariableOp>(variableOp)) {
-      // If the variable referent is not in dominance order at the module level,
-      // it may not have been converted yet. So get the unconverted op and
-      // convert its type to allow variables and uses in any order.
-      return converter.convertType(flowVariableOp.type());
-    }
-
-    return nullptr;
-  }
-
-  TypeConverter &converter;
-};
-
-class VariableStoreIndirectOpConversion
-    : public OpConversionPattern<IREE::Flow::VariableStoreIndirectOp> {
- public:
-  VariableStoreIndirectOpConversion(MLIRContext *ctx, TypeConverter &converter)
-      : OpConversionPattern(ctx) {}
-
-  LogicalResult matchAndRewrite(
-      IREE::Flow::VariableStoreIndirectOp storeOp,
-      llvm::ArrayRef<Value> newOperands,
-      ConversionPatternRewriter &rewriter) const override {
-    IREE::Flow::VariableStoreIndirectOp::Adaptor operands(newOperands);
-
-    Type variableType = operands.variable()
-                            .getType()
-                            .cast<IREE::Util::PtrType>()
-                            .getTargetType();
-    Value storeValue = implicitCastVariableStore(
-        storeOp.getLoc(), operands.value(), variableType, rewriter);
-    if (!storeValue) {
-      return rewriter.notifyMatchFailure(storeOp,
-                                         "mismatched store and variable type");
-    }
-    // TODO(benvanik): multiple converted type results to multiple variables.
-    rewriter.replaceOpWithNewOp<IREE::HAL::VariableStoreIndirectOp>(
-        storeOp, storeValue, storeOp.variable());
-    return success();
-  }
-};
-
-}  // namespace
-
-void populateFlowVariableToHALPatterns(MLIRContext *context,
-                                       OwningRewritePatternList &patterns,
-                                       TypeConverter &converter) {
-  patterns.insert<VariableOpConversion, VariableAddressOpConversion,
-                  VariableLoadOpConversion, VariableLoadIndirectOpConversion,
-                  VariableStoreOpConversion, VariableStoreIndirectOpConversion>(
-      context, converter);
-}
-
-}  // namespace iree_compiler
-}  // namespace mlir
diff --git a/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/test/BUILD b/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/test/BUILD
index 8ef4103..b62dea8 100644
--- a/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/test/BUILD
+++ b/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/test/BUILD
@@ -18,9 +18,9 @@
     srcs = enforce_glob(
         [
             "constant_ops.mlir",
+            "global_ops.mlir",
             "stream_ops.mlir",
             "tensor_ops.mlir",
-            "variable_ops.mlir",
         ],
         include = ["*.mlir"],
     ),
diff --git a/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/test/CMakeLists.txt b/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/test/CMakeLists.txt
index ceb1dcf..5dda815 100644
--- a/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/test/CMakeLists.txt
+++ b/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/test/CMakeLists.txt
@@ -15,9 +15,9 @@
     lit
   SRCS
     "constant_ops.mlir"
+    "global_ops.mlir"
     "stream_ops.mlir"
     "tensor_ops.mlir"
-    "variable_ops.mlir"
   DATA
     iree::tools::IreeFileCheck
     iree::tools::iree-opt
diff --git a/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/test/constant_ops.mlir b/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/test/constant_ops.mlir
index 34f51cc..dad4625 100644
--- a/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/test/constant_ops.mlir
+++ b/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/test/constant_ops.mlir
@@ -1,38 +1,38 @@
 // RUN: iree-opt -split-input-file -iree-convert-to-hal -verify-diagnostics %s | IreeFileCheck %s
 
-// CHECK-LABEL: hal.variable @var_i32 mutable : !hal.buffer
-flow.variable @var_i32 mutable : tensor<i32>
+// CHECK-LABEL: util.global public mutable @var_i32 : !hal.buffer
+util.global public mutable @var_i32 : tensor<i32>
 func @fn() {
-  // CHECK: %[[V:.+]] = hal.variable.load @var_i32 : !hal.buffer
-  %0 = flow.variable.load @var_i32 : tensor<i32>
-  // CHECK-NEXT: hal.variable.store %[[V]], @var_i32 : !hal.buffer
-  flow.variable.store %0, @var_i32 : tensor<i32>
+  // CHECK: %[[V:.+]] = util.global.load @var_i32 : !hal.buffer
+  %0 = util.global.load @var_i32 : tensor<i32>
+  // CHECK-NEXT: util.global.store %[[V]], @var_i32 : !hal.buffer
+  util.global.store %0, @var_i32 : tensor<i32>
   return
 }
 
 // -----
 
-// CHECK-LABEL: hal.variable @var_i1 mutable : !hal.buffer
-flow.variable @var_i1 mutable : tensor<i1>
+// CHECK-LABEL: util.global public mutable @var_i1 : !hal.buffer
+util.global public mutable @var_i1 : tensor<i1>
 func @fn() {
-  // CHECK: %[[V:.+]] = hal.variable.load @var_i1 : !hal.buffer
-  %0 = flow.variable.load @var_i1 : tensor<i1>
-  // CHECK-NEXT: hal.variable.store %[[V]], @var_i1 : !hal.buffer
-  flow.variable.store %0, @var_i1 : tensor<i1>
+  // CHECK: %[[V:.+]] = util.global.load @var_i1 : !hal.buffer
+  %0 = util.global.load @var_i1 : tensor<i1>
+  // CHECK-NEXT: util.global.store %[[V]], @var_i1 : !hal.buffer
+  util.global.store %0, @var_i1 : tensor<i1>
   return
 }
 
 // -----
 
-// CHECK-LABEL: hal.variable @var_indirect mutable : !hal.buffer
-flow.variable @var_indirect mutable : tensor<i32>
+// CHECK-LABEL: util.global public mutable @var_indirect : !hal.buffer
+util.global public mutable @var_indirect : tensor<i32>
 func @fn() {
-  // CHECK: %[[ADDR:.+]] = hal.variable.address @var_indirect
-  %0 = flow.variable.address @var_indirect : !util.ptr<tensor<i32>>
-  // CHECK-NEXT: %[[VALUE:.+]] = hal.variable.load.indirect %[[ADDR]]
-  %1 = flow.variable.load.indirect %0 : !util.ptr<tensor<i32>> -> tensor<i32>
-  // CHECK-NEXT: hal.variable.store.indirect %[[VALUE]], %[[ADDR]]
-  flow.variable.store.indirect %1, %0 : tensor<i32> -> !util.ptr<tensor<i32>>
+  // CHECK: %[[ADDR:.+]] = util.global.address @var_indirect
+  %0 = util.global.address @var_indirect : !util.ptr<tensor<i32>>
+  // CHECK-NEXT: %[[VALUE:.+]] = util.global.load.indirect %[[ADDR]]
+  %1 = util.global.load.indirect %0 : !util.ptr<tensor<i32>> -> tensor<i32>
+  // CHECK-NEXT: util.global.store.indirect %[[VALUE]], %[[ADDR]]
+  util.global.store.indirect %1, %0 : tensor<i32> -> !util.ptr<tensor<i32>>
   return
 }
 
@@ -40,14 +40,14 @@
 
 // Checks that an initializer function is generated, used and operates on
 // a hal.buffer (versus tensor).
-// CHECK: hal.variable @var_with_tensor_default
-// CHECK-SAME: init(@__var_with_tensor_default_initializer)
+// CHECK: util.global public mutable @var_with_tensor_default
+// CHECK-SAME: initializer(@__var_with_tensor_default_initializer)
 // CHECK-SAME: : !hal.buffer
 // CHECK-LABEL: func @__var_with_tensor_default_initializer() -> !hal.buffer
-flow.variable @var_with_tensor_default mutable dense<0.000000e+00> : tensor<f32>
+util.global public mutable @var_with_tensor_default = dense<0.000000e+00> : tensor<f32>
 func @fn() {
-  %0 = flow.variable.load @var_with_tensor_default : tensor<f32>
-  flow.variable.store %0, @var_with_tensor_default : tensor<f32>
+  %0 = util.global.load @var_with_tensor_default : tensor<f32>
+  util.global.store %0, @var_with_tensor_default : tensor<f32>
   return
 }
 
@@ -57,9 +57,9 @@
 // expected-error @+3 {{redefinition of symbol named '__var_with_initializer_initializer'}}
 // expected-note @+1 {{see existing symbol definition here}}
 func private @__var_with_initializer_initializer() -> ()
-flow.variable @var_with_initializer mutable dense<0.000000e+00> : tensor<f32>
+util.global public mutable @var_with_initializer = dense<0.000000e+00> : tensor<f32>
 func @fn() {
-  %0 = flow.variable.load @var_with_initializer : tensor<f32>
-  flow.variable.store %0, @var_with_initializer : tensor<f32>
+  %0 = util.global.load @var_with_initializer : tensor<f32>
+  util.global.store %0, @var_with_initializer : tensor<f32>
   return
 }
diff --git a/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/test/global_ops.mlir b/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/test/global_ops.mlir
new file mode 100644
index 0000000..cc107a0
--- /dev/null
+++ b/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/test/global_ops.mlir
@@ -0,0 +1,104 @@
+// RUN: iree-opt -split-input-file -iree-convert-to-hal -verify-diagnostics %s | IreeFileCheck %s
+
+// CHECK-LABEL: util.global public mutable @var_i32 : !hal.buffer
+util.global public mutable @var_i32 : tensor<i32>
+func @fn() {
+  // CHECK: %[[V:.+]] = util.global.load @var_i32 : !hal.buffer
+  %0 = util.global.load @var_i32 : tensor<i32>
+  // CHECK-NEXT: util.global.store %[[V]], @var_i32 : !hal.buffer
+  util.global.store %0, @var_i32 : tensor<i32>
+  return
+}
+
+// -----
+
+// CHECK-LABEL: util.global public mutable @var_i1 : !hal.buffer
+util.global public mutable @var_i1 : tensor<i1>
+func @fn() {
+  // CHECK: %[[V:.+]] = util.global.load @var_i1 : !hal.buffer
+  %0 = util.global.load @var_i1 : tensor<i1>
+  // CHECK-NEXT: util.global.store %[[V]], @var_i1 : !hal.buffer
+  util.global.store %0, @var_i1 : tensor<i1>
+  return
+}
+
+// -----
+
+// CHECK-LABEL: util.global public mutable @var_indirect : !hal.buffer
+util.global public mutable @var_indirect : tensor<i32>
+func @fn() {
+  // CHECK: %[[ADDR:.+]] = util.global.address @var_indirect
+  %0 = util.global.address @var_indirect : !util.ptr<tensor<i32>>
+  // CHECK-NEXT: %[[VALUE:.+]] = util.global.load.indirect %[[ADDR]]
+  %1 = util.global.load.indirect %0 : !util.ptr<tensor<i32>> -> tensor<i32>
+  // CHECK-NEXT: util.global.store.indirect %[[VALUE]], %[[ADDR]]
+  util.global.store.indirect %1, %0 : tensor<i32> -> !util.ptr<tensor<i32>>
+  return
+}
+
+// -----
+// Checks that an initializer function is generated, used and operates on
+// a hal.buffer (versus tensor).
+// CHECK: util.global public mutable @var_with_tensor_initializer
+// CHECK-SAME: initializer(@__var_with_tensor_initializer_initializer)
+// CHECK-SAME: : !hal.buffer
+// CHECK-LABEL: func @__var_with_tensor_initializer_initializer() -> !hal.buffer
+util.global public mutable @var_with_tensor_initializer = dense<0.000000e+00> : tensor<f32>
+func @fn() {
+  %0 = util.global.load @var_with_tensor_initializer : tensor<f32>
+  util.global.store %0, @var_with_tensor_initializer : tensor<f32>
+  return
+}
+
+// -----
+// TODO(b/145839814): It should not be possible to produce a name collision
+// expected-error @+3 {{redefinition of symbol named '__var_with_initializer_initializer'}}
+// expected-note @+1 {{see existing symbol definition here}}
+func private @__var_with_initializer_initializer() -> ()
+util.global public mutable @var_with_initializer = dense<0.000000e+00> : tensor<f32>
+func @fn() {
+  %0 = util.global.load @var_with_initializer : tensor<f32>
+  util.global.store %0, @var_with_initializer : tensor<f32>
+  return
+}
+
+// -----
+// Checks that the implicit cast allowing a buffer_view to store into a variable
+// that maps to a buffer is permitted.
+// CHECK-LABEL: util.global public mutable @var_with_buffer_view_store
+// CHECK: %[[buffer:.*]] = hal.buffer_view.buffer %arg0 : !hal.buffer
+// CHECK: util.global.store %[[buffer]], @var_with_buffer_view_store : !hal.buffer
+util.global public mutable @var_with_buffer_view_store = dense<0.000000e+00> : tensor<f32>
+func @fn(%arg0: !hal.buffer_view) {
+  %0 = hal.tensor.cast %arg0 : !hal.buffer_view -> tensor<f32>
+  util.global.store %0, @var_with_buffer_view_store : tensor<f32>
+  return
+}
+
+// -----
+// Checks that stores are permitted for variables that do not dominate the
+// function containing a store.
+// CHECK-LABEL: func @store_var_out_of_order
+// CHECK: %[[buffer:.*]] = hal.buffer_view.buffer %arg0 : !hal.buffer
+// CHECK: util.global.store %[[buffer]], @var_out_of_order : !hal.buffer
+func @store_var_out_of_order(%arg0: !hal.buffer_view) {
+  %0 = hal.tensor.cast %arg0 : !hal.buffer_view -> tensor<f32>
+  util.global.store %0, @var_out_of_order : tensor<f32>
+  return
+}
+util.global public mutable @var_out_of_order = dense<0.000000e+00> : tensor<f32>
+
+// -----
+// Checks that the implicit cast allowing a buffer_view to indirect store into
+// a variable that maps to a buffer is permitted.
+// CHECK-LABEL: util.global public mutable @var_indirect_with_buffer_view_store
+// CHECK: %[[ptr:.*]] = util.global.address @var_indirect_with_buffer_view_store : !util.ptr<!hal.buffer>
+// CHECK: %[[buffer:.*]] = hal.buffer_view.buffer %arg0 : !hal.buffer
+// CHECK: util.global.store.indirect %[[buffer]], %[[ptr]] : !hal.buffer -> !util.ptr<!hal.buffer>
+util.global public mutable @var_indirect_with_buffer_view_store : tensor<i32>
+func @fn(%arg0: !hal.buffer_view) {
+  %0 = util.global.address @var_indirect_with_buffer_view_store : !util.ptr<tensor<i32>>
+  %1 = hal.tensor.cast %arg0 : !hal.buffer_view -> tensor<i32>
+  util.global.store.indirect %1, %0 : tensor<i32> -> !util.ptr<tensor<i32>>
+  return
+}
diff --git a/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/test/stream_ops.mlir b/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/test/stream_ops.mlir
index 18e8e56..be08dbe 100644
--- a/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/test/stream_ops.mlir
+++ b/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/test/stream_ops.mlir
@@ -557,7 +557,7 @@
 
 // Test that when we copy a subspan of a large constant pool into a buffer,
 // we use the correct size.
-hal.variable @_const_pool_splats : !hal.buffer attributes {sym_visibility = "private"}
+util.global private @_const_pool_splats : !hal.buffer
 
 // CHECK-LABEL: func @cloneFromLargeBufferToSmallBuffer
 func @cloneFromLargeBufferToSmallBuffer(%input: tensor<2xi32>) -> tensor<7xi32> {
@@ -568,7 +568,7 @@
     // CHECK: %[[C0:.+]] = constant 0 : index
     // CHECK: %[[C28:.+]] = constant 28 : index
     // CHECK: %[[DSTBUF:.+]] = hal.allocator.allocate<%{{.+}} : !hal.allocator> type("HostVisible|DeviceVisible|DeviceLocal") usage("Transfer|Mapping|Dispatch") : !hal.buffer{%[[C28]]}
-    // CHECK: %[[CSTBUF:.+]] = hal.variable.load @_const_pool_splats : !hal.buffer
+    // CHECK: %[[CSTBUF:.+]] = util.global.load @_const_pool_splats : !hal.buffer
     // CHECK: hal.command_buffer.copy_buffer<%cmd : !hal.command_buffer> source(%[[CSTBUF]] : !hal.buffer)[%[[C0]]] target(%[[DSTBUF]] : !hal.buffer)[%[[C0]]] length(%[[C28]])
     %2 = flow.tensor.clone %const_span : tensor<7xi32>
     %3 = flow.tensor.update %arg0, %2[%c3] : tensor<2xi32> -> tensor<7xi32>
diff --git a/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/test/variable_ops.mlir b/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/test/variable_ops.mlir
deleted file mode 100644
index c0ec959..0000000
--- a/iree/compiler/Dialect/HAL/Conversion/FlowToHAL/test/variable_ops.mlir
+++ /dev/null
@@ -1,104 +0,0 @@
-// RUN: iree-opt -split-input-file -iree-convert-to-hal -verify-diagnostics %s | IreeFileCheck %s
-
-// CHECK-LABEL: hal.variable @var_i32 mutable : !hal.buffer
-flow.variable @var_i32 mutable : tensor<i32>
-func @fn() {
-  // CHECK: %[[V:.+]] = hal.variable.load @var_i32 : !hal.buffer
-  %0 = flow.variable.load @var_i32 : tensor<i32>
-  // CHECK-NEXT: hal.variable.store %[[V]], @var_i32 : !hal.buffer
-  flow.variable.store %0, @var_i32 : tensor<i32>
-  return
-}
-
-// -----
-
-// CHECK-LABEL: hal.variable @var_i1 mutable : !hal.buffer
-flow.variable @var_i1 mutable : tensor<i1>
-func @fn() {
-  // CHECK: %[[V:.+]] = hal.variable.load @var_i1 : !hal.buffer
-  %0 = flow.variable.load @var_i1 : tensor<i1>
-  // CHECK-NEXT: hal.variable.store %[[V]], @var_i1 : !hal.buffer
-  flow.variable.store %0, @var_i1 : tensor<i1>
-  return
-}
-
-// -----
-
-// CHECK-LABEL: hal.variable @var_indirect mutable : !hal.buffer
-flow.variable @var_indirect mutable : tensor<i32>
-func @fn() {
-  // CHECK: %[[ADDR:.+]] = hal.variable.address @var_indirect
-  %0 = flow.variable.address @var_indirect : !util.ptr<tensor<i32>>
-  // CHECK-NEXT: %[[VALUE:.+]] = hal.variable.load.indirect %[[ADDR]]
-  %1 = flow.variable.load.indirect %0 : !util.ptr<tensor<i32>> -> tensor<i32>
-  // CHECK-NEXT: hal.variable.store.indirect %[[VALUE]], %[[ADDR]]
-  flow.variable.store.indirect %1, %0 : tensor<i32> -> !util.ptr<tensor<i32>>
-  return
-}
-
-// -----
-// Checks that an initializer function is generated, used and operates on
-// a hal.buffer (versus tensor).
-// CHECK: hal.variable @var_with_tensor_initializer
-// CHECK-SAME: init(@__var_with_tensor_initializer_initializer)
-// CHECK-SAME: : !hal.buffer
-// CHECK-LABEL: func @__var_with_tensor_initializer_initializer() -> !hal.buffer
-flow.variable @var_with_tensor_initializer mutable dense<0.000000e+00> : tensor<f32>
-func @fn() {
-  %0 = flow.variable.load @var_with_tensor_initializer : tensor<f32>
-  flow.variable.store %0, @var_with_tensor_initializer : tensor<f32>
-  return
-}
-
-// -----
-// TODO(b/145839814): It should not be possible to produce a name collision
-// expected-error @+3 {{redefinition of symbol named '__var_with_initializer_initializer'}}
-// expected-note @+1 {{see existing symbol definition here}}
-func private @__var_with_initializer_initializer() -> ()
-flow.variable @var_with_initializer mutable dense<0.000000e+00> : tensor<f32>
-func @fn() {
-  %0 = flow.variable.load @var_with_initializer : tensor<f32>
-  flow.variable.store %0, @var_with_initializer : tensor<f32>
-  return
-}
-
-// -----
-// Checks that the implicit cast allowing a buffer_view to store into a variable
-// that maps to a buffer is permitted.
-// CHECK-LABEL: hal.variable @var_with_buffer_view_store
-// CHECK: %[[buffer:.*]] = hal.buffer_view.buffer %arg0 : !hal.buffer
-// CHECK: hal.variable.store %[[buffer]], @var_with_buffer_view_store : !hal.buffer
-flow.variable @var_with_buffer_view_store mutable dense<0.000000e+00> : tensor<f32>
-func @fn(%arg0: !hal.buffer_view) {
-  %0 = hal.tensor.cast %arg0 : !hal.buffer_view -> tensor<f32>
-  flow.variable.store %0, @var_with_buffer_view_store : tensor<f32>
-  return
-}
-
-// -----
-// Checks that stores are permitted for variables that do not dominate the
-// function containing a store.
-// CHECK-LABEL: func @store_var_out_of_order
-// CHECK: %[[buffer:.*]] = hal.buffer_view.buffer %arg0 : !hal.buffer
-// CHECK: hal.variable.store %[[buffer]], @var_out_of_order : !hal.buffer
-func @store_var_out_of_order(%arg0: !hal.buffer_view) {
-  %0 = hal.tensor.cast %arg0 : !hal.buffer_view -> tensor<f32>
-  flow.variable.store %0, @var_out_of_order : tensor<f32>
-  return
-}
-flow.variable @var_out_of_order mutable dense<0.000000e+00> : tensor<f32>
-
-// -----
-// Checks that the implicit cast allowing a buffer_view to indirect store into
-// a variable that maps to a buffer is permitted.
-// CHECK-LABEL: hal.variable @var_indirect_with_buffer_view_store
-// CHECK: %[[ptr:.*]] = hal.variable.address @var_indirect_with_buffer_view_store : !util.ptr<!hal.buffer>
-// CHECK: %[[buffer:.*]] = hal.buffer_view.buffer %arg0 : !hal.buffer
-// CHECK: hal.variable.store.indirect %[[buffer]], %[[ptr]] : !hal.buffer -> !util.ptr<!hal.buffer>
-flow.variable @var_indirect_with_buffer_view_store mutable : tensor<i32>
-func @fn(%arg0: !hal.buffer_view) {
-  %0 = flow.variable.address @var_indirect_with_buffer_view_store : !util.ptr<tensor<i32>>
-  %1 = hal.tensor.cast %arg0 : !hal.buffer_view -> tensor<i32>
-  flow.variable.store.indirect %1, %0 : tensor<i32> -> !util.ptr<tensor<i32>>
-  return
-}
diff --git a/iree/compiler/Dialect/HAL/Conversion/HALToHAL/ConvertConstantOps.cpp b/iree/compiler/Dialect/HAL/Conversion/HALToHAL/ConvertConstantOps.cpp
index b5125b3..c6e6e3e 100644
--- a/iree/compiler/Dialect/HAL/Conversion/HALToHAL/ConvertConstantOps.cpp
+++ b/iree/compiler/Dialect/HAL/Conversion/HALToHAL/ConvertConstantOps.cpp
@@ -6,6 +6,7 @@
 
 #include "iree/compiler/Dialect/HAL/IR/HALOps.h"
 #include "iree/compiler/Dialect/HAL/IR/HALTypes.h"
+#include "iree/compiler/Dialect/Util/IR/UtilOps.h"
 #include "iree/compiler/Dialect/Util/IR/UtilTypes.h"
 #include "mlir/Dialect/StandardOps/IR/Ops.h"
 #include "mlir/Transforms/DialectConversion.h"
@@ -22,7 +23,7 @@
   LogicalResult matchAndRewrite(
       IREE::HAL::ConstantSubspanOp op, llvm::ArrayRef<Value> operands,
       ConversionPatternRewriter &rewriter) const override {
-    auto bufferValue = rewriter.createOrFold<IREE::HAL::VariableLoadOp>(
+    auto bufferValue = rewriter.createOrFold<IREE::Util::GlobalLoadOp>(
         op.getLoc(), IREE::HAL::BufferType::get(rewriter.getContext()),
         op.runtime_buffer().getLeafReference());
     auto offsetValue = rewriter.createOrFold<mlir::ConstantOp>(
diff --git a/iree/compiler/Dialect/HAL/Conversion/HALToHAL/test/constant_ops.mlir b/iree/compiler/Dialect/HAL/Conversion/HALToHAL/test/constant_ops.mlir
index 944485a..ace82db 100644
--- a/iree/compiler/Dialect/HAL/Conversion/HALToHAL/test/constant_ops.mlir
+++ b/iree/compiler/Dialect/HAL/Conversion/HALToHAL/test/constant_ops.mlir
@@ -2,11 +2,11 @@
 
 // CHECK-LABEL: func @constant_subspan
 func @constant_subspan() {
-  //  CHECK-DAG: %[[BUFFER:.+]] = hal.variable.load @pool_buffer : !hal.buffer
+  //  CHECK-DAG: %[[BUFFER:.+]] = util.global.load @pool_buffer : !hal.buffer
   //  CHECK-DAG: %[[OFFSET:.+]] = constant 123 : index
   //  CHECK-DAG: %[[LENGTH:.+]] = constant 16 : index
   // CHECK-NEXT: = hal.buffer.subspan<%[[BUFFER]] : !hal.buffer>[%[[OFFSET]], %[[LENGTH]]] : !hal.buffer
   %cst0 = hal.constant.subspan @pool_buffer[#hal.byte_range<123, 16>] : tensor<4xf32>
   return
 }
-hal.variable @pool_buffer : !hal.buffer
+util.global @pool_buffer : !hal.buffer
diff --git a/iree/compiler/Dialect/HAL/Conversion/HALToVM/BUILD b/iree/compiler/Dialect/HAL/Conversion/HALToVM/BUILD
index 59142ca..1feec91 100644
--- a/iree/compiler/Dialect/HAL/Conversion/HALToVM/BUILD
+++ b/iree/compiler/Dialect/HAL/Conversion/HALToVM/BUILD
@@ -24,7 +24,6 @@
         "ConvertExperimentalOps.cpp",
         "ConvertHALToVM.cpp",
         "ConvertSemaphoreOps.cpp",
-        "ConvertVariableOps.cpp",
     ],
     hdrs = [
         "ConvertHALToVM.h",
@@ -35,8 +34,8 @@
         "//iree/compiler/Dialect/HAL/Utils",
         "//iree/compiler/Dialect/Util/IR",
         "//iree/compiler/Dialect/VM/Conversion",
-        "//iree/compiler/Dialect/VM/Conversion/IREEToVM",
         "//iree/compiler/Dialect/VM/Conversion/StandardToVM",
+        "//iree/compiler/Dialect/VM/Conversion/UtilToVM",
         "//iree/compiler/Dialect/VM/IR",
         "@llvm-project//llvm:Support",
         "@llvm-project//mlir:IR",
diff --git a/iree/compiler/Dialect/HAL/Conversion/HALToVM/CMakeLists.txt b/iree/compiler/Dialect/HAL/Conversion/HALToVM/CMakeLists.txt
index 0ca0990..b25c310 100644
--- a/iree/compiler/Dialect/HAL/Conversion/HALToVM/CMakeLists.txt
+++ b/iree/compiler/Dialect/HAL/Conversion/HALToVM/CMakeLists.txt
@@ -27,7 +27,6 @@
     "ConvertExperimentalOps.cpp"
     "ConvertHALToVM.cpp"
     "ConvertSemaphoreOps.cpp"
-    "ConvertVariableOps.cpp"
   DEPS
     LLVMSupport
     MLIRIR
@@ -39,8 +38,8 @@
     iree::compiler::Dialect::HAL::hal_imports
     iree::compiler::Dialect::Util::IR
     iree::compiler::Dialect::VM::Conversion
-    iree::compiler::Dialect::VM::Conversion::IREEToVM
     iree::compiler::Dialect::VM::Conversion::StandardToVM
+    iree::compiler::Dialect::VM::Conversion::UtilToVM
     iree::compiler::Dialect::VM::IR
   PUBLIC
 )
diff --git a/iree/compiler/Dialect/HAL/Conversion/HALToVM/ConvertHALToVM.cpp b/iree/compiler/Dialect/HAL/Conversion/HALToVM/ConvertHALToVM.cpp
index b128fcc..bc39e14 100644
--- a/iree/compiler/Dialect/HAL/Conversion/HALToVM/ConvertHALToVM.cpp
+++ b/iree/compiler/Dialect/HAL/Conversion/HALToVM/ConvertHALToVM.cpp
@@ -12,10 +12,10 @@
 #include "iree/compiler/Dialect/Util/IR/UtilDialect.h"
 #include "iree/compiler/Dialect/Util/IR/UtilTypes.h"
 #include "iree/compiler/Dialect/VM/Conversion/ConversionTarget.h"
-#include "iree/compiler/Dialect/VM/Conversion/IREEToVM/ConvertIREEToVM.h"
 #include "iree/compiler/Dialect/VM/Conversion/ImportUtils.h"
 #include "iree/compiler/Dialect/VM/Conversion/StandardToVM/ConvertStandardToVM.h"
 #include "iree/compiler/Dialect/VM/Conversion/TypeConverter.h"
+#include "iree/compiler/Dialect/VM/Conversion/UtilToVM/ConvertUtilToVM.h"
 #include "iree/compiler/Dialect/VM/IR/VMOps.h"
 #include "mlir/Dialect/StandardOps/IR/Ops.h"
 #include "mlir/IR/Attributes.h"
@@ -61,10 +61,6 @@
 extern void populateHALSemaphoreToVMPatterns(
     MLIRContext *context, SymbolTable &importSymbols,
     TypeConverter &typeConverter, OwningRewritePatternList &patterns);
-extern void populateHALVariableToVMPatterns(MLIRContext *context,
-                                            SymbolTable &importSymbols,
-                                            TypeConverter &typeConverter,
-                                            OwningRewritePatternList &patterns);
 
 void populateHALToVMPatterns(MLIRContext *context, SymbolTable &importSymbols,
                              OwningRewritePatternList &patterns,
@@ -89,8 +85,6 @@
                                       patterns);
   populateHALSemaphoreToVMPatterns(context, importSymbols, typeConverter,
                                    patterns);
-  populateHALVariableToVMPatterns(context, importSymbols, typeConverter,
-                                  patterns);
 }
 
 namespace {
@@ -129,7 +123,8 @@
 
     OwningRewritePatternList conversionPatterns(&getContext());
     populateStandardToVMPatterns(context, typeConverter, conversionPatterns);
-    populateIREEToVMPatterns(context, typeConverter, conversionPatterns);
+    populateUtilToVMPatterns(context, conversionTarget, typeConverter,
+                             conversionPatterns);
 
     SymbolTable importSymbols(innerModuleOp);
     populateHALToVMPatterns(context, importSymbols, conversionPatterns,
diff --git a/iree/compiler/Dialect/HAL/Conversion/HALToVM/test/BUILD b/iree/compiler/Dialect/HAL/Conversion/HALToVM/test/BUILD
index c3e78a1..a086112 100644
--- a/iree/compiler/Dialect/HAL/Conversion/HALToVM/test/BUILD
+++ b/iree/compiler/Dialect/HAL/Conversion/HALToVM/test/BUILD
@@ -25,7 +25,6 @@
             "control_flow_ops.mlir",
             "device_ops.mlir",
             "executable_ops.mlir",
-            "variable_ops.mlir",
         ],
         include = ["*.mlir"],
     ),
diff --git a/iree/compiler/Dialect/HAL/Conversion/HALToVM/test/CMakeLists.txt b/iree/compiler/Dialect/HAL/Conversion/HALToVM/test/CMakeLists.txt
index fa16efe..a94b043 100644
--- a/iree/compiler/Dialect/HAL/Conversion/HALToVM/test/CMakeLists.txt
+++ b/iree/compiler/Dialect/HAL/Conversion/HALToVM/test/CMakeLists.txt
@@ -22,7 +22,6 @@
     "control_flow_ops.mlir"
     "device_ops.mlir"
     "executable_ops.mlir"
-    "variable_ops.mlir"
   DATA
     iree::tools::IreeFileCheck
     iree::tools::iree-opt
diff --git a/iree/compiler/Dialect/HAL/Conversion/HALToVM/test/constant_ops.mlir b/iree/compiler/Dialect/HAL/Conversion/HALToVM/test/constant_ops.mlir
index 2639235..dbd1893 100644
--- a/iree/compiler/Dialect/HAL/Conversion/HALToVM/test/constant_ops.mlir
+++ b/iree/compiler/Dialect/HAL/Conversion/HALToVM/test/constant_ops.mlir
@@ -12,7 +12,7 @@
 }
 
 // CHECK: vm.global.ref private @pool_storage0_buffer initializer(@pool_storage0_buffer_initializer) : !vm.ref<!hal.buffer>
-hal.variable @pool_storage0_buffer init(@pool_storage0_buffer_initializer) : !hal.buffer attributes {sym_visibility = "private"}
+util.global private @pool_storage0_buffer initializer(@pool_storage0_buffer_initializer) : !hal.buffer
 // CHECK: vm.func private @pool_storage0_buffer_initializer() -> !vm.ref<!hal.buffer>
 func private @pool_storage0_buffer_initializer() -> !hal.buffer {
   %c0 = constant 0 : index
@@ -30,11 +30,11 @@
 }
 
 // CHECK: vm.global.ref private @pool_storage1_buffer initializer(@pool_storage1_buffer_initializer) : !vm.ref<!hal.buffer>
-hal.variable @pool_storage1_buffer init(@pool_storage1_buffer_initializer) : !hal.buffer attributes {sym_visibility = "private"}
+util.global private @pool_storage1_buffer initializer(@pool_storage1_buffer_initializer) : !hal.buffer
 func private @pool_storage1_buffer_initializer() -> !hal.buffer
 
 // CHECK: vm.global.ref private @pool_splats initializer(@pool_splats_initializer) : !vm.ref<!hal.buffer>
-hal.variable @pool_splats init(@pool_splats_initializer) : !hal.buffer attributes {sym_visibility = "private"}
+util.global private @pool_splats initializer(@pool_splats_initializer) : !hal.buffer
 // CHECK: vm.func private @pool_splats_initializer() -> !vm.ref<!hal.buffer>
 func private @pool_splats_initializer() -> !hal.buffer {
   %c64 = constant 64 : index
diff --git a/iree/compiler/Dialect/HAL/Conversion/HALToVM/test/variable_ops.mlir b/iree/compiler/Dialect/HAL/Conversion/HALToVM/test/variable_ops.mlir
deleted file mode 100644
index b757804..0000000
--- a/iree/compiler/Dialect/HAL/Conversion/HALToVM/test/variable_ops.mlir
+++ /dev/null
@@ -1,59 +0,0 @@
-// RUN: iree-opt -split-input-file -iree-convert-hal-to-vm %s | IreeFileCheck %s
-
-// CHECK: vm.global.i32 public @v_initialized_const = 4 : i32
-hal.variable @v_initialized_const = 4 : i32
-
-// CHECK: vm.global.i32 private @v_private_const = 5 : i32
-hal.variable @v_private_const attributes {sym_visibility = "private"} = 5 : i32
-
-// -----
-
-// CHECK: vm.global.ref public @v_initialized initializer(@initializer) : !vm.ref<!hal.buffer>
-hal.variable @v_initialized init(@initializer) : !hal.buffer
-func private @initializer() -> !hal.buffer
-
-// -----
-
-// CHECK: vm.global.ref public @v_loaded : !vm.ref<!hal.buffer>
-hal.variable @v_loaded : !hal.buffer
-// CHECK-LABEL: vm.func private @loaded
-func @loaded() {
-  // CHECK: %v_loaded = vm.global.load.ref @v_loaded : !vm.ref<!hal.buffer>
-  %0 = hal.variable.load @v_loaded : !hal.buffer
-  return
-}
-
-// -----
-
-// CHECK: vm.global.ref public mutable @v_stored : !vm.ref<!hal.buffer>
-hal.variable @v_stored mutable : !hal.buffer
-// CHECK-LABEL: vm.func private @stored
-func @stored(%arg0 : !hal.buffer) {
-  // CHECK: vm.global.store.ref %arg0, @v_stored : !vm.ref<!hal.buffer>
-  hal.variable.store %arg0, @v_stored : !hal.buffer
-  return
-}
-
-// -----
-
-hal.variable @v_loaded : !hal.buffer
-// CHECK-LABEL: @loaded_indirect
-func @loaded_indirect() -> !hal.buffer {
-  // CHECK-NEXT: %[[ADDR:.+]] = vm.global.address @v_loaded
-  %0 = hal.variable.address @v_loaded : !util.ptr<!hal.buffer>
-  // CHECK-NEXT: = vm.global.load.indirect.ref %[[ADDR]]
-  %1 = hal.variable.load.indirect %0 : !util.ptr<!hal.buffer> -> !hal.buffer
-  return %1 : !hal.buffer
-}
-
-// -----
-
-hal.variable @v_stored mutable : !hal.buffer
-// CHECK-LABEL: @stored_indirect
-func @stored_indirect(%arg0 : !hal.buffer) {
-  // CHECK-NEXT: %[[ADDR:.+]] = vm.global.address @v_stored
-  %0 = hal.variable.address @v_stored : !util.ptr<!hal.buffer>
-  // CHECK-NEXT: vm.global.store.indirect.ref %arg0, %[[ADDR]]
-  hal.variable.store.indirect %arg0, %0 : !hal.buffer -> !util.ptr<!hal.buffer>
-  return
-}
diff --git a/iree/compiler/Dialect/HAL/IR/HALBase.td b/iree/compiler/Dialect/HAL/IR/HALBase.td
index d61387d..9610e29 100644
--- a/iree/compiler/Dialect/HAL/IR/HALBase.td
+++ b/iree/compiler/Dialect/HAL/IR/HALBase.td
@@ -366,9 +366,9 @@
 
 def HAL_PrimitiveType : AnyTypeOf<[Index, AnySignlessInteger, AnyFloat]>;
 
-def HAL_VariableRefAttr : AliasedSymbolRefAttr;
-def HAL_VariableType : AnyTypeOf<[HAL_PrimitiveType, AnyVector, HAL_ObjectType]>;
-def HAL_VariablePtr : PtrOf<HAL_VariableType>;
+def HAL_GlobalRefAttr : AliasedSymbolRefAttr;
+def HAL_GlobalType : AnyTypeOf<[HAL_PrimitiveType, AnyVector, HAL_ObjectType]>;
+def HAL_GlobalPtr : Util_PtrOf<HAL_GlobalType>;
 
 def HAL_IndexAttr : Util_IndexAttrBase<"index">;
 def HAL_IndexArrayAttr : TypedArrayAttrBase<HAL_IndexAttr,
diff --git a/iree/compiler/Dialect/HAL/IR/HALOpFolders.cpp b/iree/compiler/Dialect/HAL/IR/HALOpFolders.cpp
index c89aa40..71cce15 100644
--- a/iree/compiler/Dialect/HAL/IR/HALOpFolders.cpp
+++ b/iree/compiler/Dialect/HAL/IR/HALOpFolders.cpp
@@ -35,130 +35,6 @@
 }
 
 //===----------------------------------------------------------------------===//
-// hal.variable.*
-//===----------------------------------------------------------------------===//
-
-namespace {
-
-/// Converts variable initializer functions that evaluate to a constant to a
-/// specified initial value.
-struct InlineConstVariableOpInitializer : public OpRewritePattern<VariableOp> {
-  using OpRewritePattern<VariableOp>::OpRewritePattern;
-
-  LogicalResult matchAndRewrite(VariableOp op,
-                                PatternRewriter &rewriter) const override {
-    if (!op.initializer()) return failure();
-    auto *symbolOp =
-        SymbolTable::lookupNearestSymbolFrom(op, op.initializer().getValue());
-    auto initializer = cast<FuncOp>(symbolOp);
-    if (initializer.getBlocks().size() == 1 &&
-        initializer.getBlocks().front().getOperations().size() == 2 &&
-        isa<mlir::ReturnOp>(
-            initializer.getBlocks().front().getOperations().back())) {
-      auto &primaryOp = initializer.getBlocks().front().getOperations().front();
-      Attribute constResult;
-      if (matchPattern(primaryOp.getResult(0), m_Constant(&constResult))) {
-        auto newOp = rewriter.create<VariableOp>(op.getLoc(), op.sym_name(),
-                                                 op.is_mutable(), op.type(),
-                                                 constResult);
-        newOp.setVisibility(op.getVisibility());
-        rewriter.replaceOp(op, {});
-        return success();
-      }
-    }
-    return failure();
-  }
-};
-
-}  // namespace
-
-void VariableOp::getCanonicalizationPatterns(OwningRewritePatternList &results,
-                                             MLIRContext *context) {
-  results.insert<InlineConstVariableOpInitializer>(context);
-}
-
-namespace {
-
-class PropagateVariableLoadAddress
-    : public OpRewritePattern<VariableLoadIndirectOp> {
-  using OpRewritePattern::OpRewritePattern;
-
- public:
-  LogicalResult matchAndRewrite(VariableLoadIndirectOp op,
-                                PatternRewriter &rewriter) const override {
-    if (auto addressOp = dyn_cast_or_null<VariableAddressOp>(
-            op.variable().getDefiningOp())) {
-      rewriter.replaceOpWithNewOp<VariableLoadOp>(op, op.result().getType(),
-                                                  addressOp.variable());
-      return success();
-    }
-    return failure();
-  }
-};
-
-}  // namespace
-
-void VariableLoadIndirectOp::getCanonicalizationPatterns(
-    OwningRewritePatternList &results, MLIRContext *context) {
-  results.insert<PropagateVariableLoadAddress>(context);
-}
-
-namespace {
-
-/// Erases hal.variable.store ops that are no-ops.
-/// This can happen if there was a variable load, some DCE'd usage, and a
-/// store back to the same variable: we want to be able to elide the entire load
-/// and store.
-struct EraseUnusedVariableStoreOp : public OpRewritePattern<VariableStoreOp> {
-  using OpRewritePattern<VariableStoreOp>::OpRewritePattern;
-
-  LogicalResult matchAndRewrite(VariableStoreOp op,
-                                PatternRewriter &rewriter) const override {
-    if (auto loadOp =
-            dyn_cast_or_null<VariableLoadOp>(op.value().getDefiningOp())) {
-      if (loadOp.variable() == op.variable()) {
-        rewriter.eraseOp(op);
-        return success();
-      }
-    }
-    return failure();
-  }
-};
-
-}  // namespace
-
-void VariableStoreOp::getCanonicalizationPatterns(
-    OwningRewritePatternList &results, MLIRContext *context) {
-  results.insert<EraseUnusedVariableStoreOp>(context);
-}
-
-namespace {
-
-class PropagateVariableStoreAddress
-    : public OpRewritePattern<VariableStoreIndirectOp> {
-  using OpRewritePattern::OpRewritePattern;
-
- public:
-  LogicalResult matchAndRewrite(VariableStoreIndirectOp op,
-                                PatternRewriter &rewriter) const override {
-    if (auto addressOp = dyn_cast_or_null<VariableAddressOp>(
-            op.variable().getDefiningOp())) {
-      rewriter.replaceOpWithNewOp<VariableStoreOp>(op, op.value(),
-                                                   addressOp.variable());
-      return success();
-    }
-    return failure();
-  }
-};
-
-}  // namespace
-
-void VariableStoreIndirectOp::getCanonicalizationPatterns(
-    OwningRewritePatternList &results, MLIRContext *context) {
-  results.insert<PropagateVariableStoreAddress>(context);
-}
-
-//===----------------------------------------------------------------------===//
 // hal.allocator.*
 //===----------------------------------------------------------------------===//
 
@@ -851,7 +727,7 @@
 
 namespace {
 
-// Resolves hal.constant.buffer ops to their runtime hal.variable buffer.
+// Resolves hal.constant.buffer ops to their runtime util.global buffer.
 struct ResolveConstantPoolLoadToRuntimeBuffer
     : public OpRewritePattern<ConstantPoolLoadOp> {
   using OpRewritePattern<ConstantPoolLoadOp>::OpRewritePattern;
diff --git a/iree/compiler/Dialect/HAL/IR/HALOps.cpp b/iree/compiler/Dialect/HAL/IR/HALOps.cpp
index 3dec9ce..be4314a 100644
--- a/iree/compiler/Dialect/HAL/IR/HALOps.cpp
+++ b/iree/compiler/Dialect/HAL/IR/HALOps.cpp
@@ -308,261 +308,6 @@
 }
 
 //===----------------------------------------------------------------------===//
-// hal.variable
-//===----------------------------------------------------------------------===//
-
-// Returns true if the given |accessType| is compatible with the |variableType|.
-// For example, this will return true if the variable type is a tensor<?xf32>
-// and the access is tensor<4xf32>.
-static bool isVariableTypeCompatible(Type variableType, Type accessType) {
-  // If one is a shaped type, then they both must be and have compatible
-  // shapes.
-  if (variableType.isa<ShapedType>() || accessType.isa<ShapedType>()) {
-    return succeeded(mlir::verifyCompatibleShape(variableType, accessType));
-  }
-
-  // Otherwise, the types must be the same.
-  return variableType == accessType;
-}
-
-static ParseResult parseVariableOp(OpAsmParser &parser,
-                                   OperationState *result) {
-  StringAttr nameAttr;
-  if (failed(parser.parseSymbolName(nameAttr,
-                                    mlir::SymbolTable::getSymbolAttrName(),
-                                    result->attributes))) {
-    return failure();
-  }
-
-  if (succeeded(parser.parseOptionalKeyword("mutable"))) {
-    result->addAttribute("is_mutable", UnitAttr::get(result->getContext()));
-  }
-
-  if (succeeded(parser.parseOptionalKeyword("init"))) {
-    FlatSymbolRefAttr initializerAttr;
-    if (failed(parser.parseLParen()) ||
-        failed(parser.parseAttribute(initializerAttr, "initializer",
-                                     result->attributes)) ||
-        failed(parser.parseRParen())) {
-      return failure();
-    }
-  }
-
-  if (failed(parser.parseOptionalAttrDictWithKeyword(result->attributes))) {
-    return failure();
-  }
-
-  Type type;
-  if (succeeded(parser.parseOptionalEqual())) {
-    // @foo = 4 : i32
-    Attribute initialValueAttr;
-    if (failed(parser.parseAttribute(initialValueAttr, "initial_value",
-                                     result->attributes))) {
-      return failure();
-    }
-    type = initialValueAttr.getType();
-  } else {
-    // @foo : index = 4 : i32
-    if (failed(parser.parseColonType(type)) ||
-        failed(parser.parseOptionalAttrDictWithKeyword(result->attributes))) {
-      return failure();
-    }
-    if (succeeded(parser.parseOptionalEqual())) {
-      Attribute initialValueAttr;
-      if (failed(parser.parseAttribute(initialValueAttr, "initial_value",
-                                       result->attributes))) {
-        return failure();
-      }
-    }
-  }
-  result->addAttribute("type", TypeAttr::get(type));
-
-  return success();
-}
-
-static void printVariableOp(OpAsmPrinter &p, VariableOp op) {
-  p << op.getOperationName() << ' ';
-  p.printSymbolName(op.sym_name());
-  if (op.is_mutable()) {
-    p << " mutable";
-  }
-  if (op.initializer().hasValue()) {
-    p << " init(";
-    p.printSymbolName(op.initializer().getValue());
-    p << ')';
-  }
-  if (op.initial_value().hasValue() &&
-      op.type() == op.initial_value().getValue().getType()) {
-    // @foo = 4 : i32
-  } else {
-    // @foo : index = 4 : i32
-    p << " : ";
-    p.printType(op.type());
-  }
-  p.printOptionalAttrDictWithKeyword(op->getAttrs(), /*elidedAttrs=*/{
-                                         "sym_name",
-                                         "type",
-                                         "is_mutable",
-                                         "initializer",
-                                         "initial_value",
-                                     });
-  if (op.initial_value().hasValue()) {
-    p << " = ";
-    p.printAttribute(op.initial_value().getValue());
-  }
-}
-
-static LogicalResult verifyVariableOp(VariableOp op) {
-  if (op.initializer().hasValue() && op.initial_value().hasValue()) {
-    return op.emitOpError()
-           << "variables can have either an initializer or an initial value";
-  } else if (op.initializer().hasValue()) {
-    // Ensure initializer returns the same type as the variable.
-    auto *symbolOp =
-        SymbolTable::lookupNearestSymbolFrom(op, op.initializer().getValue());
-    if (!symbolOp) {
-      return op.emitOpError() << "initializer function "
-                              << op.initializer().getValue() << " not found";
-    }
-    auto initializerOp = dyn_cast<FuncOp>(symbolOp);
-    if (initializerOp.getNumArguments() != 0 ||
-        initializerOp.getNumResults() != 1 ||
-        initializerOp.getType().getResult(0) != op.type()) {
-      return op.emitOpError()
-             << "initializer type mismatch; variable " << op.sym_name()
-             << " is " << op.type() << " but initializer function "
-             << initializerOp.getName() << " is " << initializerOp.getType();
-    }
-  }
-  return success();
-}
-
-void VariableOp::build(OpBuilder &builder, OperationState &result,
-                       StringRef name, bool isMutable, Type type,
-                       Optional<StringRef> initializer,
-                       Optional<Attribute> initialValue,
-                       ArrayRef<NamedAttribute> attrs) {
-  result.addAttribute(SymbolTable::getSymbolAttrName(),
-                      builder.getStringAttr(name));
-  if (isMutable) {
-    result.addAttribute("is_mutable", builder.getUnitAttr());
-  }
-  if (initializer.hasValue()) {
-    result.addAttribute("initializer",
-                        builder.getSymbolRefAttr(initializer.getValue()));
-  } else if (initialValue.hasValue()) {
-    result.addAttribute("initial_value", initialValue.getValue());
-  }
-  result.addAttribute("type", TypeAttr::get(type));
-  result.attributes.append(attrs.begin(), attrs.end());
-}
-
-void VariableOp::build(OpBuilder &builder, OperationState &result,
-                       StringRef name, bool isMutable, mlir::FuncOp initializer,
-                       ArrayRef<NamedAttribute> attrs) {
-  build(builder, result, name, isMutable, initializer.getType().getResult(0),
-        initializer.getName(), llvm::None, attrs);
-}
-
-void VariableOp::build(OpBuilder &builder, OperationState &result,
-                       StringRef name, bool isMutable, Type type,
-                       Attribute initialValue, ArrayRef<NamedAttribute> attrs) {
-  build(builder, result, name, isMutable, type, llvm::None, initialValue,
-        attrs);
-}
-
-void VariableOp::build(OpBuilder &builder, OperationState &result,
-                       StringRef name, bool isMutable, Type type,
-                       ArrayRef<NamedAttribute> attrs) {
-  build(builder, result, name, isMutable, type, llvm::None, llvm::None, attrs);
-}
-
-//===----------------------------------------------------------------------===//
-// hal.variable.load
-//===----------------------------------------------------------------------===//
-
-void VariableLoadOp::getEffects(
-    SmallVectorImpl<MemoryEffects::EffectInstance> &effects) {
-  // HACK: works around the lack of symbol side effects in mlir by only saying
-  // we have a side-effect if the variable we are loading is mutable.
-  auto *symbolOp = SymbolTable::lookupNearestSymbolFrom(*this, variable());
-  assert(symbolOp);
-  auto variableOp = dyn_cast<VariableOp>(symbolOp);
-  if (variableOp.is_mutable()) {
-    effects.emplace_back(MemoryEffects::Read::get());
-  }
-}
-
-static LogicalResult verifyVariableLoadOp(VariableLoadOp &op) {
-  auto *symbolOp = SymbolTable::lookupNearestSymbolFrom(op, op.variable());
-  if (!symbolOp) {
-    return op.emitOpError() << "undefined variable: " << op.variable();
-  }
-  auto variableOp = dyn_cast<VariableOp>(symbolOp);
-  auto loadType = op.result().getType();
-  if (!isVariableTypeCompatible(variableOp.type(), loadType)) {
-    return op.emitOpError()
-           << "variable type mismatch; variable " << op.variable() << " is "
-           << variableOp.type() << " but load is " << loadType;
-  }
-  return success();
-}
-
-//===----------------------------------------------------------------------===//
-// hal.variable.load.indirect
-//===----------------------------------------------------------------------===//
-
-static LogicalResult verifyVariableLoadIndirectOp(VariableLoadIndirectOp &op) {
-  auto variableType =
-      op.variable().getType().cast<IREE::Util::PtrType>().getTargetType();
-  auto loadType = op.result().getType();
-  if (!isVariableTypeCompatible(variableType, loadType)) {
-    return op.emitOpError() << "variable type mismatch; variable pointer is "
-                            << variableType << " but load is " << loadType;
-  }
-  return success();
-}
-
-//===----------------------------------------------------------------------===//
-// hal.variable.store
-//===----------------------------------------------------------------------===//
-
-static LogicalResult verifyVariableStoreOp(VariableStoreOp &op) {
-  auto *symbolOp = SymbolTable::lookupNearestSymbolFrom(op, op.variable());
-  if (!symbolOp) {
-    return op.emitOpError() << "undefined variable: " << op.variable();
-  }
-  auto variableOp = dyn_cast<VariableOp>(symbolOp);
-  auto storeType = op.value().getType();
-  if (!isVariableTypeCompatible(variableOp.type(), storeType)) {
-    return op.emitOpError()
-           << "variable type mismatch; variable " << op.variable() << " is "
-           << variableOp.type() << " but store is " << storeType;
-  }
-  if (!variableOp.is_mutable()) {
-    return op.emitOpError() << "variable " << op.variable()
-                            << " is not mutable and cannot be stored to";
-  }
-  return success();
-}
-
-//===----------------------------------------------------------------------===//
-// hal.variable.store.indirect
-//===----------------------------------------------------------------------===//
-
-static LogicalResult verifyVariableStoreIndirectOp(
-    VariableStoreIndirectOp &op) {
-  auto variableType =
-      op.variable().getType().cast<IREE::Util::PtrType>().getTargetType();
-  auto storeType = op.value().getType();
-  if (!isVariableTypeCompatible(variableType, storeType)) {
-    return op.emitOpError() << "variable type mismatch; variable pointer is "
-                            << variableType << " but store is " << storeType;
-  }
-  return success();
-}
-
-//===----------------------------------------------------------------------===//
 // hal.allocator.compute_size
 //===----------------------------------------------------------------------===//
 
diff --git a/iree/compiler/Dialect/HAL/IR/HALOps.h b/iree/compiler/Dialect/HAL/IR/HALOps.h
index d25ea13..8ec603a 100644
--- a/iree/compiler/Dialect/HAL/IR/HALOps.h
+++ b/iree/compiler/Dialect/HAL/IR/HALOps.h
@@ -13,6 +13,7 @@
 #include "iree/compiler/Dialect/HAL/IR/HALTypes.h"
 #include "iree/compiler/Dialect/Shape/IR/ShapeDialect.h"
 #include "iree/compiler/Dialect/Shape/IR/ShapeTypes.h"
+#include "iree/compiler/Dialect/Util/IR/UtilOps.h"
 #include "iree/compiler/Dialect/Util/IR/UtilTraits.h"
 #include "mlir/IR/Attributes.h"
 #include "mlir/IR/BuiltinOps.h"
diff --git a/iree/compiler/Dialect/HAL/IR/HALOps.td b/iree/compiler/Dialect/HAL/IR/HALOps.td
index 199355c..8f6dbaa 100644
--- a/iree/compiler/Dialect/HAL/IR/HALOps.td
+++ b/iree/compiler/Dialect/HAL/IR/HALOps.td
@@ -108,170 +108,6 @@
 }
 
 //===----------------------------------------------------------------------===//
-// Global variables
-//===----------------------------------------------------------------------===//
-
-def HAL_VariableOp : HAL_Op<"variable", [
-    Symbol,
-  ]> {
-  let summary = [{stateful variable declaration}];
-  let description = [{
-    Declares a global variable that maintains its value across invocations.
-    The value is tied to the execution context of the module and different
-    contexts will have different variable storage.
-  }];
-
-  let arguments = (ins
-    StrAttr:$sym_name,
-    TypeAttr:$type,
-    UnitAttr:$is_mutable,
-    // TODO(benvanik): verify matches $type.
-    OptionalAttr<FlatSymbolRefAttr>:$initializer,
-    // TODO(benvanik): verify matches $type.
-    OptionalAttr<AnyAttr>:$initial_value
-  );
-
-  let skipDefaultBuilders = 1;
-  let builders = [
-    OpBuilder<(ins
-      "StringRef":$name,
-      "bool":$isMutable,
-      "Type":$type,
-      "Optional<StringRef>":$initializer,
-      "Optional<Attribute>":$initialValue,
-      CArg<"ArrayRef<NamedAttribute>", "{}">:$attrs
-    )>,
-    OpBuilder<(ins
-      "StringRef":$name,
-      "bool":$isMutable,
-      "mlir::FuncOp":$initializer,
-      CArg<"ArrayRef<NamedAttribute>", "{}">:$attrs
-    )>,
-    OpBuilder<(ins
-      "StringRef":$name,
-      "bool":$isMutable,
-      "Type":$type,
-      "Attribute":$initialValue,
-      CArg<"ArrayRef<NamedAttribute>", "{}">:$attrs
-    )>,
-    OpBuilder<(ins
-      "StringRef":$name,
-      "bool":$isMutable,
-      "Type":$type,
-      CArg<"ArrayRef<NamedAttribute>", "{}">:$attrs
-    )>,
-  ];
-
-  let verifier = [{ return verifyVariableOp(*this); }];
-
-  let hasCanonicalizer = 1;
-}
-
-def HAL_VariableAddressOp : HAL_PureOp<"variable.address"> {
-  let summary = [{returns an address reference to a variable}];
-  let description = [{
-    Returns the address of a variable as a typed reference. Can be used with the
-    variable load and store indirect ops.
-  }];
-
-  let arguments = (ins
-    HAL_VariableRefAttr:$variable
-  );
-  let results = (outs
-    HAL_VariablePtr:$result
-  );
-
-  let assemblyFormat = [{
-    $variable attr-dict `:` type($result)
-  }];
-}
-
-def HAL_VariableLoadOp : HAL_Op<"variable.load", [
-    // HACK: works around the lack of symbol side effects in C++.
-    DeclareOpInterfaceMethods<MemoryEffectsOpInterface>,
-  ]> {
-  let summary = [{loads a value from a global variable}];
-  let description = [{
-    Returns a copy of the variable value.
-  }];
-
-  let arguments = (ins
-    HAL_VariableRefAttr:$variable
-  );
-  let results = (outs
-    HAL_VariableType:$result
-  );
-
-  let assemblyFormat = [{
-    $variable attr-dict `:` type($result)
-  }];
-
-  let verifier = [{ return verifyVariableLoadOp(*this); }];
-}
-
-def HAL_VariableLoadIndirectOp : HAL_Op<"variable.load.indirect"> {
-  let summary = [{loads a value from a global variable}];
-  let description = [{
-    Returns a copy of the variable value.
-  }];
-
-  let arguments = (ins
-    HAL_VariablePtr:$variable
-  );
-  let results = (outs
-    HAL_VariableType:$result
-  );
-
-  let assemblyFormat = [{
-    $variable attr-dict `:` type($variable) `->` type($result)
-  }];
-
-  let verifier = [{ return verifyVariableLoadIndirectOp(*this); }];
-
-  let hasCanonicalizer = 1;
-}
-
-def HAL_VariableStoreOp : HAL_Op<"variable.store"> {
-  let summary = [{stores a value into a global variable}];
-  let description = [{
-    Stores a copy of the value into a variable.
-  }];
-
-  let arguments = (ins
-    HAL_VariableType:$value,
-    HAL_VariableRefAttr:$variable
-  );
-
-  let assemblyFormat = [{
-    $value `,` $variable attr-dict `:` type($value)
-  }];
-
-  let verifier = [{ return verifyVariableStoreOp(*this); }];
-
-  let hasCanonicalizer = 1;
-}
-
-def HAL_VariableStoreIndirectOp : HAL_Op<"variable.store.indirect"> {
-  let summary = [{stores a value into a global variable}];
-  let description = [{
-    Stores a copy of the value into a variable.
-  }];
-
-  let arguments = (ins
-    HAL_VariableType:$value,
-    HAL_VariablePtr:$variable
-  );
-
-  let assemblyFormat = [{
-    $value `,` $variable attr-dict `:` type($value) `->` type($variable)
-  }];
-
-  let verifier = [{ return verifyVariableStoreIndirectOp(*this); }];
-
-  let hasCanonicalizer = 1;
-}
-
-//===----------------------------------------------------------------------===//
 // Control flow
 //===----------------------------------------------------------------------===//
 
diff --git a/iree/compiler/Dialect/HAL/IR/test/BUILD b/iree/compiler/Dialect/HAL/IR/test/BUILD
index a3a2012..564225c 100644
--- a/iree/compiler/Dialect/HAL/IR/test/BUILD
+++ b/iree/compiler/Dialect/HAL/IR/test/BUILD
@@ -36,8 +36,6 @@
             "interface_ops.mlir",
             "invalid.mlir",
             "semaphore_ops.mlir",
-            "variable_folding.mlir",
-            "variable_ops.mlir",
         ],
         include = ["*.mlir"],
     ),
diff --git a/iree/compiler/Dialect/HAL/IR/test/CMakeLists.txt b/iree/compiler/Dialect/HAL/IR/test/CMakeLists.txt
index 56260fc..e560f52 100644
--- a/iree/compiler/Dialect/HAL/IR/test/CMakeLists.txt
+++ b/iree/compiler/Dialect/HAL/IR/test/CMakeLists.txt
@@ -33,8 +33,6 @@
     "interface_ops.mlir"
     "invalid.mlir"
     "semaphore_ops.mlir"
-    "variable_folding.mlir"
-    "variable_ops.mlir"
   DATA
     iree::tools::IreeFileCheck
     iree::tools::iree-opt
diff --git a/iree/compiler/Dialect/HAL/IR/test/constant_ops.mlir b/iree/compiler/Dialect/HAL/IR/test/constant_ops.mlir
index 125027e..50971df 100644
--- a/iree/compiler/Dialect/HAL/IR/test/constant_ops.mlir
+++ b/iree/compiler/Dialect/HAL/IR/test/constant_ops.mlir
@@ -74,8 +74,8 @@
 
 // -----
 
-// CHECK: hal.variable @storage0_buffer0 : !hal.buffer
-hal.variable @storage0_buffer0 : !hal.buffer
+// CHECK: util.global private @storage0_buffer0 : !hal.buffer
+util.global private @storage0_buffer0 : !hal.buffer
 // CHECK-LABEL: func @runtime_buffer_subspan()
 func @runtime_buffer_subspan() {
   // CHECK-NEXT: = hal.constant.subspan @storage0_buffer0[#hal.byte_range<0, 1024>] : tensor<4xf32>
diff --git a/iree/compiler/Dialect/HAL/IR/test/invalid.mlir b/iree/compiler/Dialect/HAL/IR/test/invalid.mlir
index e1b918f..18ecfc3 100644
--- a/iree/compiler/Dialect/HAL/IR/test/invalid.mlir
+++ b/iree/compiler/Dialect/HAL/IR/test/invalid.mlir
@@ -1,17 +1,17 @@
 // RUN: iree-opt -split-input-file -verify-diagnostics %s
 
-hal.variable @var mutable : !hal.buffer
+util.global mutable @var : !hal.buffer
 func @fn(%arg0: !hal.buffer_view) {
-  // expected-error @+1 {{variable var is '!hal.buffer' but store is '!hal.buffer_view'}}
-  hal.variable.store %arg0, @var : !hal.buffer_view
+  // expected-error @+1 {{global var is '!hal.buffer' but store is '!hal.buffer_view'}}
+  util.global.store %arg0, @var : !hal.buffer_view
   return
 }
 
 // -----
-hal.variable @var mutable : !hal.buffer
+util.global mutable @var : !hal.buffer
 func @fn(%arg0: !hal.buffer_view) {
-  %0 = hal.variable.address @var_indirect_with_buffer_view_store : !util.ptr<!hal.buffer>
-  // expected-error @+1 {{variable pointer is '!hal.buffer' but store is '!hal.buffer_view'}}
-  hal.variable.store.indirect %arg0, %0 : !hal.buffer_view -> !util.ptr<!hal.buffer>
+  %0 = util.global.address @var : !util.ptr<!hal.buffer>
+  // expected-error @+1 {{global pointer is '!hal.buffer' but store is '!hal.buffer_view'}}
+  util.global.store.indirect %arg0, %0 : !hal.buffer_view -> !util.ptr<!hal.buffer>
   return
 }
diff --git a/iree/compiler/Dialect/HAL/IR/test/variable_folding.mlir b/iree/compiler/Dialect/HAL/IR/test/variable_folding.mlir
deleted file mode 100644
index 2d7a1f9..0000000
--- a/iree/compiler/Dialect/HAL/IR/test/variable_folding.mlir
+++ /dev/null
@@ -1,53 +0,0 @@
-// Tests folding and canonicalization of variable ops.
-
-// RUN: iree-opt -split-input-file -canonicalize %s | iree-opt -split-input-file | IreeFileCheck %s
-
-// CHECK: hal.variable @v_initialized = 4 : i32
-hal.variable @v_initialized init(@initializer) : i32
-func @initializer() -> i32 {
-  %0 = constant 4 : i32
-  return %0 : i32
-}
-
-// -----
-
-hal.variable @v_unused : !hal.buffer
-// CHECK-LABEL: @unused_load
-func @unused_load() {
-  // CHECK-NEXT: return
-  %0 = hal.variable.load @v_unused : !hal.buffer
-  return
-}
-
-// -----
-
-hal.variable @v_nop mutable : !hal.buffer
-// CHECK-LABEL: @nop_load_store
-func @nop_load_store() {
-  // CHECK-NEXT: return
-  %0 = hal.variable.load @v_nop : !hal.buffer
-  hal.variable.store %0, @v_nop : !hal.buffer
-  return
-}
-
-// -----
-
-hal.variable @v : !hal.buffer
-// CHECK-LABEL: @fold_load_indirect
-func @fold_load_indirect() -> !hal.buffer {
-  %0 = hal.variable.address @v : !util.ptr<!hal.buffer>
-  // CHECK-NEXT: = hal.variable.load @v
-  %1 = hal.variable.load.indirect %0 : !util.ptr<!hal.buffer> -> !hal.buffer
-  return %1 : !hal.buffer
-}
-
-// -----
-
-hal.variable @v mutable : !hal.buffer
-// CHECK-LABEL: @fold_store_indirect
-func @fold_store_indirect(%arg0 : !hal.buffer) {
-  %0 = hal.variable.address @v : !util.ptr<!hal.buffer>
-  // CHECK-NEXT: hal.variable.store %arg0, @v
-  hal.variable.store.indirect %arg0, %0 : !hal.buffer -> !util.ptr<!hal.buffer>
-  return
-}
diff --git a/iree/compiler/Dialect/HAL/IR/test/variable_ops.mlir b/iree/compiler/Dialect/HAL/IR/test/variable_ops.mlir
deleted file mode 100644
index 198ed0e..0000000
--- a/iree/compiler/Dialect/HAL/IR/test/variable_ops.mlir
+++ /dev/null
@@ -1,73 +0,0 @@
-// Tests printing and parsing of variable ops.
-
-// RUN: iree-opt -allow-unregistered-dialect -split-input-file %s | iree-opt -allow-unregistered-dialect -split-input-file | IreeFileCheck %s
-
-// CHECK: hal.variable @v_immutable : tensor<i32>
-hal.variable @v_immutable : tensor<i32>
-// CHECK: hal.variable @v_mutable mutable : tensor<i32>
-hal.variable @v_mutable mutable : tensor<i32>
-
-// -----
-
-// CHECK: hal.variable @v_initialized_const0 = 4 : i32
-hal.variable @v_initialized_const0 = 4 : i32
-
-// CHECK: hal.variable @v_initialized_const1 = 40 : i32
-hal.variable @v_initialized_const1 = 40 : i32
-
-// CHECK: hal.variable @v_initialized_const2 = 40 : i64
-hal.variable @v_initialized_const2 = 40 : i64
-
-// -----
-
-// CHECK: hal.variable @v_initialized init(@initializer) : !hal.buffer
-hal.variable @v_initialized init(@initializer) : !hal.buffer
-func private @initializer() -> !hal.buffer
-
-// -----
-
-hal.variable @v_loaded : !hal.buffer
-// CHECK-LABEL: @loaded
-func @loaded() {
-  // CHECK-NEXT: = hal.variable.load @v_loaded : !hal.buffer
-  %0 = hal.variable.load @v_loaded : !hal.buffer
-  return
-}
-
-// -----
-
-hal.variable @v_stored mutable : !hal.buffer
-// CHECK-LABEL: @stored
-func @stored() {
-  // CHECK-NEXT: %[[BUF:.+]] = "test_hal.buffer"
-  %0 = "test_hal.buffer"() : () -> !hal.buffer
-  // CHECK-NEXT: hal.variable.store %[[BUF]], @v_stored : !hal.buffer
-  hal.variable.store %0, @v_stored : !hal.buffer
-  return
-}
-
-// -----
-
-hal.variable @v_loaded : !hal.buffer
-// CHECK-LABEL: @loaded_indirect
-func @loaded_indirect() {
-  // CHECK-NEXT: %[[ADDR:.+]] = hal.variable.address @v_loaded
-  %0 = hal.variable.address @v_loaded : !util.ptr<!hal.buffer>
-  // CHECK-NEXT: = hal.variable.load.indirect %[[ADDR]]
-  %1 = hal.variable.load.indirect %0 : !util.ptr<!hal.buffer> -> !hal.buffer
-  return
-}
-
-// -----
-
-hal.variable @v_stored mutable : !hal.buffer
-// CHECK-LABEL: @stored_indirect
-func @stored_indirect() {
-  // CHECK-NEXT: %[[BUF:.+]] = "test_hal.buffer"
-  %0 = "test_hal.buffer"() : () -> !hal.buffer
-  // CHECK-NEXT: %[[ADDR:.+]] = hal.variable.address @v_stored
-  %1 = hal.variable.address @v_stored : !util.ptr<!hal.buffer>
-  // CHECK-NEXT: hal.variable.store.indirect %[[BUF]], %[[ADDR]]
-  hal.variable.store.indirect %0, %1 : !hal.buffer -> !util.ptr<!hal.buffer>
-  return
-}
diff --git a/iree/compiler/Dialect/HAL/Transforms/BUILD b/iree/compiler/Dialect/HAL/Transforms/BUILD
index 7797917..ab73955 100644
--- a/iree/compiler/Dialect/HAL/Transforms/BUILD
+++ b/iree/compiler/Dialect/HAL/Transforms/BUILD
@@ -15,7 +15,6 @@
     srcs = [
         "AssignTargetDevices.cpp",
         "BenchmarkBatchDispatches.cpp",
-        "CSEVariableLoads.cpp",
         "ConvertToHAL.cpp",
         "IdentifyConstantPools.cpp",
         "InlineDeviceSwitches.cpp",
@@ -49,7 +48,7 @@
         "//iree/compiler/Dialect/HAL/Utils",
         "//iree/compiler/Dialect/Shape/IR",
         "//iree/compiler/Dialect/Shape/Transforms",
-        "//iree/compiler/Dialect/Util/Conversion:PreserveCompilerHints",
+        "//iree/compiler/Dialect/Util/Conversion",
         "//iree/compiler/Dialect/Util/IR",
         "//iree/compiler/Dialect/Util/Transforms",
         "@llvm-project//llvm:Support",
diff --git a/iree/compiler/Dialect/HAL/Transforms/CMakeLists.txt b/iree/compiler/Dialect/HAL/Transforms/CMakeLists.txt
index 2f5bd2d..101666c 100644
--- a/iree/compiler/Dialect/HAL/Transforms/CMakeLists.txt
+++ b/iree/compiler/Dialect/HAL/Transforms/CMakeLists.txt
@@ -18,7 +18,6 @@
   SRCS
     "AssignTargetDevices.cpp"
     "BenchmarkBatchDispatches.cpp"
-    "CSEVariableLoads.cpp"
     "ConvertToHAL.cpp"
     "IdentifyConstantPools.cpp"
     "InlineDeviceSwitches.cpp"
@@ -55,7 +54,7 @@
     iree::compiler::Dialect::HAL::Utils
     iree::compiler::Dialect::Shape::IR
     iree::compiler::Dialect::Shape::Transforms
-    iree::compiler::Dialect::Util::Conversion::PreserveCompilerHints
+    iree::compiler::Dialect::Util::Conversion
     iree::compiler::Dialect::Util::IR
     iree::compiler::Dialect::Util::Transforms
   PUBLIC
diff --git a/iree/compiler/Dialect/HAL/Transforms/CSEVariableLoads.cpp b/iree/compiler/Dialect/HAL/Transforms/CSEVariableLoads.cpp
deleted file mode 100644
index e4ae95b..0000000
--- a/iree/compiler/Dialect/HAL/Transforms/CSEVariableLoads.cpp
+++ /dev/null
@@ -1,95 +0,0 @@
-// Copyright 2020 The IREE Authors
-//
-// Licensed under the Apache License v2.0 with LLVM Exceptions.
-// See https://llvm.org/LICENSE.txt for license information.
-// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
-
-#include "iree/compiler/Dialect/HAL/IR/HALDialect.h"
-#include "iree/compiler/Dialect/HAL/IR/HALOps.h"
-#include "iree/compiler/Dialect/HAL/Transforms/Passes.h"
-#include "mlir/IR/Builders.h"
-#include "mlir/Pass/Pass.h"
-
-namespace mlir {
-namespace iree_compiler {
-namespace IREE {
-namespace HAL {
-
-class CSEVariableLoadsPass
-    : public PassWrapper<CSEVariableLoadsPass, OperationPass<FuncOp>> {
- public:
-  void getDependentDialects(DialectRegistry &registry) const override {
-    registry.insert<HALDialect>();
-  }
-
-  StringRef getArgument() const override {
-    return "iree-hal-cse-variable-loads";
-  }
-
-  StringRef getDescription() const override {
-    return "Eliminates redundant 'hal.variable.load' ops within functions with "
-           "no 'hal.variable.store' ops";
-  }
-
-  void runOnOperation() override {
-    auto funcOp = getOperation();
-
-    // Note: we assume that no IsolatedFromAbove regions are used with HAL
-    // variables here. If there are any, they would need to be treated
-    // independently of other regions.
-    DenseMap<StringRef, SmallVector<VariableLoadOp, 4>>
-        loadOpsGroupedByVariable;
-    DenseSet<StringRef> storeOps;
-    funcOp.walk([&](Operation *op) {
-      if (auto loadOp = dyn_cast<VariableLoadOp>(op)) {
-        loadOpsGroupedByVariable[loadOp.variable()].push_back(loadOp);
-      } else if (auto storeOp = dyn_cast<VariableStoreOp>(op)) {
-        storeOps.insert(storeOp.variable());
-      } else if (auto storeIndirectOp = dyn_cast<VariableStoreIndirectOp>(op)) {
-        // Not sure (without more analysis) which variable is being stored,
-        // so give up.
-        // TODO(scotttodd): handle indirect stores (trace to variable names)
-        return;
-      } else if (auto callOp = dyn_cast<CallOp>(op)) {
-        // Not sure (without more analysis) which variables may be written to
-        // as a result of the call, so give up.
-        // TODO(scotttodd): handle calls (aggregate set of variables written
-        //   by the function or any function that may be reached under it)
-        return;
-      }
-    });
-
-    Block *entryBlock = &funcOp.body().front();
-    auto entryBlockBuilder = OpBuilder::atBlockBegin(entryBlock);
-
-    for (auto loadOpsGroup : loadOpsGroupedByVariable) {
-      StringRef variableName = loadOpsGroup.first;
-      auto loadOps = loadOpsGroup.second;
-
-      // Bail if the variable was written to at all.
-      // We could do more complex analysis here but that's better handled
-      // upstream with real CSE and side effect modeling :)
-      if (storeOps.count(variableName)) continue;
-
-      if (loadOps.size() == 1) continue;
-
-      // Replace all load ops with a new load op in the entry block.
-      auto clonedLoadOp = entryBlockBuilder.clone(*loadOps[0]);
-      for (int i = 0; i < loadOps.size(); ++i) {
-        loadOps[i].replaceAllUsesWith(clonedLoadOp);
-        loadOps[i].erase();
-      }
-    }
-  }
-};
-
-std::unique_ptr<OperationPass<FuncOp>> createCSEVariableLoadsPass() {
-  return std::make_unique<CSEVariableLoadsPass>();
-}
-
-static PassRegistration<CSEVariableLoadsPass> pass;
-
-}  // namespace HAL
-}  // namespace IREE
-}  // namespace iree_compiler
-}  // namespace mlir
diff --git a/iree/compiler/Dialect/HAL/Transforms/ConvertToHAL.cpp b/iree/compiler/Dialect/HAL/Transforms/ConvertToHAL.cpp
index 73ad8e7..a06b073 100644
--- a/iree/compiler/Dialect/HAL/Transforms/ConvertToHAL.cpp
+++ b/iree/compiler/Dialect/HAL/Transforms/ConvertToHAL.cpp
@@ -16,7 +16,7 @@
 #include "iree/compiler/Dialect/HAL/IR/HALOps.h"
 #include "iree/compiler/Dialect/HAL/IR/HALTypes.h"
 #include "iree/compiler/Dialect/Shape/IR/ShapeOps.h"
-#include "iree/compiler/Dialect/Util/Conversion/PreserveCompilerHints.h"
+#include "iree/compiler/Dialect/Util/Conversion/ConversionPatterns.h"
 #include "iree/compiler/Dialect/Util/IR/UtilDialect.h"
 #include "iree/compiler/Dialect/Util/IR/UtilOps.h"
 #include "iree/compiler/Dialect/Util/IR/UtilTypes.h"
@@ -74,9 +74,12 @@
     populateIREEToHALPatterns(context, conversionTarget, typeConverter,
                               patterns);
 
-    IREE::Util::setupCompilerHintsLegality(context, conversionTarget,
-                                           typeConverter);
-    IREE::Util::populatePreserveCompilerHintsPatterns(context, patterns);
+    populateUtilConversionPatterns(context, conversionTarget, typeConverter,
+                                   patterns);
+    conversionTarget.addDynamicallyLegalOp<IREE::Util::GlobalOp>(
+        [&](IREE::Util::GlobalOp op) {
+          return typeConverter.isLegal(op.type());
+        });
 
     setupStandardToHALLegality(context, conversionTarget, typeConverter);
     populateStandardToHALPatterns(context, patterns, typeConverter);
diff --git a/iree/compiler/Dialect/HAL/Transforms/IdentifyConstantPools.cpp b/iree/compiler/Dialect/HAL/Transforms/IdentifyConstantPools.cpp
index 704b84f..98b5e08 100644
--- a/iree/compiler/Dialect/HAL/Transforms/IdentifyConstantPools.cpp
+++ b/iree/compiler/Dialect/HAL/Transforms/IdentifyConstantPools.cpp
@@ -12,6 +12,8 @@
 #include "iree/compiler/Dialect/HAL/IR/HALDialect.h"
 #include "iree/compiler/Dialect/HAL/IR/HALOps.h"
 #include "iree/compiler/Dialect/HAL/Transforms/Passes.h"
+#include "iree/compiler/Dialect/Util/IR/UtilDialect.h"
+#include "iree/compiler/Dialect/Util/IR/UtilOps.h"
 #include "mlir/Dialect/StandardOps/IR/Ops.h"
 #include "mlir/IR/Attributes.h"
 #include "mlir/IR/Builders.h"
@@ -33,6 +35,7 @@
     registry.insert<mlir::StandardOpsDialect>();
     registry.insert<IREE::Flow::FlowDialect>();
     registry.insert<IREE::HAL::HALDialect>();
+    registry.insert<IREE::Util::UtilDialect>();
   }
 
   StringRef getArgument() const override {
@@ -40,27 +43,27 @@
   }
 
   StringRef getDescription() const override {
-    return "Combines constant variables into one or more hal.constant_pools "
+    return "Combines constant globals into one or more hal.constant_pools "
            "based on usage semantics.";
   }
 
   void runOnOperation() override {
     auto moduleOp = getOperation();
 
-    // Gather constant variables. We assume that prior passes/pipelines have
-    // hoisted anything worth pooling to flow.variables at the module scope.
-    // We expect that immutable variables have already been de-duped and that
-    // mutable variables that remain may have identical initializers.
-    SmallVector<IREE::Flow::VariableOp, 16> mutableOps;
-    SmallVector<IREE::Flow::VariableOp, 16> immutableOps;
-    for (auto variableOp : moduleOp.getOps<IREE::Flow::VariableOp>()) {
-      if (!variableOp.initial_value().hasValue()) continue;
-      auto variableType = variableOp.type().dyn_cast<RankedTensorType>();
-      if (!variableType) continue;
-      if (variableOp.is_mutable()) {
-        mutableOps.push_back(variableOp);
+    // Gather constant globals. We assume that prior passes/pipelines have
+    // hoisted anything worth pooling to util.globals at the module scope.
+    // We expect that immutable globals have already been de-duped and that
+    // mutable globals that remain may have identical initializers.
+    SmallVector<IREE::Util::GlobalOp, 16> mutableOps;
+    SmallVector<IREE::Util::GlobalOp, 16> immutableOps;
+    for (auto globalOp : moduleOp.getOps<IREE::Util::GlobalOp>()) {
+      if (!globalOp.initial_value().hasValue()) continue;
+      auto globalType = globalOp.type().dyn_cast<RankedTensorType>();
+      if (!globalType) continue;
+      if (globalOp.is_mutable()) {
+        mutableOps.push_back(globalOp);
       } else {
-        immutableOps.push_back(variableOp);
+        immutableOps.push_back(globalOp);
       }
     }
     if (mutableOps.empty() && immutableOps.empty()) {
@@ -74,20 +77,18 @@
 
     SymbolTable moduleSymbolTable(moduleOp);
     auto moduleBuilder = OpBuilder::atBlockBegin(moduleOp.getBody());
-    auto variableUsages = gatherVariableUsages(moduleOp);
+    auto globalUsages = gatherGlobalUsages(moduleOp);
 
     // Process the mutable ops where each constant is only used as an
     // initializer. The lifetime of these is short as we only use them to
-    // populate the initial variable buffer contents.
+    // populate the initial global buffer contents.
     makeConstantPool("_const_pool_init", mutableOps, bufferConstraints,
-                     variableUsages, moduleOp, moduleSymbolTable,
-                     moduleBuilder);
+                     globalUsages, moduleOp, moduleSymbolTable, moduleBuilder);
 
     // Process the immutable ops where the same buffer will be used for the
     // lifetime of the module.
     makeConstantPool("_const_pool", immutableOps, bufferConstraints,
-                     variableUsages, moduleOp, moduleSymbolTable,
-                     moduleBuilder);
+                     globalUsages, moduleOp, moduleSymbolTable, moduleBuilder);
 
     // NOTE: pools now contain the values but they are in an undefined order.
     // We should have following passes that reorder the values to cluster them
@@ -96,32 +97,31 @@
   }
 
  private:
-  enum VariableUsage {
+  enum GlobalUsage {
     kAddress = 1 << 0,
     kLoad = 1 << 1,
   };
 
-  // Gathers information about the usage of all variables in the module.
-  DenseMap<StringRef, VariableUsage> gatherVariableUsages(
-      mlir::ModuleOp moduleOp) {
-    DenseMap<StringRef, VariableUsage> uses;
+  // Gathers information about the usage of all globals in the module.
+  DenseMap<StringRef, GlobalUsage> gatherGlobalUsages(mlir::ModuleOp moduleOp) {
+    DenseMap<StringRef, GlobalUsage> uses;
     for (auto funcOp : moduleOp.getOps<mlir::FuncOp>()) {
       funcOp.walk([&](Operation *op) {
-        if (auto addressOp = dyn_cast<IREE::Flow::VariableAddressOp>(op)) {
-          auto it = uses.find(addressOp.variable());
+        if (auto addressOp = dyn_cast<IREE::Util::GlobalAddressOp>(op)) {
+          auto it = uses.find(addressOp.global());
           if (it == uses.end()) {
-            uses[addressOp.variable()] = VariableUsage::kAddress;
+            uses[addressOp.global()] = GlobalUsage::kAddress;
           } else {
-            uses[addressOp.variable()] = static_cast<VariableUsage>(
-                it->second | VariableUsage::kAddress);
+            uses[addressOp.global()] =
+                static_cast<GlobalUsage>(it->second | GlobalUsage::kAddress);
           }
-        } else if (auto loadOp = dyn_cast<IREE::Flow::VariableLoadOp>(op)) {
-          auto it = uses.find(loadOp.variable());
+        } else if (auto loadOp = dyn_cast<IREE::Util::GlobalLoadOp>(op)) {
+          auto it = uses.find(loadOp.global());
           if (it == uses.end()) {
-            uses[loadOp.variable()] = VariableUsage::kLoad;
+            uses[loadOp.global()] = GlobalUsage::kLoad;
           } else {
-            uses[loadOp.variable()] =
-                static_cast<VariableUsage>(it->second | VariableUsage::kLoad);
+            uses[loadOp.global()] =
+                static_cast<GlobalUsage>(it->second | GlobalUsage::kLoad);
           }
         }
       });
@@ -130,14 +130,13 @@
   }
 
   // Makes a new hal.constant_pool containing the values of the given
-  // variable ops. The variables will be erased and all variable loads will be
+  // global ops. The globals will be erased and all global loads will be
   // replaced with constant loads. Returns the constant pool, if it was created.
   Optional<ConstantPoolOp> makeConstantPool(
-      StringRef poolName, ArrayRef<IREE::Flow::VariableOp> variableOps,
+      StringRef poolName, ArrayRef<IREE::Util::GlobalOp> globalOps,
       BufferConstraintsAttr bufferConstraints,
-      DenseMap<StringRef, VariableUsage> &variableUsages,
-      mlir::ModuleOp moduleOp, SymbolTable &moduleSymbolTable,
-      OpBuilder &moduleBuilder) {
+      DenseMap<StringRef, GlobalUsage> &globalUsages, mlir::ModuleOp moduleOp,
+      SymbolTable &moduleSymbolTable, OpBuilder &moduleBuilder) {
     // Create the pool to be filled with constant values.
     auto poolOp = OpBuilder(moduleBuilder.getContext())
                       .create<ConstantPoolOp>(moduleBuilder.getUnknownLoc(),
@@ -145,47 +144,45 @@
     moduleSymbolTable.insert(poolOp, moduleBuilder.getInsertionPoint());
     poolOp.setPrivate();
 
-    // Replace each variable and keep track of the mapping from variable->value.
+    // Replace each global and keep track of the mapping from global->value.
     // This allows us to do one run through the module to replace usages as a
     // post-processing step.
     DenseMap<StringRef, IREE::HAL::ConstantPoolValueOp> constantReplacements;
     SmallVector<Operation *, 4> deadOps;
     auto poolBuilder = OpBuilder::atBlockBegin(poolOp.getBody());
-    for (auto variableOp : variableOps) {
-      // Grab the constant value from the variable that we'll be pooling.
-      auto value = variableOp.initial_value()
-                       .getValue()
-                       .dyn_cast_or_null<ElementsAttr>();
+    for (auto globalOp : globalOps) {
+      // Grab the constant value from the global that we'll be pooling.
+      auto value =
+          globalOp.initial_value().getValue().dyn_cast_or_null<ElementsAttr>();
       assert(value && "value precondition not met: must be elements attr");
 
       // Create the constant in the pool.
       auto valueOp = poolBuilder.create<ConstantPoolValueOp>(
-          variableOp.getLoc(), variableOp.getName(), value);
+          globalOp.getLoc(), globalOp.getName(), value);
       valueOp.setNested();
 
-      // If the variable is an immutable constant and used in compatible
+      // If the global is an immutable constant and used in compatible
       // ways we can turn them into constant loads instead. These will avoid
-      // the additional runtime overhead of variable lifetime tracking and
+      // the additional runtime overhead of global lifetime tracking and
       // allow further optimizations at use sites where we know the values
       // come from constant memory.
-      auto variableUsage = variableUsages[variableOp.getName()];
-      if (!variableOp.is_mutable() &&
-          (variableUsage & VariableUsage::kAddress)) {
-        variableOp.emitWarning() << "variable is used indirectly; currently "
-                                    "unsupported for constant pooling";
+      auto globalUsage = globalUsages[globalOp.getName()];
+      if (!globalOp.is_mutable() && (globalUsage & GlobalUsage::kAddress)) {
+        globalOp.emitWarning() << "global is used indirectly; currently "
+                                  "unsupported for constant pooling";
         continue;
       }
 
-      if (!variableOp.is_mutable()) {
-        // Replace all loads of the variable with loads of the constant.
+      if (!globalOp.is_mutable()) {
+        // Replace all loads of the global with loads of the constant.
         // We do the actual replacement in a post-processing step so we don't
         // modify the IR during this loop.
-        constantReplacements[variableOp.getName()] = valueOp;
-        deadOps.push_back(variableOp);
+        constantReplacements[globalOp.getName()] = valueOp;
+        deadOps.push_back(globalOp);
       } else {
-        // Build an initializer function to populate the variable with the
+        // Build an initializer function to populate the global with the
         // constant value on startup.
-        changeToVariableInitializerFunc(variableOp, valueOp);
+        changeToGlobalInitializerFunc(globalOp, valueOp);
       }
     }
 
@@ -196,9 +193,9 @@
     }
 
     // Process pending usage replacements.
-    replaceConstantVariableLoads(moduleOp, constantReplacements);
+    replaceConstantGlobalLoads(moduleOp, constantReplacements);
 
-    // Cleanup any inlined variables we no longer need after replacement.
+    // Cleanup any inlined globals we no longer need after replacement.
     for (auto deadOp : deadOps) {
       deadOp->erase();
     }
@@ -206,69 +203,67 @@
     return poolOp;
   }
 
-  // Constructs a function that can be used as an initializer for a variable
-  // and inserts it by the variable op in the module.
-  FuncOp changeToVariableInitializerFunc(
-      IREE::Flow::VariableOp variableOp,
-      IREE::HAL::ConstantPoolValueOp valueOp) {
-    // Create the function and make the variable point to it for init.
-    OpBuilder moduleBuilder(variableOp.getContext());
-    moduleBuilder.setInsertionPointAfter(variableOp);
-    auto initializerName = (variableOp.getName() + "_initializer").str();
+  // Constructs a function that can be used as an initializer for a global
+  // and inserts it by the global op in the module.
+  FuncOp changeToGlobalInitializerFunc(IREE::Util::GlobalOp globalOp,
+                                       IREE::HAL::ConstantPoolValueOp valueOp) {
+    // Create the function and make the global point to it for init.
+    OpBuilder moduleBuilder(globalOp.getContext());
+    moduleBuilder.setInsertionPointAfter(globalOp);
+    auto initializerName = (globalOp.getName() + "_initializer").str();
     auto initializerFunc = moduleBuilder.create<FuncOp>(
-        variableOp.getLoc(), initializerName,
-        moduleBuilder.getFunctionType({}, {variableOp.type()}));
+        globalOp.getLoc(), initializerName,
+        moduleBuilder.getFunctionType({}, {globalOp.type()}));
     initializerFunc.setPrivate();
-    variableOp->removeAttr("initial_value");
-    variableOp->setAttr("initializer",
-                        moduleBuilder.getSymbolRefAttr(initializerFunc));
+    globalOp->removeAttr("initial_value");
+    globalOp->setAttr("initializer",
+                      moduleBuilder.getSymbolRefAttr(initializerFunc));
 
     // Emit a constant load that will later on be turned into a runtime buffer
     // reference.
     auto funcBuilder = OpBuilder::atBlockBegin(initializerFunc.addEntryBlock());
     auto constValue = funcBuilder.createOrFold<IREE::HAL::ConstantPoolLoadOp>(
-        variableOp.getLoc(), variableOp.type(),
+        globalOp.getLoc(), globalOp.type(),
         funcBuilder.getSymbolRefAttr(
             valueOp->getParentOfType<ConstantPoolOp>().getName(),
             {funcBuilder.getSymbolRefAttr(valueOp)}));
-    funcBuilder.create<mlir::ReturnOp>(variableOp.getLoc(), constValue);
+    funcBuilder.create<mlir::ReturnOp>(globalOp.getLoc(), constValue);
 
     return initializerFunc;
   }
 
-  // Replaces uses of each variable with references to the constant pool value.
-  void replaceConstantVariableLoads(
+  // Replaces uses of each global with references to the constant pool value.
+  void replaceConstantGlobalLoads(
       mlir::ModuleOp moduleOp,
       DenseMap<StringRef, IREE::HAL::ConstantPoolValueOp> &replacements) {
     SmallVector<
-        std::pair<IREE::Flow::VariableLoadOp, IREE::HAL::ConstantPoolValueOp>,
-        8>
+        std::pair<IREE::Util::GlobalLoadOp, IREE::HAL::ConstantPoolValueOp>, 8>
         loadValues;
     for (auto funcOp : moduleOp.getOps<mlir::FuncOp>()) {
-      funcOp.walk([&](IREE::Flow::VariableLoadOp loadOp) {
-        auto replacement = replacements.find(loadOp.variable());
+      funcOp.walk([&](IREE::Util::GlobalLoadOp loadOp) {
+        auto replacement = replacements.find(loadOp.global());
         if (replacement != replacements.end()) {
           loadValues.push_back(std::make_pair(loadOp, replacement->second));
         }
       });
     }
     for (auto &loadValue : loadValues) {
-      replaceVariableLoadWithConstantLoad(loadValue.first, loadValue.second);
+      replaceGlobalLoadWithConstantLoad(loadValue.first, loadValue.second);
     }
   }
 
-  // Replaces a flow.variable.load with a hal.constant_pool.load of a pooled
+  // Replaces a util.global.load with a hal.constant_pool.load of a pooled
   // value.
-  void replaceVariableLoadWithConstantLoad(
-      IREE::Flow::VariableLoadOp variableLoadOp, ConstantPoolValueOp valueOp) {
-    OpBuilder builder(variableLoadOp);
-    auto loadOp = builder.create<ConstantPoolLoadOp>(
-        variableLoadOp.getLoc(), variableLoadOp.getType(),
+  void replaceGlobalLoadWithConstantLoad(IREE::Util::GlobalLoadOp globalLoadOp,
+                                         ConstantPoolValueOp valueOp) {
+    OpBuilder builder(globalLoadOp);
+    auto poolLoadOp = builder.create<ConstantPoolLoadOp>(
+        globalLoadOp.getLoc(), globalLoadOp.getType(),
         builder.getSymbolRefAttr(
             valueOp->getParentOfType<ConstantPoolOp>().getName(),
             {builder.getSymbolRefAttr(valueOp)}));
-    variableLoadOp.replaceAllUsesWith(loadOp.result());
-    variableLoadOp.erase();
+    globalLoadOp.replaceAllUsesWith(poolLoadOp.result());
+    globalLoadOp.erase();
   }
 };
 
diff --git a/iree/compiler/Dialect/HAL/Transforms/MaterializeConstantPoolBuffers.cpp b/iree/compiler/Dialect/HAL/Transforms/MaterializeConstantPoolBuffers.cpp
index e779dfb..663ad78 100644
--- a/iree/compiler/Dialect/HAL/Transforms/MaterializeConstantPoolBuffers.cpp
+++ b/iree/compiler/Dialect/HAL/Transforms/MaterializeConstantPoolBuffers.cpp
@@ -62,16 +62,16 @@
 
       // 1:1 storage to runtime buffers.
       for (auto storageOp : poolOp.getOps<ConstantStorageOp>()) {
-        makeStorageBufferRuntimeVariable(poolOp, storageOp, moduleSymbolTable,
-                                         insertionPoint);
+        makeStorageBufferRuntimeGlobal(poolOp, storageOp, moduleSymbolTable,
+                                       insertionPoint);
       }
 
       // We currently put all splats on their own so that we are always able to
       // map the storage buffers above as read-only.
       auto splatOps = llvm::to_vector<4>(poolOp.getOps<ConstantPoolSplatOp>());
       if (!splatOps.empty()) {
-        makeSplatRuntimeVariable(poolOp, splatOps, moduleSymbolTable,
-                                 insertionPoint);
+        makeSplatRuntimeGlobal(poolOp, splatOps, moduleSymbolTable,
+                               insertionPoint);
       }
     }
   }
@@ -79,23 +79,23 @@
  private:
   // Creates a runtime buffer into which the storage buffer will be mapped or
   // uploaded.
-  void makeStorageBufferRuntimeVariable(ConstantPoolOp poolOp,
-                                        ConstantStorageOp storageOp,
-                                        SymbolTable &moduleSymbolTable,
-                                        Block::iterator insertionPoint) {
+  void makeStorageBufferRuntimeGlobal(ConstantPoolOp poolOp,
+                                      ConstantStorageOp storageOp,
+                                      SymbolTable &moduleSymbolTable,
+                                      Block::iterator insertionPoint) {
     auto *context = poolOp.getContext();
     auto variableName =
         (poolOp.getName() + storageOp.getName() + "_buffer").str();
     auto variableType = IREE::HAL::BufferType::get(context);
-    auto variableOp = OpBuilder(context).create<IREE::HAL::VariableOp>(
+    auto globalOp = OpBuilder(context).create<IREE::Util::GlobalOp>(
         storageOp.getLoc(), variableName, /*isMutable=*/false, variableType);
-    moduleSymbolTable.insert(variableOp, insertionPoint);
-    variableOp.setPrivate();
+    moduleSymbolTable.insert(globalOp, insertionPoint);
+    globalOp.setPrivate();
 
     // Find all the spans in the pool that map into this storage buffer so that
     // we can update them with their runtime offsets. Note that since we are
     // uploading 1:1 today all the offsets are the same as their storage ones.
-    auto variableSymRef = SymbolRefAttr::get(context, variableOp.getName());
+    auto variableSymRef = SymbolRefAttr::get(context, globalOp.getName());
     for (auto spanOp : poolOp.getOps<ConstantPoolSpanOp>()) {
       if (spanOp.storage_buffer().getLeafReference() != storageOp.getName()) {
         continue;
@@ -105,9 +105,9 @@
     }
 
     auto initializerFunc = makeStorageBufferRuntimeInitializerFunc(
-        variableOp.getName(), storageOp, poolOp.buffer_constraints());
+        globalOp.getName(), storageOp, poolOp.buffer_constraints());
     moduleSymbolTable.insert(initializerFunc, insertionPoint);
-    variableOp.initializerAttr(
+    globalOp.initializerAttr(
         SymbolRefAttr::get(context, initializerFunc.getName()));
   }
 
@@ -163,10 +163,10 @@
 
   // Creates a runtime buffer for the given constant pool splats and constructs
   // its initializer to fill the contents.
-  void makeSplatRuntimeVariable(ConstantPoolOp poolOp,
-                                ArrayRef<ConstantPoolSplatOp> splatOps,
-                                SymbolTable &moduleSymbolTable,
-                                Block::iterator insertionPoint) {
+  void makeSplatRuntimeGlobal(ConstantPoolOp poolOp,
+                              ArrayRef<ConstantPoolSplatOp> splatOps,
+                              SymbolTable &moduleSymbolTable,
+                              Block::iterator insertionPoint) {
     auto *context = poolOp.getContext();
 
     // TODO(benvanik): we don't need host-visible here as we could require that
@@ -182,15 +182,15 @@
                                      return splatOp.getLoc();
                                    })));
     auto variableName = (poolOp.getName() + "_splats").str();
-    auto variableOp = OpBuilder(context).create<IREE::HAL::VariableOp>(
+    auto globalOp = OpBuilder(context).create<IREE::Util::GlobalOp>(
         variableLoc, variableName, /*isMutable=*/false, variableType);
-    moduleSymbolTable.insert(variableOp, insertionPoint);
-    variableOp.setPrivate();
+    moduleSymbolTable.insert(globalOp, insertionPoint);
+    globalOp.setPrivate();
 
     // Compute the ranges for all the splats at runtime and the required buffer
     // size based on the constraints provided.
     auto bufferConstraints = poolOp.buffer_constraints();
-    auto variableSymRef = SymbolRefAttr::get(context, variableOp.getName());
+    auto variableSymRef = SymbolRefAttr::get(context, globalOp.getName());
     uint64_t bufferLength = 0;
     for (auto splatOp : poolOp.getOps<ConstantPoolSplatOp>()) {
       uint64_t splatOffset =
@@ -210,7 +210,7 @@
     // TODO(benvanik): if we spill here we'll need to create more buffers. We
     // could flip this loop inside out and first allocate the splats.
     if (bufferLength > bufferConstraints.max_buffer_range().getZExtValue()) {
-      variableOp.emitError()
+      globalOp.emitError()
           << "constant splat buffer length " << bufferLength
           << " spills max buffer range of "
           << bufferConstraints.max_buffer_range().getZExtValue()
@@ -218,9 +218,9 @@
     }
 
     auto initializerFunc = makeSplatRuntimeInitializerFunc(
-        variableOp.getLoc(), variableOp.getName(), splatOps, bufferLength);
+        globalOp.getLoc(), globalOp.getName(), splatOps, bufferLength);
     moduleSymbolTable.insert(initializerFunc, insertionPoint);
-    variableOp.initializerAttr(
+    globalOp.initializerAttr(
         SymbolRefAttr::get(context, initializerFunc.getName()));
   }
 
diff --git a/iree/compiler/Dialect/HAL/Transforms/MaterializeResourceCaches.cpp b/iree/compiler/Dialect/HAL/Transforms/MaterializeResourceCaches.cpp
index 183a290..5e3ff9f 100644
--- a/iree/compiler/Dialect/HAL/Transforms/MaterializeResourceCaches.cpp
+++ b/iree/compiler/Dialect/HAL/Transforms/MaterializeResourceCaches.cpp
@@ -86,7 +86,8 @@
   }
 
  private:
-  VariableOp defineDescriptorSetLayoutOp(Location loc, ArrayAttr bindingsAttr) {
+  IREE::Util::GlobalOp defineDescriptorSetLayoutOp(Location loc,
+                                                   ArrayAttr bindingsAttr) {
     auto existingIt = descriptorSetLayoutCache_.find(bindingsAttr);
     if (existingIt != descriptorSetLayoutCache_.end()) {
       return existingIt->second;
@@ -98,12 +99,12 @@
     auto initializerName = symbolName + "_initializer";
 
     auto layoutType = DescriptorSetLayoutType::get(loc.getContext());
-    auto variableOp = moduleBuilder.create<VariableOp>(
+    auto globalOp = moduleBuilder.create<IREE::Util::GlobalOp>(
         loc, symbolName,
         /*isMutable=*/false, layoutType, StringRef(initializerName),
         llvm::None);
-    variableOp.setPrivate();
-    descriptorSetLayoutCache_.try_emplace(bindingsAttr, variableOp);
+    globalOp.setPrivate();
+    descriptorSetLayoutCache_.try_emplace(bindingsAttr, globalOp);
 
     auto initializerOp = moduleBuilder.create<FuncOp>(
         loc, initializerName, moduleBuilder.getFunctionType({}, {layoutType}));
@@ -116,12 +117,12 @@
         loc, layoutType, deviceValue, layoutUsage, bindingsAttr);
     blockBuilder.create<mlir::ReturnOp>(loc, layoutValue);
 
-    return variableOp;
+    return globalOp;
   }
 
-  VariableOp defineExecutableLayoutOp(Location loc,
-                                      ArrayAttr setLayoutsArrayAttr,
-                                      IntegerAttr pushConstantsAttr) {
+  IREE::Util::GlobalOp defineExecutableLayoutOp(Location loc,
+                                                ArrayAttr setLayoutsArrayAttr,
+                                                IntegerAttr pushConstantsAttr) {
     // Push constants are optional but we always provide the value.
     if (!pushConstantsAttr) {
       pushConstantsAttr = IntegerAttr::get(IndexType::get(loc.getContext()), 0);
@@ -139,9 +140,9 @@
 
     // First lookup (or create) all the required descriptor sets. This ensures
     // they end up in the proper initialization order.
-    SmallVector<VariableOp, 4> setLayoutVariableOps;
+    SmallVector<IREE::Util::GlobalOp, 4> setLayoutGlobalOps;
     for (auto setLayoutsAttr : setLayoutsArrayAttr) {
-      setLayoutVariableOps.push_back(
+      setLayoutGlobalOps.push_back(
           defineDescriptorSetLayoutOp(loc, setLayoutsAttr.cast<ArrayAttr>()));
     }
 
@@ -151,11 +152,11 @@
     auto initializerName = symbolName + "_initializer";
 
     auto layoutType = ExecutableLayoutType::get(loc.getContext());
-    auto variableOp = moduleBuilder.create<VariableOp>(
+    auto globalOp = moduleBuilder.create<IREE::Util::GlobalOp>(
         loc, symbolName, /*isMutable=*/false, layoutType,
         StringRef(initializerName), llvm::None);
-    variableOp.setPrivate();
-    executableLayoutCache_.try_emplace(cacheKey, variableOp);
+    globalOp.setPrivate();
+    executableLayoutCache_.try_emplace(cacheKey, globalOp);
 
     auto initializerOp = moduleBuilder.create<FuncOp>(
         loc, initializerName, moduleBuilder.getFunctionType({}, {layoutType}));
@@ -163,10 +164,10 @@
     auto *block = initializerOp.addEntryBlock();
     OpBuilder blockBuilder = OpBuilder::atBlockEnd(block);
     SmallVector<Value, 4> setLayoutValues;
-    for (auto setLayoutVariableOp : setLayoutVariableOps) {
-      auto setLayoutValue = blockBuilder.createOrFold<VariableLoadOp>(
+    for (auto setLayoutGlobalOp : setLayoutGlobalOps) {
+      auto setLayoutValue = blockBuilder.createOrFold<IREE::Util::GlobalLoadOp>(
           loc, DescriptorSetLayoutType::get(loc.getContext()),
-          setLayoutVariableOp.sym_name());
+          setLayoutGlobalOp.sym_name());
       setLayoutValues.push_back(setLayoutValue);
     }
     auto deviceValue = blockBuilder.createOrFold<ExSharedDeviceOp>(loc);
@@ -174,21 +175,21 @@
         loc, layoutType, deviceValue, pushConstantsAttr, setLayoutValues);
     blockBuilder.create<mlir::ReturnOp>(loc, layoutValue);
 
-    return variableOp;
+    return globalOp;
   }
 
-  VariableOp defineExecutableOp(ExecutableOp executableOp) {
+  IREE::Util::GlobalOp defineExecutableOp(ExecutableOp executableOp) {
     auto loc = executableOp.getLoc();
     auto symbolName =
         (StringRef("_executable_") + executableOp.sym_name()).str();
     auto initializerName = symbolName + "_initializer";
 
     auto executableType = ExecutableType::get(executableOp.getContext());
-    auto variableOp = moduleBuilder.create<VariableOp>(
+    auto globalOp = moduleBuilder.create<IREE::Util::GlobalOp>(
         loc, symbolName, /*isMutable=*/false, executableType,
         StringRef(initializerName), llvm::None);
-    variableOp.setPrivate();
-    executableCache_.try_emplace(executableOp.sym_name(), variableOp);
+    globalOp.setPrivate();
+    executableCache_.try_emplace(executableOp.sym_name(), globalOp);
 
     auto initializerOp = moduleBuilder.create<FuncOp>(
         loc, initializerName,
@@ -221,13 +222,13 @@
             SymbolTable::lookupNearestSymbolFrom<IREE::HAL::InterfaceOp>(
                 executableOp, entryPointOp.interface());
         assert(interfaceOp && "must have an interface available");
-        auto executableLayoutVariableOp = defineExecutableLayoutOp(
+        auto executableLayoutGlobalOp = defineExecutableLayoutOp(
             executableOp.getLoc(), interfaceOp.getExecutableSetLayoutsAttr(),
             interfaceOp.push_constantsAttr());
         executableLayoutValues.push_back(
-            caseBuilder.createOrFold<VariableLoadOp>(
+            caseBuilder.createOrFold<IREE::Util::GlobalLoadOp>(
                 loc, ExecutableLayoutType::get(loc.getContext()),
-                executableLayoutVariableOp.sym_name()));
+                executableLayoutGlobalOp.sym_name()));
       }
 
       auto executableValue = caseBuilder.createOrFold<ExecutableCreateOp>(
@@ -252,29 +253,29 @@
     auto executableValue = switchOp.getResult(0);
     blockBuilder.create<mlir::ReturnOp>(loc, executableValue);
 
-    return variableOp;
+    return globalOp;
   }
 
   void replaceDescriptorSetLayoutLookupOp(
       DescriptorSetLayoutLookupOp &lookupOp) {
     OpBuilder builder(lookupOp);
-    auto variableOp =
+    auto globalOp =
         defineDescriptorSetLayoutOp(lookupOp.getLoc(), lookupOp.bindings());
-    auto loadOp = builder.create<VariableLoadOp>(
+    auto loadOp = builder.create<IREE::Util::GlobalLoadOp>(
         lookupOp.getLoc(), DescriptorSetLayoutType::get(lookupOp.getContext()),
-        variableOp.sym_name());
+        globalOp.sym_name());
     lookupOp.replaceAllUsesWith(loadOp.getOperation());
     lookupOp.erase();
   }
 
   void replaceExecutableLayoutLookupOp(ExecutableLayoutLookupOp &lookupOp) {
     OpBuilder builder(lookupOp);
-    auto variableOp =
+    auto globalOp =
         defineExecutableLayoutOp(lookupOp.getLoc(), lookupOp.set_layouts(),
                                  lookupOp.push_constantsAttr());
-    auto loadOp = builder.create<VariableLoadOp>(
+    auto loadOp = builder.create<IREE::Util::GlobalLoadOp>(
         lookupOp.getLoc(), ExecutableLayoutType::get(lookupOp.getContext()),
-        variableOp.sym_name());
+        globalOp.sym_name());
     lookupOp.replaceAllUsesWith(loadOp.getOperation());
     lookupOp.erase();
   }
@@ -284,10 +285,10 @@
     auto executableIt = executableCache_.find(lookupOp.executable());
     assert(executableIt != executableCache_.end() &&
            "executable must have been cached");
-    auto variableOp = executableIt->second;
-    auto loadOp = builder.create<VariableLoadOp>(
+    auto globalOp = executableIt->second;
+    auto loadOp = builder.create<IREE::Util::GlobalLoadOp>(
         lookupOp.getLoc(), ExecutableType::get(lookupOp.getContext()),
-        variableOp.sym_name());
+        globalOp.sym_name());
     lookupOp.replaceAllUsesWith(loadOp.getOperation());
     lookupOp.erase();
   }
@@ -295,9 +296,9 @@
   TargetOptions targetOptions_;
 
   OpBuilder moduleBuilder{static_cast<MLIRContext *>(nullptr)};
-  DenseMap<Attribute, VariableOp> descriptorSetLayoutCache_;
-  DenseMap<Attribute, VariableOp> executableLayoutCache_;
-  DenseMap<StringRef, VariableOp> executableCache_;
+  DenseMap<Attribute, IREE::Util::GlobalOp> descriptorSetLayoutCache_;
+  DenseMap<Attribute, IREE::Util::GlobalOp> executableLayoutCache_;
+  DenseMap<StringRef, IREE::Util::GlobalOp> executableCache_;
 
   int nextUniqueExecutableLayoutId = 0;
   int nextUniqueDescriptorSetLayoutId = 0;
diff --git a/iree/compiler/Dialect/HAL/Transforms/MemoizeDeviceQueries.cpp b/iree/compiler/Dialect/HAL/Transforms/MemoizeDeviceQueries.cpp
index 7c61661..92f0ba4 100644
--- a/iree/compiler/Dialect/HAL/Transforms/MemoizeDeviceQueries.cpp
+++ b/iree/compiler/Dialect/HAL/Transforms/MemoizeDeviceQueries.cpp
@@ -83,10 +83,10 @@
           moduleBuilder.getFunctionType({}, {queryType}));
       initializerOp.setPrivate();
       moduleBuilder.setInsertionPoint(initializerOp);
-      auto variableOp = moduleBuilder.create<IREE::HAL::VariableOp>(
+      auto globalOp = moduleBuilder.create<IREE::Util::GlobalOp>(
           fusedLoc, variableName,
           /*isMutable=*/false, initializerOp);
-      variableOp.setPrivate();
+      globalOp.setPrivate();
       moduleBuilder.setInsertionPointAfter(initializerOp);
 
       auto funcBuilder = OpBuilder::atBlockBegin(initializerOp.addEntryBlock());
@@ -100,8 +100,8 @@
 
       for (auto queryOp : queryOps) {
         OpBuilder replaceBuilder(queryOp);
-        auto loadOp = replaceBuilder.create<IREE::HAL::VariableLoadOp>(
-            fusedLoc, queryType, variableOp.getName());
+        auto loadOp = replaceBuilder.create<IREE::Util::GlobalLoadOp>(
+            fusedLoc, queryType, globalOp.getName());
         queryOp.replaceAllUsesWith(ValueRange{
             replaceBuilder.createOrFold<ConstantIntOp>(
                 loadOp.getLoc(), /*value=*/1, /*width=*/1),
diff --git a/iree/compiler/Dialect/HAL/Transforms/Passes.cpp b/iree/compiler/Dialect/HAL/Transforms/Passes.cpp
index 3ba6340..c7680b7 100644
--- a/iree/compiler/Dialect/HAL/Transforms/Passes.cpp
+++ b/iree/compiler/Dialect/HAL/Transforms/Passes.cpp
@@ -11,6 +11,7 @@
 #include "iree/compiler/Dialect/HAL/IR/HALDialect.h"
 #include "iree/compiler/Dialect/HAL/IR/HALOps.h"
 #include "iree/compiler/Dialect/Shape/Transforms/Passes.h"
+#include "iree/compiler/Dialect/Util/Transforms/Passes.h"
 #include "mlir/Conversion/AffineToStandard/AffineToStandard.h"
 #include "mlir/Pass/PassRegistry.h"
 #include "mlir/Transforms/Passes.h"
@@ -145,7 +146,8 @@
   // Run our own CSE on variable loads before moving on.
   // When specifying side effects can help MLIR's core CSE pass eliminate
   // redundant loads we can remove this.
-  passManager.addNestedPass<FuncOp>(createCSEVariableLoadsPass());
+  passManager.addNestedPass<FuncOp>(
+      IREE::Util::createSimplifyGlobalAccessesPass());
 
   if (transformOptions.serializeExecutables) {
     passManager.addNestedPass<IREE::HAL::ExecutableOp>(
diff --git a/iree/compiler/Dialect/HAL/Transforms/test/BUILD b/iree/compiler/Dialect/HAL/Transforms/test/BUILD
index 7506ce9..8c5d6dc 100644
--- a/iree/compiler/Dialect/HAL/Transforms/test/BUILD
+++ b/iree/compiler/Dialect/HAL/Transforms/test/BUILD
@@ -19,7 +19,6 @@
         [
             "assign_target_devices.mlir",
             "benchmark_batch_dispatches.mlir",
-            "cse_variable_loads.mlir",
             "identify_constant_pools.mlir",
             "inline_device_switches.mlir",
             "materialize_constant_pool_buffers.mlir",
diff --git a/iree/compiler/Dialect/HAL/Transforms/test/CMakeLists.txt b/iree/compiler/Dialect/HAL/Transforms/test/CMakeLists.txt
index 4ea32aa..951175ab 100644
--- a/iree/compiler/Dialect/HAL/Transforms/test/CMakeLists.txt
+++ b/iree/compiler/Dialect/HAL/Transforms/test/CMakeLists.txt
@@ -16,7 +16,6 @@
   SRCS
     "assign_target_devices.mlir"
     "benchmark_batch_dispatches.mlir"
-    "cse_variable_loads.mlir"
     "identify_constant_pools.mlir"
     "inline_device_switches.mlir"
     "materialize_constant_pool_buffers.mlir"
diff --git a/iree/compiler/Dialect/HAL/Transforms/test/benchmark_batch_dispatches.mlir b/iree/compiler/Dialect/HAL/Transforms/test/benchmark_batch_dispatches.mlir
index 08f7d86..902d989 100644
--- a/iree/compiler/Dialect/HAL/Transforms/test/benchmark_batch_dispatches.mlir
+++ b/iree/compiler/Dialect/HAL/Transforms/test/benchmark_batch_dispatches.mlir
@@ -1,13 +1,13 @@
 // RUN: iree-opt -split-input-file -test-iree-hal-benchmark-batch-dispatches-2-times %s | IreeFileCheck %s
 
-hal.variable @_executable : !hal.executable
+util.global @_executable : !hal.executable
 
 // CHECK-LABEL: @duplicate_dispatches
 //  CHECK-SAME: (%[[CMD1:.+]]: !hal.command_buffer,
 //  CHECK-SAME:  %[[CMD2:.+]]: !hal.command_buffer)
 func @duplicate_dispatches(%cmd1 : !hal.command_buffer, %cmd2 : !hal.command_buffer) {
-  // CHECK: %[[EXE:.+]] = hal.variable.load @_executable
-  %exe = hal.variable.load @_executable : !hal.executable
+  // CHECK: %[[EXE:.+]] = util.global.load @_executable
+  %exe = util.global.load @_executable : !hal.executable
 
   %c1 = constant 1 : index
   %c2 = constant 2 : index
diff --git a/iree/compiler/Dialect/HAL/Transforms/test/cse_variable_loads.mlir b/iree/compiler/Dialect/HAL/Transforms/test/cse_variable_loads.mlir
deleted file mode 100644
index c6b4991..0000000
--- a/iree/compiler/Dialect/HAL/Transforms/test/cse_variable_loads.mlir
+++ /dev/null
@@ -1,108 +0,0 @@
-// RUN: iree-opt -split-input-file -iree-hal-cse-variable-loads %s | IreeFileCheck %s
-
-// CHECK: hal.variable @_executable : !hal.executable
-hal.variable @_executable : !hal.executable
-
-// CHECK-LABEL: @multiple_reads_no_writes
-// CHECK-SAME: %[[CMD:.+]]: !hal.command_buffer
-func @multiple_reads_no_writes(%cmd : !hal.command_buffer) {
-  // CHECK-NEXT: %[[EXE:.+]] = hal.variable.load @_executable : !hal.executable
-  %exe0 = hal.variable.load @_executable : !hal.executable
-  // CHECK-NOT: hal.variable.load
-  %exe1 = hal.variable.load @_executable : !hal.executable
-  // CHECK-NOT: hal.variable.load
-  %exe2 = hal.variable.load @_executable : !hal.executable
-
-  %c1 = constant 1 : index
-  // CHECK: hal.command_buffer.dispatch<%[[CMD]] : !hal.command_buffer> target(%[[EXE]] : !hal.executable)[0]
-  hal.command_buffer.dispatch<%cmd : !hal.command_buffer> target(%exe0 : !hal.executable)[0] workgroups([%c1, %c1, %c1])
-  // CHECK: hal.command_buffer.dispatch<%[[CMD]] : !hal.command_buffer> target(%[[EXE]] : !hal.executable)[1]
-  hal.command_buffer.dispatch<%cmd : !hal.command_buffer> target(%exe1 : !hal.executable)[1] workgroups([%c1, %c1, %c1])
-  // CHECK: hal.command_buffer.dispatch<%[[CMD]] : !hal.command_buffer> target(%[[EXE]] : !hal.executable)[2]
-  hal.command_buffer.dispatch<%cmd : !hal.command_buffer> target(%exe2 : !hal.executable)[2] workgroups([%c1, %c1, %c1])
-
-  return
-}
-
-// -----
-
-// CHECK: hal.variable @_executable_0 : !hal.executable
-hal.variable @_executable_0 : !hal.executable
-// CHECK: hal.variable @_executable_1 : !hal.executable
-hal.variable @_executable_1 : !hal.executable
-
-// CHECK-LABEL: @different_variables_are_not_eliminated
-// CHECK-SAME: %[[CMD:.+]]: !hal.command_buffer
-func @different_variables_are_not_eliminated(%cmd : !hal.command_buffer) {
-  // CHECK-NEXT: %[[EXE0:.+]] = hal.variable.load @_executable_0 : !hal.executable
-  %exe0 = hal.variable.load @_executable_0 : !hal.executable
-  // CHECK-NEXT: %[[EXE1:.+]] = hal.variable.load @_executable_1 : !hal.executable
-  %exe1 = hal.variable.load @_executable_1 : !hal.executable
-
-  %c1 = constant 1 : index
-  // CHECK: hal.command_buffer.dispatch<%[[CMD]] : !hal.command_buffer> target(%[[EXE0]] : !hal.executable)[0]
-  hal.command_buffer.dispatch<%cmd : !hal.command_buffer> target(%exe0 : !hal.executable)[0] workgroups([%c1, %c1, %c1])
-  // CHECK: hal.command_buffer.dispatch<%[[CMD]] : !hal.command_buffer> target(%[[EXE1]] : !hal.executable)[1]
-  hal.command_buffer.dispatch<%cmd : !hal.command_buffer> target(%exe1 : !hal.executable)[1] workgroups([%c1, %c1, %c1])
-
-  return
-}
-
-// -----
-
-hal.executable @exe {}
-
-// CHECK: hal.variable @_executable mutable : !hal.executable
-hal.variable @_executable mutable : !hal.executable
-
-// CHECK-LABEL: @writes_prevent_cse
-// CHECK-SAME: %[[CMD:.+]]: !hal.command_buffer
-func @writes_prevent_cse(%cmd : !hal.command_buffer) {
-  // CHECK-NEXT: %[[EXE0:.+]] = hal.variable.load @_executable : !hal.executable
-  %exe0 = hal.variable.load @_executable : !hal.executable
-  // CHECK-NEXT: %[[EXE1:.+]] = hal.variable.load @_executable : !hal.executable
-  %exe1 = hal.variable.load @_executable : !hal.executable
-
-  %dev = hal.ex.shared_device : !hal.device
-  %exe = hal.executable.lookup device(%dev : !hal.device) executable(@exe) : !hal.executable
-  // CHECK: hal.variable.store %exe, @_executable : !hal.executable
-  hal.variable.store %exe, @_executable : !hal.executable
-
-  %c1 = constant 1 : index
-  // CHECK: hal.command_buffer.dispatch<%[[CMD]] : !hal.command_buffer> target(%[[EXE0]] : !hal.executable)[0]
-  hal.command_buffer.dispatch<%cmd : !hal.command_buffer> target(%exe0 : !hal.executable)[0] workgroups([%c1, %c1, %c1])
-  // CHECK: hal.command_buffer.dispatch<%[[CMD]] : !hal.command_buffer> target(%[[EXE1]] : !hal.executable)[1]
-  hal.command_buffer.dispatch<%cmd : !hal.command_buffer> target(%exe1 : !hal.executable)[1] workgroups([%c1, %c1, %c1])
-
-  return
-}
-
-// -----
-
-// CHECK: hal.variable @_executable : !hal.executable
-hal.variable @_executable : !hal.executable
-
-// CHECK-LABEL: @reads_in_blocks
-// CHECK-SAME: %[[CMD:.+]]: !hal.command_buffer
-func @reads_in_blocks(%cmd : !hal.command_buffer) {
-  // load should be hoisted to the entry block
-  // CHECK-NEXT: %[[EXE:.+]] = hal.variable.load @_executable : !hal.executable
-
-  %c1 = constant 1 : index
-  %i1 = constant 1 : i1
-  cond_br %i1, ^bb1, ^bb2
-^bb1:
-  // CHECK-NOT: hal.variable.load
-  %exe0 = hal.variable.load @_executable : !hal.executable
-  // CHECK: hal.command_buffer.dispatch<%[[CMD]] : !hal.command_buffer> target(%[[EXE]] : !hal.executable)[0]
-  hal.command_buffer.dispatch<%cmd : !hal.command_buffer> target(%exe0 : !hal.executable)[0] workgroups([%c1, %c1, %c1])
-  br ^bb3
-^bb2:
-  // CHECK-NOT: hal.variable.load
-  %exe1 = hal.variable.load @_executable : !hal.executable
-  // CHECK: hal.command_buffer.dispatch<%[[CMD]] : !hal.command_buffer> target(%[[EXE]] : !hal.executable)[1]
-  hal.command_buffer.dispatch<%cmd : !hal.command_buffer> target(%exe1 : !hal.executable)[1] workgroups([%c1, %c1, %c1])
-  br ^bb3
-^bb3:
-  return
-}
diff --git a/iree/compiler/Dialect/HAL/Transforms/test/identify_constant_pools.mlir b/iree/compiler/Dialect/HAL/Transforms/test/identify_constant_pools.mlir
index b8fe060..370d5b1 100644
--- a/iree/compiler/Dialect/HAL/Transforms/test/identify_constant_pools.mlir
+++ b/iree/compiler/Dialect/HAL/Transforms/test/identify_constant_pools.mlir
@@ -13,20 +13,20 @@
 //      CHECK: hal.constant_pool @_const_pool attributes
 // CHECK-SAME:     buffer_constraints = #hal.buffer_constraints<max_allocation_size = 1073741824, min_buffer_offset_alignment = 256, max_buffer_range = 134217728, min_buffer_range_alignment = 16>
 // CHECK-NEXT:   hal.constant_pool.value @cst0 = dense<1.000000e+00> : tensor<1xf32>
-flow.variable @cst0 dense<1.000000e+00> : tensor<1xf32>
+util.global private @cst0 = dense<1.000000e+00> : tensor<1xf32>
 // CHECK-NEXT:   hal.constant_pool.value @cst1 = dense<[2.100000e+00, 3.200000e+00, 4.300000e+00, 5.400000e+00]> : tensor<4xf32>
-flow.variable @cst1 dense<[2.1, 3.2, 4.3, 5.4]> : tensor<4xf32>
+util.global private @cst1 = dense<[2.1, 3.2, 4.3, 5.4]> : tensor<4xf32>
 // CHECK-NEXT:   hal.constant_pool.value @cst2 = dense<[6, 7, 8]> : tensor<3xi8>
-flow.variable @cst2 dense<[6, 7, 8]> : tensor<3xi8>
+util.global private @cst2 = dense<[6, 7, 8]> : tensor<3xi8>
 
 // CHECK-LABEL: func @immutable_variables
 func @immutable_variables() -> (tensor<1xf32>, tensor<4xf32>, tensor<3xi8>) {
   // CHECK-NEXT: = hal.constant_pool.load @_const_pool::@cst0 : tensor<1xf32>
-  %cst0 = flow.variable.load @cst0 : tensor<1xf32>
+  %cst0 = util.global.load @cst0 : tensor<1xf32>
   // CHECK-NEXT: = hal.constant_pool.load @_const_pool::@cst1 : tensor<4xf32>
-  %cst1 = flow.variable.load @cst1 : tensor<4xf32>
+  %cst1 = util.global.load @cst1 : tensor<4xf32>
   // CHECK-NEXT: = hal.constant_pool.load @_const_pool::@cst2 : tensor<3xi8>
-  %cst2 = flow.variable.load @cst2 : tensor<3xi8>
+  %cst2 = util.global.load @cst2 : tensor<3xi8>
   return %cst0, %cst1, %cst2 : tensor<1xf32>, tensor<4xf32>, tensor<3xi8>
 }
 
@@ -37,8 +37,8 @@
 //      CHECK: hal.constant_pool @_const_pool_init
 // CHECK-NEXT:   hal.constant_pool.value @variable_0 = dense<3.000000e+00> : tensor<128xf32>
 
-// CHECK: flow.variable @variable_0 mutable init(@variable_0_initializer)
-flow.variable @variable_0 mutable dense<3.0> : tensor<128xf32>
+// CHECK: util.global private mutable @variable_0 initializer(@variable_0_initializer)
+util.global private mutable @variable_0 = dense<3.0> : tensor<128xf32>
 // CHECK-NEXT: func private @variable_0_initializer() -> tensor<128xf32>
 // CHECK-NEXT:   [[CONST:%.+]] = hal.constant_pool.load @_const_pool_init::@variable_0 : tensor<128xf32>
 // CHECK-NEXT:   return [[CONST]] : tensor<128xf32>
@@ -46,20 +46,20 @@
 
 // CHECK-LABEL: func @mutable_variables
 func @mutable_variables() -> tensor<128xf32> {
-  // CHECK: flow.variable.load @variable_0
-  %var_0 = flow.variable.load @variable_0 : tensor<128xf32>
+  // CHECK: util.global.load @variable_0
+  %var_0 = util.global.load @variable_0 : tensor<128xf32>
   return %var_0 : tensor<128xf32>
 }
 
 // -----
 
 // NOTE: indirect variable accesses not currently supported.
-// CHECK: flow.variable @_large_const_0
-flow.variable @_large_const_0 dense<3.0> : tensor<128xf32>
+// CHECK: util.global private @_large_const_0
+util.global private @_large_const_0 = dense<3.0> : tensor<128xf32>
 func @skip_indirect_variables() -> (tensor<128xf32>) {
-  // CHECK: flow.variable.address
-  %0 = flow.variable.address @_large_const_0 : !util.ptr<tensor<128xf32>>
-  // CHECK: flow.variable.load.indirect
-  %1 = flow.variable.load.indirect %0 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+  // CHECK: util.global.address
+  %0 = util.global.address @_large_const_0 : !util.ptr<tensor<128xf32>>
+  // CHECK: util.global.load.indirect
+  %1 = util.global.load.indirect %0 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
   return %1 : tensor<128xf32>
 }
diff --git a/iree/compiler/Dialect/HAL/Transforms/test/materialize_constant_pool_buffers.mlir b/iree/compiler/Dialect/HAL/Transforms/test/materialize_constant_pool_buffers.mlir
index 90c59dd..e0130f3 100644
--- a/iree/compiler/Dialect/HAL/Transforms/test/materialize_constant_pool_buffers.mlir
+++ b/iree/compiler/Dialect/HAL/Transforms/test/materialize_constant_pool_buffers.mlir
@@ -9,7 +9,7 @@
   hal.constant_storage @_storage = dense<1> : vector<768xi8>
 }
 
-//      CHECK: hal.variable @dense_variable_init_storage_buffer init(@dense_variable_init_storage_buffer_initializer) : !hal.buffer
+//      CHECK: util.global private @dense_variable_init_storage_buffer initializer(@dense_variable_init_storage_buffer_initializer) : !hal.buffer
 // CHECK-NEXT: func private @dense_variable_init_storage_buffer_initializer() -> !hal.buffer
 //      CHECK: %[[STORAGE:.+]] = hal.constant_storage.lookup @dense_variable_init::@_storage : !util.byte_buffer
 //      CHECK: = hal.allocator.map<%allocator : !hal.allocator>
@@ -26,7 +26,7 @@
   hal.constant_pool.splat @cst1 = dense<1234567890> : tensor<8xi32>
 }
 
-//      CHECK: hal.variable @splat_variable_init_splats init(@splat_variable_init_splats_initializer) : !hal.buffer
+//      CHECK: util.global private @splat_variable_init_splats initializer(@splat_variable_init_splats_initializer) : !hal.buffer
 // CHECK-NEXT: func private @splat_variable_init_splats_initializer() -> !hal.buffer
 //      CHECK: %[[BUFFER:.+]] = hal.allocator.allocate<%allocator : !hal.allocator>
 // CHECK-SAME:   type("HostVisible|DeviceVisible|DeviceLocal")
@@ -54,17 +54,17 @@
   hal.constant_storage @_storage1 = dense<[6, 7, 8, 0]> : vector<4xi8>
 }
 
-//      CHECK: hal.variable @pool_storage0_buffer init(@pool_storage0_buffer_initializer) : !hal.buffer
+//      CHECK: util.global private @pool_storage0_buffer initializer(@pool_storage0_buffer_initializer) : !hal.buffer
 // CHECK-NEXT: func private @pool_storage0_buffer_initializer() -> !hal.buffer
 //      CHECK: %[[STORAGE:.+]] = hal.constant_storage.lookup @pool::@_storage0 : !util.byte_buffer
 //      CHECK: = hal.allocator.map<%allocator : !hal.allocator>
 // CHECK-SAME:   source(%[[STORAGE]] : !util.byte_buffer)[%c0, %c16]
 // CHECK-SAME:   : !hal.buffer
 
-//      CHECK: hal.variable @pool_storage1_buffer init(@pool_storage1_buffer_initializer) : !hal.buffer
+//      CHECK: util.global private @pool_storage1_buffer initializer(@pool_storage1_buffer_initializer) : !hal.buffer
 // CHECK-NEXT: func private @pool_storage1_buffer_initializer() -> !hal.buffer
 
-//      CHECK: hal.variable @pool_splats init(@pool_splats_initializer) : !hal.buffer
+//      CHECK: util.global private @pool_splats initializer(@pool_splats_initializer) : !hal.buffer
 // CHECK-NEXT: func private @pool_splats_initializer() -> !hal.buffer
 //      CHECK: %[[BUFFER:.+]] = hal.allocator.allocate<%allocator : !hal.allocator>
 // CHECK-SAME:   : !hal.buffer{%c64}
diff --git a/iree/compiler/Dialect/HAL/Transforms/test/materialize_interfaces.mlir b/iree/compiler/Dialect/HAL/Transforms/test/materialize_interfaces.mlir
index ec77f0c..b9fec3f 100644
--- a/iree/compiler/Dialect/HAL/Transforms/test/materialize_interfaces.mlir
+++ b/iree/compiler/Dialect/HAL/Transforms/test/materialize_interfaces.mlir
@@ -349,8 +349,8 @@
     }
   }
 }
-hal.variable @storage0 : !hal.buffer
-hal.variable @storage1 : !hal.buffer
+util.global @storage0 : !hal.buffer
+util.global @storage1 : !hal.buffer
 func @usage(%func_arg: tensor<8x4xf32>) -> tensor<4x8xf32> {
   %0 = flow.ex.stream.fragment(%func_arg) : (tensor<8x4xf32>) -> tensor<4x8xf32> =
       (%stream_arg: tensor<8x4xf32>) -> tensor<4x8xf32> {
diff --git a/iree/compiler/Dialect/HAL/Transforms/test/materialize_resource_caches.mlir b/iree/compiler/Dialect/HAL/Transforms/test/materialize_resource_caches.mlir
index ac269cb..2336174 100644
--- a/iree/compiler/Dialect/HAL/Transforms/test/materialize_resource_caches.mlir
+++ b/iree/compiler/Dialect/HAL/Transforms/test/materialize_resource_caches.mlir
@@ -1,6 +1,6 @@
 // RUN: iree-opt -split-input-file -iree-hal-materialize-resource-caches %s | IreeFileCheck %s
 
-//      CHECK: hal.variable @_descriptor_set_layout_0 init(@_descriptor_set_layout_0_initializer) : !hal.descriptor_set_layout
+//      CHECK: util.global private @_descriptor_set_layout_0 initializer(@_descriptor_set_layout_0_initializer) : !hal.descriptor_set_layout
 // CHECK-NEXT: func private @_descriptor_set_layout_0_initializer() -> !hal.descriptor_set_layout {
 // CHECK-NEXT:   %device = hal.ex.shared_device : !hal.device
 // CHECK-NEXT:   %descriptor_set_layout = hal.descriptor_set_layout.create
@@ -15,7 +15,7 @@
 
 // CHECK-LABEL: @descriptorSetLayoutLookup
 func @descriptorSetLayoutLookup(%device : !hal.device) -> !hal.descriptor_set_layout {
-  // CHECK-NEXT: %[[LAYOUT:.+]] = hal.variable.load @_descriptor_set_layout_0 : !hal.descriptor_set_layout
+  // CHECK-NEXT: %[[LAYOUT:.+]] = util.global.load @_descriptor_set_layout_0 : !hal.descriptor_set_layout
   %0 = hal.descriptor_set_layout.lookup device(%device : !hal.device)
                                         usage(PushOnly)
                                         bindings([
@@ -28,11 +28,11 @@
 
 // -----
 
-// CHECK: hal.variable @_descriptor_set_layout_0 init(@_descriptor_set_layout_0_initializer) : !hal.descriptor_set_layout
+// CHECK: util.global private @_descriptor_set_layout_0 initializer(@_descriptor_set_layout_0_initializer) : !hal.descriptor_set_layout
 
-//      CHECK: hal.variable @_executable_layout_0 init(@_executable_layout_0_initializer) : !hal.executable_layout
+//      CHECK: util.global private @_executable_layout_0 initializer(@_executable_layout_0_initializer) : !hal.executable_layout
 // CHECK-NEXT: func private @_executable_layout_0_initializer() -> !hal.executable_layout {
-// CHECK-NEXT:   %[[SET0:.+]] = hal.variable.load @_descriptor_set_layout_0 : !hal.descriptor_set_layout
+// CHECK-NEXT:   %[[SET0:.+]] = util.global.load @_descriptor_set_layout_0 : !hal.descriptor_set_layout
 // CHECK-NEXT:   %device = hal.ex.shared_device : !hal.device
 // CHECK-NEXT:   %executable_layout = hal.executable_layout.create
 // CHECK-SAME:     device(%device : !hal.device)
@@ -43,7 +43,7 @@
 
 // CHECK-LABEL: @exeLayoutLookup
 func @exeLayoutLookup(%device : !hal.device) -> !hal.executable_layout {
-  // CHECK: %[[LAYOUT:.+]] = hal.variable.load @_executable_layout_0 : !hal.executable_layout
+  // CHECK: %[[LAYOUT:.+]] = util.global.load @_executable_layout_0 : !hal.executable_layout
   %0 = hal.executable_layout.lookup device(%device : !hal.device)
                                     layouts([
     [
@@ -57,13 +57,13 @@
 
 // -----
 
-// CHECK: hal.variable @_descriptor_set_layout_0
-// CHECK: hal.variable @_descriptor_set_layout_1
+// CHECK: util.global private @_descriptor_set_layout_0
+// CHECK: util.global private @_descriptor_set_layout_1
 
-//      CHECK: hal.variable @_executable_layout_0 init(@_executable_layout_0_initializer) : !hal.executable_layout
+//      CHECK: util.global private @_executable_layout_0 initializer(@_executable_layout_0_initializer) : !hal.executable_layout
 // CHECK-NEXT: func private @_executable_layout_0_initializer() -> !hal.executable_layout {
-// CHECK-NEXT:   %[[SET0:.+]] = hal.variable.load @_descriptor_set_layout_0 : !hal.descriptor_set_layout
-// CHECK-NEXT:   %[[SET1:.+]] = hal.variable.load @_descriptor_set_layout_1 : !hal.descriptor_set_layout
+// CHECK-NEXT:   %[[SET0:.+]] = util.global.load @_descriptor_set_layout_0 : !hal.descriptor_set_layout
+// CHECK-NEXT:   %[[SET1:.+]] = util.global.load @_descriptor_set_layout_1 : !hal.descriptor_set_layout
 // CHECK-NEXT:   %device = hal.ex.shared_device : !hal.device
 // CHECK-NEXT:   %executable_layout = hal.executable_layout.create
 // CHECK-SAME:     device(%device : !hal.device)
@@ -74,7 +74,7 @@
 
 // CHECK-LABEL: @sharedLayoutLookup
 func @sharedLayoutLookup(%device : !hal.device) -> !hal.executable_layout {
-  // CHECK: %[[LAYOUT:.+]] = hal.variable.load @_executable_layout_0 : !hal.executable_layout
+  // CHECK: %[[LAYOUT:.+]] = util.global.load @_executable_layout_0 : !hal.executable_layout
   %0 = hal.executable_layout.lookup device(%device : !hal.device)
                                     layouts([
     [
@@ -92,7 +92,7 @@
 
 // CHECK: @otherDescriptorSetLayoutLookup
 func @otherDescriptorSetLayoutLookup(%device : !hal.device) -> !hal.descriptor_set_layout {
-  // CHECK: %[[LAYOUT:.+]] = hal.variable.load @_descriptor_set_layout_0 : !hal.descriptor_set_layout
+  // CHECK: %[[LAYOUT:.+]] = util.global.load @_descriptor_set_layout_0 : !hal.descriptor_set_layout
   %0 = hal.descriptor_set_layout.lookup device(%device : !hal.device)
                                         usage(PushOnly)
                                         bindings([
@@ -138,19 +138,19 @@
   }
 }
 
-// CHECK-DAG: hal.variable @_descriptor_set_layout_0
-// CHECK-DAG: hal.variable @_executable_layout_0
-// CHECK-DAG: hal.variable @_descriptor_set_layout_1
-// CHECK-DAG: hal.variable @_executable_layout_1
+// CHECK-DAG: util.global private @_descriptor_set_layout_0
+// CHECK-DAG: util.global private @_executable_layout_0
+// CHECK-DAG: util.global private @_descriptor_set_layout_1
+// CHECK-DAG: util.global private @_executable_layout_1
 
-// CHECK: hal.variable @_executable_exe init(@_executable_exe_initializer) : !hal.executable
+// CHECK: util.global private @_executable_exe initializer(@_executable_exe_initializer) : !hal.executable
 // CHECK: func private @_executable_exe_initializer() -> !hal.executable {
 // CHECK:   %[[DEV:.+]] = hal.ex.shared_device : !hal.device
 // CHECK:   %[[RET:.+]] = hal.device.switch<%[[DEV]] : !hal.device> -> !hal.executable
 // CHECK:   #hal.device.match.executable.format<"vmvx-bytecode-fb"> {
-// CHECK:     %[[LAYOUT0:.+]] = hal.variable.load @_executable_layout_0 : !hal.executable_layout
-// CHECK:     %[[LAYOUT0_2:.+]] = hal.variable.load @_executable_layout_0 : !hal.executable_layout
-// CHECK:     %[[LAYOUT1:.+]] = hal.variable.load @_executable_layout_1 : !hal.executable_layout
+// CHECK:     %[[LAYOUT0:.+]] = util.global.load @_executable_layout_0 : !hal.executable_layout
+// CHECK:     %[[LAYOUT0_2:.+]] = util.global.load @_executable_layout_0 : !hal.executable_layout
+// CHECK:     %[[LAYOUT1:.+]] = util.global.load @_executable_layout_1 : !hal.executable_layout
 // CHECK:     %[[EXE:.+]] = hal.executable.create
 // CHECK-SAME:  device(%[[DEV]] : !hal.device)
 // CHECK-SAME:  target(@exe::@vmvx)
@@ -167,7 +167,7 @@
 
 // CHECK-LABEL: @exeLookup
 func @exeLookup(%device : !hal.device) -> !hal.executable {
-  // CHECK: %[[EXE:.+]] = hal.variable.load @_executable_exe : !hal.executable
+  // CHECK: %[[EXE:.+]] = util.global.load @_executable_exe : !hal.executable
   %0 = hal.executable.lookup device(%device : !hal.device)
                              executable(@exe) : !hal.executable
   // CHECK-NEXT: return %[[EXE]]
diff --git a/iree/compiler/Dialect/HAL/Transforms/test/memoize_device_queries.mlir b/iree/compiler/Dialect/HAL/Transforms/test/memoize_device_queries.mlir
index 41fa0ec..77f60af 100644
--- a/iree/compiler/Dialect/HAL/Transforms/test/memoize_device_queries.mlir
+++ b/iree/compiler/Dialect/HAL/Transforms/test/memoize_device_queries.mlir
@@ -1,31 +1,31 @@
 // RUN: iree-opt -split-input-file -iree-hal-memoize-device-queries -canonicalize %s | IreeFileCheck %s
 
-//      CHECK: hal.variable @_device_query_0 init(@_device_query_0_initializer) : i1
+//      CHECK: util.global private @_device_query_0 initializer(@_device_query_0_initializer) : i1
 //      CHECK: func private @_device_query_0_initializer() -> i1
 // CHECK-NEXT:   %[[DEVICE:.+]] = hal.ex.shared_device : !hal.device
 // CHECK-NEXT:   %[[OK0:.+]], %[[VALUE0:.+]] = hal.device.query<%[[DEVICE]] : !hal.device> key("hal.device.id" :: "id0*") : i1, i1 = false
 // CHECK-NEXT:   return %[[VALUE0]] : i1
 
-//      CHECK: hal.variable @_device_query_1 init(@_device_query_1_initializer) : i1
+//      CHECK: util.global private @_device_query_1 initializer(@_device_query_1_initializer) : i1
 //      CHECK: func private @_device_query_1_initializer() -> i1
 // CHECK-NEXT:   %[[DEVICE:.+]] = hal.ex.shared_device : !hal.device
 // CHECK-NEXT:   %[[OK1:.+]], %[[VALUE1:.+]] = hal.device.query<%[[DEVICE]] : !hal.device> key("hal.device.id" :: "id1") : i1, i1 = false
 // CHECK-NEXT:   return %[[VALUE1]] : i1
 
-// CHECK: hal.variable @_device_query_2
+// CHECK: util.global private @_device_query_2
 
 // CHECK-LABEL: func @device_matchers
 func @device_matchers(%device : !hal.device) -> (i1, i1, i1, i1) {
   // Same queries (same variables):
-  // CHECK-NEXT: = hal.variable.load @_device_query_0 : i1
+  // CHECK-NEXT: = util.global.load @_device_query_0 : i1
   %id0_a_ok, %id0_a = hal.device.query<%device : !hal.device> key("hal.device.id" :: "id0*") : i1, i1 = false
-  // CHECK-NEXT: = hal.variable.load @_device_query_0 : i1
+  // CHECK-NEXT: = util.global.load @_device_query_0 : i1
   %id0_b_ok, %id0_b = hal.device.query<%device : !hal.device> key("hal.device.id" :: "id0*") : i1, i1 = false
 
   // Same query but with different defaults (different variables):
-  // CHECK-NEXT: = hal.variable.load @_device_query_1 : i1
+  // CHECK-NEXT: = util.global.load @_device_query_1 : i1
   %id1_a_ok, %id1_a = hal.device.query<%device : !hal.device> key("hal.device.id" :: "id1") : i1, i1 = false
-  // CHECK-NEXT: = hal.variable.load @_device_query_2 : i1
+  // CHECK-NEXT: = util.global.load @_device_query_2 : i1
   %id1_b_ok, %id1_b = hal.device.query<%device : !hal.device> key("hal.device.id" :: "id1") : i1, i1 = true
 
   return %id0_a, %id0_b, %id1_a, %id1_b : i1, i1, i1, i1
diff --git a/iree/compiler/Dialect/Util/Conversion/BUILD b/iree/compiler/Dialect/Util/Conversion/BUILD
index df5120e..a3b1b0c 100644
--- a/iree/compiler/Dialect/Util/Conversion/BUILD
+++ b/iree/compiler/Dialect/Util/Conversion/BUILD
@@ -11,16 +11,19 @@
 )
 
 cc_library(
-    name = "PreserveCompilerHints",
+    name = "Conversion",
     srcs = [
-        "PreserveCompilerHints.cpp",
+        "ConversionPatterns.cpp",
     ],
     hdrs = [
-        "PreserveCompilerHints.h",
+        "ConversionPatterns.h",
     ],
     deps = [
         "//iree/compiler/Dialect/Util/IR",
+        "@llvm-project//llvm:Support",
         "@llvm-project//mlir:IR",
+        "@llvm-project//mlir:StandardOps",
+        "@llvm-project//mlir:Support",
         "@llvm-project//mlir:Transforms",
     ],
 )
diff --git a/iree/compiler/Dialect/Util/Conversion/CMakeLists.txt b/iree/compiler/Dialect/Util/Conversion/CMakeLists.txt
index 9b8def8..dbf27e4 100644
--- a/iree/compiler/Dialect/Util/Conversion/CMakeLists.txt
+++ b/iree/compiler/Dialect/Util/Conversion/CMakeLists.txt
@@ -12,13 +12,16 @@
 
 iree_cc_library(
   NAME
-    PreserveCompilerHints
+    Conversion
   HDRS
-    "PreserveCompilerHints.h"
+    "ConversionPatterns.h"
   SRCS
-    "PreserveCompilerHints.cpp"
+    "ConversionPatterns.cpp"
   DEPS
+    LLVMSupport
     MLIRIR
+    MLIRStandard
+    MLIRSupport
     MLIRTransforms
     iree::compiler::Dialect::Util::IR
   PUBLIC
diff --git a/iree/compiler/Dialect/Util/Conversion/ConversionPatterns.cpp b/iree/compiler/Dialect/Util/Conversion/ConversionPatterns.cpp
new file mode 100644
index 0000000..f800f8c
--- /dev/null
+++ b/iree/compiler/Dialect/Util/Conversion/ConversionPatterns.cpp
@@ -0,0 +1,62 @@
+// Copyright 2019 The IREE Authors
+//
+// Licensed under the Apache License v2.0 with LLVM Exceptions.
+// See https://llvm.org/LICENSE.txt for license information.
+// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+
+#include "iree/compiler/Dialect/Util/IR/UtilOps.h"
+#include "iree/compiler/Dialect/Util/IR/UtilTypes.h"
+#include "llvm/ADT/DenseMap.h"
+#include "mlir/Dialect/StandardOps/IR/Ops.h"
+#include "mlir/IR/Attributes.h"
+#include "mlir/IR/BlockAndValueMapping.h"
+#include "mlir/IR/Builders.h"
+#include "mlir/IR/BuiltinOps.h"
+#include "mlir/IR/Matchers.h"
+#include "mlir/Transforms/DialectConversion.h"
+
+namespace mlir {
+namespace iree_compiler {
+namespace {
+
+//===----------------------------------------------------------------------===//
+// Hints
+//===----------------------------------------------------------------------===//
+
+class PreserveDoNotOptimize
+    : public OpConversionPattern<IREE::Util::DoNotOptimizeOp> {
+ public:
+  using OpConversionPattern<IREE::Util::DoNotOptimizeOp>::OpConversionPattern;
+  LogicalResult matchAndRewrite(
+      IREE::Util::DoNotOptimizeOp op, llvm::ArrayRef<Value> operands,
+      ConversionPatternRewriter &rewriter) const override {
+    rewriter.replaceOpWithNewOp<IREE::Util::DoNotOptimizeOp>(op, operands,
+                                                             op->getAttrs());
+    return success();
+  }
+};
+
+}  // namespace
+
+void populateUtilConversionPatterns(MLIRContext *context,
+                                    TypeConverter &typeConverter,
+                                    OwningRewritePatternList &patterns) {
+  patterns.insert<PreserveDoNotOptimize>(context);
+}
+
+void populateUtilConversionPatterns(MLIRContext *context,
+                                    ConversionTarget &conversionTarget,
+                                    TypeConverter &typeConverter,
+                                    OwningRewritePatternList &patterns) {
+  conversionTarget.addDynamicallyLegalOp<IREE::Util::DoNotOptimizeOp>(
+      [&](IREE::Util::DoNotOptimizeOp op) {
+        return llvm::all_of(op.getResultTypes(), [&typeConverter](Type t) {
+          return typeConverter.isLegal(t);
+        });
+      });
+
+  populateUtilConversionPatterns(context, typeConverter, patterns);
+}
+
+}  // namespace iree_compiler
+}  // namespace mlir
diff --git a/iree/compiler/Dialect/Util/Conversion/ConversionPatterns.h b/iree/compiler/Dialect/Util/Conversion/ConversionPatterns.h
new file mode 100644
index 0000000..af07bae
--- /dev/null
+++ b/iree/compiler/Dialect/Util/Conversion/ConversionPatterns.h
@@ -0,0 +1,30 @@
+// Copyright 2021 The IREE Authors
+//
+// Licensed under the Apache License v2.0 with LLVM Exceptions.
+// See https://llvm.org/LICENSE.txt for license information.
+// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+
+#ifndef IREE_COMPILER_DIALECT_UTIL_CONVERSION_CONVERSIONPATTERNS_H_
+#define IREE_COMPILER_DIALECT_UTIL_CONVERSION_CONVERSIONPATTERNS_H_
+
+#include "mlir/Pass/Pass.h"
+#include "mlir/Transforms/DialectConversion.h"
+
+namespace mlir {
+namespace iree_compiler {
+
+// Populates conversion patterns that perform conversion on util dialect ops.
+// These patterns ensure that nested types are run through the provided
+// |typeConverter|.
+void populateUtilConversionPatterns(MLIRContext *context,
+                                    TypeConverter &typeConverter,
+                                    OwningRewritePatternList &patterns);
+void populateUtilConversionPatterns(MLIRContext *context,
+                                    ConversionTarget &conversionTarget,
+                                    TypeConverter &typeConverter,
+                                    OwningRewritePatternList &patterns);
+
+}  // namespace iree_compiler
+}  // namespace mlir
+
+#endif  // IREE_COMPILER_DIALECT_UTIL_CONVERSION_CONVERSIONPATTERNS_H_
diff --git a/iree/compiler/Dialect/Util/Conversion/PreserveCompilerHints.cpp b/iree/compiler/Dialect/Util/Conversion/PreserveCompilerHints.cpp
deleted file mode 100644
index f4f1bda..0000000
--- a/iree/compiler/Dialect/Util/Conversion/PreserveCompilerHints.cpp
+++ /dev/null
@@ -1,49 +0,0 @@
-// Copyright 2019 The IREE Authors
-//
-// Licensed under the Apache License v2.0 with LLVM Exceptions.
-// See https://llvm.org/LICENSE.txt for license information.
-// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
-
-#include "iree/compiler/Dialect/Util/Conversion/PreserveCompilerHints.h"
-
-#include "iree/compiler/Dialect/Util/IR/UtilOps.h"
-#include "mlir/IR/MLIRContext.h"
-#include "mlir/IR/PatternMatch.h"
-#include "mlir/Transforms/DialectConversion.h"
-
-namespace mlir {
-namespace iree_compiler {
-namespace IREE {
-namespace Util {
-
-namespace {
-class PreserveDoNotOptimize : public OpConversionPattern<DoNotOptimizeOp> {
- public:
-  using OpConversionPattern<DoNotOptimizeOp>::OpConversionPattern;
-  LogicalResult matchAndRewrite(
-      DoNotOptimizeOp op, llvm::ArrayRef<Value> operands,
-      ConversionPatternRewriter &rewriter) const override {
-    rewriter.replaceOpWithNewOp<DoNotOptimizeOp>(op, operands, op->getAttrs());
-    return success();
-  }
-};
-}  // namespace
-
-void setupCompilerHintsLegality(MLIRContext *context, ConversionTarget &target,
-                                TypeConverter &typeConverter) {
-  target.addDynamicallyLegalOp<DoNotOptimizeOp>([&](DoNotOptimizeOp op) {
-    return llvm::all_of(op.getResultTypes(), [&typeConverter](Type t) {
-      return typeConverter.isLegal(t);
-    });
-  });
-}
-
-void populatePreserveCompilerHintsPatterns(MLIRContext *context,
-                                           OwningRewritePatternList &patterns) {
-  patterns.insert<PreserveDoNotOptimize>(context);
-}
-
-}  // namespace Util
-}  // namespace IREE
-}  // namespace iree_compiler
-}  // namespace mlir
diff --git a/iree/compiler/Dialect/Util/Conversion/PreserveCompilerHints.h b/iree/compiler/Dialect/Util/Conversion/PreserveCompilerHints.h
deleted file mode 100644
index 96ca616..0000000
--- a/iree/compiler/Dialect/Util/Conversion/PreserveCompilerHints.h
+++ /dev/null
@@ -1,35 +0,0 @@
-// Copyright 2019 The IREE Authors
-//
-// Licensed under the Apache License v2.0 with LLVM Exceptions.
-// See https://llvm.org/LICENSE.txt for license information.
-// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
-
-#ifndef IREE_COMPILER_DIALECT_IREE_CONVERSION_PRESERVECOMPILERHINTS_H_
-#define IREE_COMPILER_DIALECT_IREE_CONVERSION_PRESERVECOMPILERHINTS_H_
-
-#include "mlir/IR/MLIRContext.h"
-#include "mlir/IR/PatternMatch.h"
-#include "mlir/Transforms/DialectConversion.h"
-
-namespace mlir {
-namespace iree_compiler {
-namespace IREE {
-namespace Util {
-
-// Adds op legality rules to |conversionTarget| to preserve compiler hints
-// that satisfy the type constraints of |typeConverter|.
-void setupCompilerHintsLegality(MLIRContext *context,
-                                ConversionTarget &conversionTarget,
-                                TypeConverter &typeConverter);
-
-// Appends all patterns for preserving compiler hints while they are transformed
-// by the dialect conversion framework.
-void populatePreserveCompilerHintsPatterns(MLIRContext *context,
-                                           OwningRewritePatternList &patterns);
-
-}  // namespace Util
-}  // namespace IREE
-}  // namespace iree_compiler
-}  // namespace mlir
-
-#endif  // IREE_COMPILER_DIALECT_IREE_CONVERSION_PRESERVECOMPILERHINTS_H_
diff --git a/iree/compiler/Dialect/Util/Conversion/test/BUILD b/iree/compiler/Dialect/Util/Conversion/test/BUILD
index 88c7759..2921aa9 100644
--- a/iree/compiler/Dialect/Util/Conversion/test/BUILD
+++ b/iree/compiler/Dialect/Util/Conversion/test/BUILD
@@ -16,7 +16,7 @@
 iree_lit_test_suite(
     name = "lit",
     srcs = enforce_glob(
-        ["convert_flow_to_hal.mlir"],
+        ["hint_ops.mlir"],
         include = ["*.mlir"],
     ),
     data = [
diff --git a/iree/compiler/Dialect/Util/Conversion/test/CMakeLists.txt b/iree/compiler/Dialect/Util/Conversion/test/CMakeLists.txt
index 6ff9b49..827d8e4 100644
--- a/iree/compiler/Dialect/Util/Conversion/test/CMakeLists.txt
+++ b/iree/compiler/Dialect/Util/Conversion/test/CMakeLists.txt
@@ -14,7 +14,7 @@
   NAME
     lit
   SRCS
-    "convert_flow_to_hal.mlir"
+    "hint_ops.mlir"
   DATA
     iree::tools::IreeFileCheck
     iree::tools::iree-opt
diff --git a/iree/compiler/Dialect/Util/Conversion/test/convert_flow_to_hal.mlir b/iree/compiler/Dialect/Util/Conversion/test/hint_ops.mlir
similarity index 100%
rename from iree/compiler/Dialect/Util/Conversion/test/convert_flow_to_hal.mlir
rename to iree/compiler/Dialect/Util/Conversion/test/hint_ops.mlir
diff --git a/iree/compiler/Dialect/Util/IR/BUILD b/iree/compiler/Dialect/Util/IR/BUILD
index 9ee3355..cf34616 100644
--- a/iree/compiler/Dialect/Util/IR/BUILD
+++ b/iree/compiler/Dialect/Util/IR/BUILD
@@ -36,6 +36,7 @@
     name = "IR",
     srcs = [
         "UtilDialect.cpp",
+        "UtilOpFolders.cpp",
         "UtilOpInterfaces.cpp.inc",
         "UtilOps.cpp",
         "UtilOps.cpp.inc",
@@ -53,11 +54,14 @@
         ":UtilInterfacesGen",
         ":UtilOpsGen",
         "@llvm-project//llvm:Support",
+        "@llvm-project//mlir:ControlFlowInterfaces",
         "@llvm-project//mlir:IR",
         "@llvm-project//mlir:Parser",
+        "@llvm-project//mlir:SideEffectInterfaces",
         "@llvm-project//mlir:SideEffects",
         "@llvm-project//mlir:StandardOps",
         "@llvm-project//mlir:Support",
+        "@llvm-project//mlir:Transforms",
     ],
 )
 
diff --git a/iree/compiler/Dialect/Util/IR/CMakeLists.txt b/iree/compiler/Dialect/Util/IR/CMakeLists.txt
index c8e23d6..72d4d1f 100644
--- a/iree/compiler/Dialect/Util/IR/CMakeLists.txt
+++ b/iree/compiler/Dialect/Util/IR/CMakeLists.txt
@@ -22,6 +22,7 @@
     "UtilTypes.h"
   SRCS
     "UtilDialect.cpp"
+    "UtilOpFolders.cpp"
     "UtilOpInterfaces.cpp.inc"
     "UtilOps.cpp"
     "UtilOps.cpp.inc"
@@ -30,11 +31,13 @@
     ::UtilInterfacesGen
     ::UtilOpsGen
     LLVMSupport
+    MLIRControlFlowInterfaces
     MLIRIR
     MLIRParser
     MLIRSideEffectInterfaces
     MLIRStandard
     MLIRSupport
+    MLIRTransforms
   PUBLIC
 )
 
diff --git a/iree/compiler/Dialect/Util/IR/UtilBase.td b/iree/compiler/Dialect/Util/IR/UtilBase.td
index 8f25e17..5f05ec7 100644
--- a/iree/compiler/Dialect/Util/IR/UtilBase.td
+++ b/iree/compiler/Dialect/Util/IR/UtilBase.td
@@ -79,19 +79,18 @@
 // NamedTuple type constraint
 //===----------------------------------------------------------------------===//
 
-class NamedTupleElement<int thisOrdinal, string thisName, Type thisType> {
+class Util_NamedTupleElement<int thisOrdinal, string thisName, Type thisType> {
   int ordinal = thisOrdinal;
   string name = thisName;
   Type type = thisType;
 }
 
 // Check if all of the tuple elements are buildable.
-class AreTupleElementsBuildable<list<NamedTupleElement> lst> {
+class Util_AreTupleElementsBuildable<list<Util_NamedTupleElement> lst> {
   bit ret = !foldl(1, lst, lhs, y, !and(lhs, !ne(y.type.builderCall, "")));
 }
 
-// TODO(b/143188410): support ordered tuples in OpBase.td.
-class NamedTupleOf<list<NamedTupleElement> elements, string descr> :
+class Util_NamedTupleOf<list<Util_NamedTupleElement> elements, string descr> :
     Type<And<[
       IsTupleTypePred,
       CPred<"$_self.cast<TupleType>().size() == " # !size(elements)>,
@@ -102,7 +101,7 @@
               element.type.predicate>)>
     ]>, descr> {
   // Generate a builder call if all of the elements are buildable.
-  let builderCall = !if(!eq(AreTupleElementsBuildable<elements>.ret, 0),
+  let builderCall = !if(!eq(Util_AreTupleElementsBuildable<elements>.ret, 0),
     "", "$_builder.getTupleType({" #
         !interleave(!foreach(t, elements, t.type.builderCall), ", ") # "})"
   );
@@ -139,7 +138,7 @@
 // ptr types
 //===----------------------------------------------------------------------===//
 
-def AnyPtr : DialectType<
+def Util_AnyPtr : DialectType<
     Util_Dialect,
     CPred<"$_self.isa<IREE::Util::PtrType>()">,
     "ptr"> {
@@ -149,7 +148,7 @@
   let builderCall = "$_builder.getType<IREE::Util::PtrType>()";
 }
 
-class PtrOf<Type type> :
+class Util_PtrOf<Type type> :
     Type<And<[
       CPred<"$_self.isa<IREE::Util::PtrType>()">,
       SubstLeaves<"$_self", "$_self.cast<IREE::Util::PtrType>().getTargetType()",
@@ -160,7 +159,7 @@
                            "", "IREE::Util::PtrType::get(" # type.builderCall # ")");
 }
 
-class AnyPtrOf<list<Type> types> :
+class Util_AnyPtrOf<list<Type> types> :
     Type<And<[
       CPred<"$_self.isa<IREE::Util::PtrType>()">,
       Or<!foreach(type, types,
@@ -172,6 +171,24 @@
   string builderCall = "";
 }
 
+//===----------------------------------------------------------------------===//
+// Variable types
+//===----------------------------------------------------------------------===//
+
+def Util_GlobalRefAttr : Confined<FlatSymbolRefAttr, [
+  ReferToOp<"IREE::Util::GlobalOp">,
+]>;
+
+def Util_AnyGlobalPtr : TypeAlias<Util_AnyPtr>;
+// TODO(benvanik): actually implement Util_GlobalPtrOf.
+class Util_GlobalPtrOf<list<Type> types> : TypeAlias<Util_AnyPtr>;
+
+//===----------------------------------------------------------------------===//
+// Buffer types
+//===----------------------------------------------------------------------===//
+
+// TODO(benvanik): rework these as a single type with an access mode attr.
+
 def ByteBufferType : DialectType<
     Util_Dialect,
     CPred<"$_self.isa<IREE::Util::ByteBufferType>()">,
@@ -195,7 +212,7 @@
 // List types
 //===----------------------------------------------------------------------===//
 
-def AnyList : DialectType<
+def Util_AnyList : DialectType<
     Util_Dialect,
     CPred<"$_self.isa<IREE::Util::ListType>()">,
     "list"> {
@@ -204,7 +221,7 @@
   }];
 }
 
-class ListOf<Type type> :
+class Util_ListOf<Type type> :
     Type<And<[
       CPred<"$_self.isa<IREE::Util::ListType>()">,
       SubstLeaves<"$_self",
diff --git a/iree/compiler/Dialect/Util/IR/UtilInterfaces.td b/iree/compiler/Dialect/Util/IR/UtilInterfaces.td
index ffed6dd..6deb9a1 100644
--- a/iree/compiler/Dialect/Util/IR/UtilInterfaces.td
+++ b/iree/compiler/Dialect/Util/IR/UtilInterfaces.td
@@ -7,7 +7,7 @@
 #ifndef IREE_DIALECT_UTIL_IR_UTIL_INTERFACES
 #define IREE_DIALECT_UTIL_IR_UTIL_INTERFACES
 
-include "iree/compiler/Dialect/Util/IR/UtilBase.td"
+include "mlir/IR/OpBase.td"
 
 //===----------------------------------------------------------------------===//
 // IREE::Util::TiedOpInterface
@@ -170,4 +170,39 @@
   }];
 }
 
+//===----------------------------------------------------------------------===//
+// IREE::Util::GlobalTypeInterface
+//===----------------------------------------------------------------------===//
+
+def Util_GlobalTypeInterface : TypeInterface<"GlobalTypeInterface"> {
+  let cppNamespace = "::mlir::iree_compiler::IREE::Util";
+
+  let description = [{
+    Interface used to mark types as supported for global variables.
+  }];
+
+  let methods = [
+    InterfaceMethod<
+      /*desc=*/[{
+        Returns true if the access to a global via a specific type is compatible
+        with the storage type of the global. For example, a storage of
+        `tensor<?xf32>` is compatible with an access as `tensor<4xf32>`.
+      }],
+      /*retTy=*/"bool",
+      /*methodName=*/"isAccessStorageCompatible",
+      /*args=*/(ins "Type":$accessType),
+      /*methodBody=*/[{}],
+      /*defaultImplementation=*/[{
+        // If one is a shaped type, then they both must be and have compatible
+        // shapes.
+        if ($_type.isa<ShapedType>() || accessType.isa<ShapedType>()) {
+          return succeeded(mlir::verifyCompatibleShape($_type, accessType));
+        }
+        // Otherwise, the types must be the same.
+        return $_type == accessType;
+      }]
+    >,
+  ];
+}
+
 #endif  // IREE_DIALECT_UTIL_IR_UTIL_INTERFACES
diff --git a/iree/compiler/Dialect/Util/IR/UtilOpFolders.cpp b/iree/compiler/Dialect/Util/IR/UtilOpFolders.cpp
new file mode 100644
index 0000000..18860e8
--- /dev/null
+++ b/iree/compiler/Dialect/Util/IR/UtilOpFolders.cpp
@@ -0,0 +1,174 @@
+// Copyright 2021 The IREE Authors
+//
+// Licensed under the Apache License v2.0 with LLVM Exceptions.
+// See https://llvm.org/LICENSE.txt for license information.
+// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+
+#include "iree/compiler/Dialect/Util/IR/UtilOps.h"
+#include "mlir/IR/Attributes.h"
+#include "mlir/IR/Builders.h"
+#include "mlir/IR/Matchers.h"
+#include "mlir/IR/OpDefinition.h"
+#include "mlir/IR/OpImplementation.h"
+#include "mlir/IR/PatternMatch.h"
+#include "mlir/IR/SymbolTable.h"
+#include "mlir/IR/TypeUtilities.h"
+#include "mlir/IR/Value.h"
+#include "mlir/Interfaces/ControlFlowInterfaces.h"
+#include "mlir/Support/LogicalResult.h"
+
+namespace mlir {
+namespace iree_compiler {
+namespace IREE {
+namespace Util {
+
+//===----------------------------------------------------------------------===//
+// Globals
+//===----------------------------------------------------------------------===//
+
+namespace {
+
+/// Converts global initializer functions that evaluate to a constant to a
+/// specified initial value.
+struct InlineConstantGlobalOpInitializer : public OpRewritePattern<GlobalOp> {
+  using OpRewritePattern<GlobalOp>::OpRewritePattern;
+
+  LogicalResult matchAndRewrite(GlobalOp op,
+                                PatternRewriter &rewriter) const override {
+    if (!op.initializer()) return failure();
+    auto *symbolOp =
+        SymbolTable::lookupNearestSymbolFrom(op, op.initializer().getValue());
+    auto initializer = cast<mlir::FuncOp>(symbolOp);
+    if (initializer.getBlocks().size() != 1) return failure();
+    auto &entryBlock = initializer.getBlocks().front();
+    if (entryBlock.getOperations().size() == 2 &&
+        entryBlock.getTerminator()->hasTrait<OpTrait::ReturnLike>()) {
+      auto &primaryOp = entryBlock.front();
+      Attribute constResult;
+      if (matchPattern(primaryOp.getResult(0), m_Constant(&constResult))) {
+        auto visibility = op.getVisibility();
+        auto newOp = rewriter.replaceOpWithNewOp<GlobalOp>(
+            op, op.sym_name(), op.is_mutable(), op.type(), constResult);
+        newOp.setVisibility(visibility);
+        return success();
+      }
+    }
+    return failure();
+  }
+};
+
+}  // namespace
+
+void GlobalOp::getCanonicalizationPatterns(OwningRewritePatternList &results,
+                                           MLIRContext *context) {
+  results.insert<InlineConstantGlobalOpInitializer>(context);
+}
+
+OpFoldResult GlobalLoadOp::fold(ArrayRef<Attribute> operands) {
+  auto globalOp =
+      SymbolTable::lookupNearestSymbolFrom<GlobalOp>(*this, global());
+  if (!globalOp) return {};
+  if (globalOp->getAttr("noinline")) {
+    // Inlining of the constant has been disabled.
+    return {};
+  } else if (globalOp.is_mutable()) {
+    // We can't inline mutable globals as they may be changed at any time.
+    // There may still be other folders/canonicalizers that can help (such as
+    // store-forwarding).
+    return {};
+  } else if (!globalOp.initial_value()) {
+    // Uninitialized globals (or those with initializers) can't be folded as
+    // we don't yet know the value. InlineConstantGlobalOpInitializer may
+    // help.
+    return {};
+  }
+  return globalOp.initial_value().getValue();
+}
+
+namespace {
+
+/// Turns util.global.address -> util.global.load.indirect into a direct load.
+class PropagateGlobalLoadAddress
+    : public OpRewritePattern<GlobalLoadIndirectOp> {
+  using OpRewritePattern::OpRewritePattern;
+
+ public:
+  LogicalResult matchAndRewrite(GlobalLoadIndirectOp op,
+                                PatternRewriter &rewriter) const override {
+    if (auto addressOp =
+            dyn_cast_or_null<GlobalAddressOp>(op.global().getDefiningOp())) {
+      rewriter.replaceOpWithNewOp<GlobalLoadOp>(op, op.result().getType(),
+                                                addressOp.global());
+      return success();
+    }
+    return failure();
+  }
+};
+
+}  // namespace
+
+void GlobalLoadIndirectOp::getCanonicalizationPatterns(
+    OwningRewritePatternList &results, MLIRContext *context) {
+  results.insert<PropagateGlobalLoadAddress>(context);
+}
+
+namespace {
+
+/// Erases util.global.store ops that are no-ops.
+/// This can happen if there was a global load, some DCE'd usage, and a
+/// store back to the same global: we want to be able to elide the entire load
+/// and store.
+struct EraseUnusedGlobalStoreOp : public OpRewritePattern<GlobalStoreOp> {
+  using OpRewritePattern<GlobalStoreOp>::OpRewritePattern;
+
+  LogicalResult matchAndRewrite(GlobalStoreOp op,
+                                PatternRewriter &rewriter) const override {
+    if (auto loadOp =
+            dyn_cast_or_null<GlobalLoadOp>(op.value().getDefiningOp())) {
+      if (loadOp.global() == op.global()) {
+        rewriter.eraseOp(op);
+        return success();
+      }
+    }
+    return failure();
+  }
+};
+
+}  // namespace
+
+void GlobalStoreOp::getCanonicalizationPatterns(
+    OwningRewritePatternList &results, MLIRContext *context) {
+  results.insert<EraseUnusedGlobalStoreOp>(context);
+}
+
+namespace {
+
+/// Turns util.global.address -> util.global.store.indirect into a direct store.
+class PropagateGlobalStoreAddress
+    : public OpRewritePattern<GlobalStoreIndirectOp> {
+  using OpRewritePattern::OpRewritePattern;
+
+ public:
+  LogicalResult matchAndRewrite(GlobalStoreIndirectOp op,
+                                PatternRewriter &rewriter) const override {
+    if (auto addressOp =
+            dyn_cast_or_null<GlobalAddressOp>(op.global().getDefiningOp())) {
+      rewriter.replaceOpWithNewOp<GlobalStoreOp>(op, op.value(),
+                                                 addressOp.global());
+      return success();
+    }
+    return failure();
+  }
+};
+
+}  // namespace
+
+void GlobalStoreIndirectOp::getCanonicalizationPatterns(
+    OwningRewritePatternList &results, MLIRContext *context) {
+  results.insert<PropagateGlobalStoreAddress>(context);
+}
+
+}  // namespace Util
+}  // namespace IREE
+}  // namespace iree_compiler
+}  // namespace mlir
diff --git a/iree/compiler/Dialect/Util/IR/UtilOps.cpp b/iree/compiler/Dialect/Util/IR/UtilOps.cpp
index 3977552..5cab132 100644
--- a/iree/compiler/Dialect/Util/IR/UtilOps.cpp
+++ b/iree/compiler/Dialect/Util/IR/UtilOps.cpp
@@ -28,6 +28,70 @@
 namespace Util {
 
 //===----------------------------------------------------------------------===//
+// custom<SymbolVisibility>($sym_visibility)
+//===----------------------------------------------------------------------===//
+// some.op custom<SymbolVisibility>($sym_visibility) $sym_name
+// ->
+// some.op @foo
+// some.op private @foo
+
+static ParseResult parseSymbolVisibility(OpAsmParser &parser,
+                                         StringAttr &symVisibilityAttr) {
+  StringRef symVisibility;
+  parser.parseOptionalKeyword(&symVisibility, {"public", "private", "nested"});
+  if (!symVisibility.empty()) {
+    symVisibilityAttr = parser.getBuilder().getStringAttr(symVisibility);
+  }
+  return success();
+}
+
+static void printSymbolVisibility(OpAsmPrinter &p, Operation *op,
+                                  StringAttr symVisibilityAttr) {
+  if (!symVisibilityAttr) {
+    p << "public";
+  } else {
+    p << symVisibilityAttr.getValue();
+  }
+}
+
+//===----------------------------------------------------------------------===//
+// custom<TypeOrAttr>($type, $attr)
+//===----------------------------------------------------------------------===//
+// some.op custom<TypeOrAttr>($type, $attr)
+// ->
+// some.op : i32
+// some.op = 42 : i32
+
+static ParseResult parseTypeOrAttr(OpAsmParser &parser, TypeAttr &typeAttr,
+                                   Attribute &attr) {
+  if (succeeded(parser.parseOptionalEqual())) {
+    if (failed(parser.parseAttribute(attr))) {
+      return parser.emitError(parser.getCurrentLocation())
+             << "expected attribute";
+    }
+    typeAttr = TypeAttr::get(attr.getType());
+  } else {
+    Type type;
+    if (failed(parser.parseColonType(type))) {
+      return parser.emitError(parser.getCurrentLocation()) << "expected type";
+    }
+    typeAttr = TypeAttr::get(type);
+  }
+  return success();
+}
+
+static void printTypeOrAttr(OpAsmPrinter &p, Operation *op, TypeAttr type,
+                            Attribute attr) {
+  if (attr) {
+    p << " = ";
+    p.printAttribute(attr);
+  } else {
+    p << " : ";
+    p.printAttribute(type);
+  }
+}
+
+//===----------------------------------------------------------------------===//
 // util.do_not_optimize
 //===----------------------------------------------------------------------===//
 
@@ -145,6 +209,207 @@
 }
 
 //===----------------------------------------------------------------------===//
+// Globals
+//===----------------------------------------------------------------------===//
+
+// Returns true if the given |accessType| is compatible with the |globalType|.
+// For example, this will return true if the global type is a tensor<?xf32>
+// and the access is tensor<4xf32>.
+static bool isGlobalTypeCompatible(Type globalType, Type accessType) {
+  // If one is a shaped type, then they both must be and have compatible
+  // shapes.
+  if (globalType.isa<ShapedType>() || accessType.isa<ShapedType>()) {
+    return succeeded(mlir::verifyCompatibleShape(globalType, accessType));
+  }
+
+  // TODO(benvanik): use GlobalOpInterface.
+
+  // Otherwise, the types must be the same.
+  return globalType == accessType;
+}
+
+void GlobalOp::build(OpBuilder &builder, OperationState &result, StringRef name,
+                     bool isMutable, Type type, Optional<StringRef> initializer,
+                     Optional<Attribute> initialValue,
+                     ArrayRef<NamedAttribute> attrs) {
+  result.addAttribute(SymbolTable::getSymbolAttrName(),
+                      builder.getStringAttr(name));
+  if (isMutable) {
+    result.addAttribute("is_mutable", builder.getUnitAttr());
+  }
+  if (initializer.hasValue()) {
+    result.addAttribute("initializer",
+                        builder.getSymbolRefAttr(initializer.getValue()));
+  } else if (initialValue.hasValue()) {
+    result.addAttribute("initial_value", initialValue.getValue());
+  }
+  result.addAttribute("type", TypeAttr::get(type));
+  result.attributes.append(attrs.begin(), attrs.end());
+}
+
+void GlobalOp::build(OpBuilder &builder, OperationState &result, StringRef name,
+                     bool isMutable, mlir::FuncOp initializer,
+                     ArrayRef<NamedAttribute> attrs) {
+  build(builder, result, name, isMutable, initializer.getType().getResult(0),
+        initializer.getName(), llvm::None, attrs);
+}
+
+void GlobalOp::build(OpBuilder &builder, OperationState &result, StringRef name,
+                     bool isMutable, Type type, Attribute initialValue,
+                     ArrayRef<NamedAttribute> attrs) {
+  build(builder, result, name, isMutable, type, llvm::None, initialValue,
+        attrs);
+}
+
+void GlobalOp::build(OpBuilder &builder, OperationState &result, StringRef name,
+                     bool isMutable, Type type,
+                     ArrayRef<NamedAttribute> attrs) {
+  build(builder, result, name, isMutable, type, llvm::None, llvm::None, attrs);
+}
+
+static LogicalResult verifyGlobalOp(GlobalOp op) {
+  if (op.initializer().hasValue() && op.initial_value().hasValue()) {
+    return op->emitOpError()
+           << "globals can have either an initializer or an initial value";
+  } else if (op.initializer().hasValue()) {
+    // Ensure initializer returns the same value as the global.
+    auto initializerFunc = SymbolTable::lookupNearestSymbolFrom<mlir::FuncOp>(
+        op, op.initializerAttr());
+    if (!initializerFunc) {
+      return op.emitOpError() << "initializer function " << op.initializerAttr()
+                              << " not found or wrong type";
+    }
+    if (initializerFunc.getType().getNumInputs() != 0 ||
+        initializerFunc.getType().getNumResults() != 1 ||
+        !isGlobalTypeCompatible(op.type(),
+                                initializerFunc.getType().getResult(0))) {
+      return op->emitOpError()
+             << "initializer type mismatch; global " << op.getSymbolName()
+             << " is " << op.type() << " but initializer function "
+             << initializerFunc.getName() << " is "
+             << initializerFunc.getType();
+    }
+  } else if (op.initial_value().hasValue()) {
+    // Ensure the value is something we can convert to a const.
+    if (!isGlobalTypeCompatible(op.type(), op.initial_valueAttr().getType())) {
+      return op->emitOpError()
+             << "initial value type mismatch; global " << op.getSymbolName()
+             << " is " << op.type() << " but initial value provided is "
+             << op.initial_valueAttr().getType();
+    }
+  }
+  return success();
+}
+
+IREE::Util::GlobalOp GlobalAddressOp::getGlobalOp() {
+  return SymbolTable::lookupNearestSymbolFrom<IREE::Util::GlobalOp>(
+      getOperation()->getParentOp(), global());
+}
+
+void GlobalAddressOp::getAsmResultNames(
+    function_ref<void(Value, StringRef)> setNameFn) {
+  setNameFn(result(), Twine("ptr_" + global()).str());
+}
+
+static LogicalResult verifyGlobalAddressOp(GlobalAddressOp op) {
+  auto globalOp = op.getGlobalOp();
+  if (!globalOp) {
+    return op.emitOpError() << "undefined global: " << op.global();
+  }
+  return success();
+}
+
+void GlobalLoadOp::build(OpBuilder &builder, OperationState &state,
+                         GlobalOp globalOp, ArrayRef<NamedAttribute> attrs) {
+  state.addTypes({globalOp.type()});
+  state.addAttribute("global", builder.getSymbolRefAttr(globalOp));
+  state.attributes.append(attrs.begin(), attrs.end());
+}
+
+IREE::Util::GlobalOp GlobalLoadOp::getGlobalOp() {
+  return SymbolTable::lookupNearestSymbolFrom<IREE::Util::GlobalOp>(
+      getOperation()->getParentOp(), global());
+}
+
+bool GlobalLoadOp::isGlobalImmutable() { return !getGlobalOp().is_mutable(); }
+
+void GlobalLoadOp::getAsmResultNames(
+    function_ref<void(Value, StringRef)> setNameFn) {
+  setNameFn(result(), global());
+}
+
+void GlobalLoadOp::getEffects(
+    SmallVectorImpl<MemoryEffects::EffectInstance> &effects) {
+  // HACK: works around the lack of symbol side effects in mlir by only saying
+  // we have a side-effect if the variable we are loading is mutable.
+  auto globalOp =
+      SymbolTable::lookupNearestSymbolFrom<GlobalOp>(*this, global());
+  assert(globalOp);
+  if (globalOp.is_mutable()) {
+    effects.emplace_back(MemoryEffects::Read::get());
+  }
+}
+
+static LogicalResult verifyGlobalLoadOp(GlobalLoadOp op) {
+  auto globalOp = op.getGlobalOp();
+  if (!globalOp) {
+    return op->emitOpError() << "undefined global: " << op.global();
+  }
+  auto loadType = op->getResult(0).getType();
+  if (!isGlobalTypeCompatible(globalOp.type(), loadType)) {
+    return op->emitOpError()
+           << "global type mismatch; global " << op.global() << " is "
+           << globalOp.type() << " but load is " << loadType;
+  }
+  return success();
+}
+
+static LogicalResult verifyGlobalLoadIndirectOp(GlobalLoadIndirectOp &op) {
+  auto globalType =
+      op.global().getType().cast<IREE::Util::PtrType>().getTargetType();
+  auto loadType = op.result().getType();
+  if (!isGlobalTypeCompatible(globalType, loadType)) {
+    return op.emitOpError() << "global type mismatch; global pointer is "
+                            << globalType << " but load is " << loadType;
+  }
+  return success();
+}
+
+IREE::Util::GlobalOp GlobalStoreOp::getGlobalOp() {
+  return SymbolTable::lookupNearestSymbolFrom<IREE::Util::GlobalOp>(
+      getOperation()->getParentOp(), global());
+}
+
+static LogicalResult verifyGlobalStoreOp(GlobalStoreOp op) {
+  auto globalOp = op.getGlobalOp();
+  if (!globalOp) {
+    return op->emitOpError() << "undefined global: " << op.global();
+  }
+  auto storeType = op->getOperand(0).getType();
+  if (globalOp.type() != storeType) {
+    return op->emitOpError()
+           << "global type mismatch; global " << op.global() << " is "
+           << globalOp.type() << " but store is " << storeType;
+  }
+  if (!globalOp.isMutable()) {
+    return op->emitOpError() << "global " << op.global()
+                             << " is not mutable and cannot be stored to";
+  }
+  return success();
+}
+
+static LogicalResult verifyGlobalStoreIndirectOp(GlobalStoreIndirectOp &op) {
+  auto globalType =
+      op.global().getType().cast<IREE::Util::PtrType>().getTargetType();
+  auto storeType = op.value().getType();
+  if (!isGlobalTypeCompatible(globalType, storeType)) {
+    return op.emitOpError() << "global type mismatch; global pointer is "
+                            << globalType << " but store is " << storeType;
+  }
+  return success();
+}
+
+//===----------------------------------------------------------------------===//
 // Lists
 //===----------------------------------------------------------------------===//
 
diff --git a/iree/compiler/Dialect/Util/IR/UtilOps.h b/iree/compiler/Dialect/Util/IR/UtilOps.h
index 9414f11..f0453fa 100644
--- a/iree/compiler/Dialect/Util/IR/UtilOps.h
+++ b/iree/compiler/Dialect/Util/IR/UtilOps.h
@@ -8,10 +8,14 @@
 #define IREE_COMPILER_DIALECT_IREE_IR_IREEOPS_H_
 
 #include "mlir/IR/Attributes.h"
+#include "mlir/IR/BuiltinOps.h"
 #include "mlir/IR/BuiltinTypes.h"
 #include "mlir/IR/Dialect.h"
 #include "mlir/IR/OpDefinition.h"
+#include "mlir/IR/OpImplementation.h"
+#include "mlir/IR/SymbolTable.h"
 #include "mlir/Interfaces/SideEffectInterfaces.h"
+#include "mlir/Transforms/DialectConversion.h"
 
 #define GET_OP_CLASSES
 #include "iree/compiler/Dialect/Util/IR/UtilOps.h.inc"  // IWYU pragma: export
diff --git a/iree/compiler/Dialect/Util/IR/UtilOps.td b/iree/compiler/Dialect/Util/IR/UtilOps.td
index a8912e4..2a7efd2 100644
--- a/iree/compiler/Dialect/Util/IR/UtilOps.td
+++ b/iree/compiler/Dialect/Util/IR/UtilOps.td
@@ -8,6 +8,8 @@
 #define IREE_DIALECT_UTIL_IR_UTIL_OPS
 
 include "iree/compiler/Dialect/Util/IR/UtilBase.td"
+include "mlir/IR/OpAsmInterface.td"
+include "mlir/IR/SymbolInterfaces.td"
 include "mlir/Interfaces/SideEffectInterfaces.td"
 
 //===----------------------------------------------------------------------===//
@@ -149,6 +151,217 @@
 }
 
 //===----------------------------------------------------------------------===//
+// Globals
+//===----------------------------------------------------------------------===//
+
+def Util_GlobalOp : Util_Op<"global", [
+  Symbol,
+]> {
+  let summary = [{stateful global variable declaration}];
+  let description = [{
+    Declares a global variable that maintains its value across invocations.
+    The value is tied to the execution context of the module and different
+    contexts will have different variable storage.
+  }];
+
+  let arguments = (ins
+    OptionalAttr<StrAttr>:$sym_visibility,
+    SymbolNameAttr:$sym_name,
+    TypeAttr:$type,
+    UnitAttr:$is_mutable,
+    OptionalAttr<FlatSymbolRefAttr>:$initializer,
+    OptionalAttr<AnyAttr>:$initial_value
+  );
+
+  let assemblyFormat = [{
+    custom<SymbolVisibility>($sym_visibility)
+    (`mutable` $is_mutable^)?
+    $sym_name
+    attr-dict
+    (`initializer` `(` $initializer^ `)`):(``)?
+    custom<TypeOrAttr>($type, $initial_value)
+  }];
+
+  let skipDefaultBuilders = 1;
+  let builders = [
+    OpBuilder<(ins
+      "StringRef":$name,
+      "bool":$isMutable,
+      "Type":$type,
+      "Optional<StringRef>":$initializer,
+      "Optional<Attribute>":$initialValue,
+      CArg<"ArrayRef<NamedAttribute>", "{}">:$attrs
+    )>,
+    OpBuilder<(ins
+      "StringRef":$name,
+      "bool":$isMutable,
+      "mlir::FuncOp":$initializer,
+      CArg<"ArrayRef<NamedAttribute>", "{}">:$attrs
+    )>,
+    OpBuilder<(ins
+      "StringRef":$name,
+      "bool":$isMutable,
+      "Type":$type,
+      "Attribute":$initialValue,
+      CArg<"ArrayRef<NamedAttribute>", "{}">:$attrs
+    )>,
+    OpBuilder<(ins
+      "StringRef":$name,
+      "bool":$isMutable,
+      "Type":$type,
+      CArg<"ArrayRef<NamedAttribute>", "{}">:$attrs
+    )>,
+  ];
+
+  let extraClassDeclaration = [{
+    StringRef getSymbolName() { return sym_name(); }
+
+    bool isMutable() { return is_mutable(); }
+    void makeMutable() { (*this)->setAttr("is_mutable", UnitAttr::get(getContext())); }
+
+    Optional<StringRef> getInitializerAttr() { return initializer(); }
+    void clearInitializer() { (*this)->removeAttr("initializer"); }
+
+    Optional<Attribute> getInitialValueAttr() { return initial_valueAttr(); }
+    void clearInitialValue() { (*this)->removeAttr("initial_value"); }
+  }];
+
+    // TODO(benvanik): verify matches $type.
+  let verifier = [{ return verifyGlobalOp(*this); }];
+
+  let hasCanonicalizer = 1;
+}
+
+def Util_GlobalAddressOp : Util_PureOp<"global.address", [
+  DeclareOpInterfaceMethods<OpAsmOpInterface>,
+]> {
+  let summary = [{returns an address reference to a global}];
+  let description = [{
+    Returns the address of a global as a typed reference. Can be used with the
+    global load and store indirect ops.
+  }];
+
+  let arguments = (ins
+    Util_GlobalRefAttr:$global
+  );
+  let results = (outs
+    Util_AnyGlobalPtr:$result
+  );
+
+  let assemblyFormat = [{
+    $global attr-dict `:` type($result)
+  }];
+
+  let extraClassDeclaration = [{
+    IREE::Util::GlobalOp getGlobalOp();
+  }];
+}
+
+def Util_GlobalLoadOp : Util_Op<"global.load", [
+  DeclareOpInterfaceMethods<OpAsmOpInterface>,
+  // HACK: works around the lack of symbol side effects in C++.
+  DeclareOpInterfaceMethods<MemoryEffectsOpInterface>,
+]> {
+  let summary = [{loads a value from a global variable}];
+  let description = [{
+    Returns a global variable value.
+  }];
+
+  let arguments = (ins
+    Arg<Util_GlobalRefAttr, "", []>:$global
+  );
+  let results = (outs
+    AnyType:$result
+  );
+
+  let assemblyFormat = [{
+    $global attr-dict `:` type($result)
+  }];
+
+  let builders = [
+    OpBuilder<(ins
+      "IREE::Util::GlobalOp":$globalOp,
+      CArg<"ArrayRef<NamedAttribute>", "{}">:$attributes
+    )>,
+  ];
+
+  let extraClassDeclaration = [{
+    IREE::Util::GlobalOp getGlobalOp();
+    bool isGlobalImmutable();
+  }];
+
+  let verifier = [{ return verifyGlobalLoadOp(*this); }];
+
+  let hasFolder = 1;
+}
+
+def Util_GlobalLoadIndirectOp : Util_Op<"global.load.indirect"> {
+  let summary = [{loads a value from a global variable}];
+  let description = [{
+    Returns a copy of the global variable value.
+  }];
+
+  let arguments = (ins
+    Arg<Util_AnyGlobalPtr, "", []>:$global
+  );
+  let results = (outs
+    AnyType:$result
+  );
+
+  let assemblyFormat = [{
+    $global attr-dict `:` type($global) `->` type($result)
+  }];
+
+  let verifier = [{ return verifyGlobalLoadIndirectOp(*this); }];
+
+  let hasCanonicalizer = 1;
+}
+
+def Util_GlobalStoreOp : Util_Op<"global.store"> {
+  let summary = [{stores a value into a global variable}];
+  let description = [{
+    Stores a copy of the value into a global variable.
+  }];
+
+  let arguments = (ins
+    AnyType:$value,
+    Arg<Util_GlobalRefAttr, "", []>:$global
+  );
+
+  let assemblyFormat = [{
+    $value `,` $global attr-dict `:` type($value)
+  }];
+
+  let extraClassDeclaration = [{
+    IREE::Util::GlobalOp getGlobalOp();
+  }];
+
+  let verifier = [{ return verifyGlobalStoreOp(*this); }];
+
+  let hasCanonicalizer = 1;
+}
+
+def Util_GlobalStoreIndirectOp : Util_Op<"global.store.indirect"> {
+  let summary = [{stores a value into a global variable}];
+  let description = [{
+    Stores a copy of the value into a global variable.
+  }];
+
+  let arguments = (ins
+    AnyType:$value,
+    Arg<Util_AnyGlobalPtr, "", []>:$global
+  );
+
+  let assemblyFormat = [{
+    $value `,` $global attr-dict `:` type($value) `->` type($global)
+  }];
+
+  let verifier = [{ return verifyGlobalStoreIndirectOp(*this); }];
+
+  let hasCanonicalizer = 1;
+}
+
+//===----------------------------------------------------------------------===//
 // Lists
 //===----------------------------------------------------------------------===//
 // NOTE: this type is mostly just a placeholder. Ideally we'd make this
@@ -167,7 +380,7 @@
     Optional<Index>:$initial_capacity
   );
   let results = (outs
-    AnyList:$result
+    Util_AnyList:$result
   );
 
   let assemblyFormat = "($initial_capacity^)? attr-dict `:` type($result)";
@@ -180,7 +393,7 @@
   }];
 
   let arguments = (ins
-    AnyList:$list
+    Util_AnyList:$list
   );
   let results = (outs
     Index:$result
@@ -198,7 +411,7 @@
   }];
 
   let arguments = (ins
-    AnyList:$list,
+    Util_AnyList:$list,
     Index:$new_size
   );
 
@@ -213,7 +426,7 @@
   }];
 
   let arguments = (ins
-    AnyList:$list,
+    Util_AnyList:$list,
     Index:$index
   );
   let results = (outs
@@ -232,7 +445,7 @@
   }];
 
   let arguments = (ins
-    AnyList:$list,
+    Util_AnyList:$list,
     Index:$index,
     AnyType:$value
   );
diff --git a/iree/compiler/Dialect/Util/IR/UtilTypes.cpp b/iree/compiler/Dialect/Util/IR/UtilTypes.cpp
index 8385394..cd2534b 100644
--- a/iree/compiler/Dialect/Util/IR/UtilTypes.cpp
+++ b/iree/compiler/Dialect/Util/IR/UtilTypes.cpp
@@ -108,7 +108,7 @@
   return Base::getChecked(emitError, targetType.getContext(), targetType);
 }
 
-Type PtrType::getTargetType() { return getImpl()->targetType; }
+Type PtrType::getTargetType() const { return getImpl()->targetType; }
 
 //===----------------------------------------------------------------------===//
 // IREE::Util::TiedOpInterface
diff --git a/iree/compiler/Dialect/Util/IR/UtilTypes.h b/iree/compiler/Dialect/Util/IR/UtilTypes.h
index 7ba9b53..c051a65 100644
--- a/iree/compiler/Dialect/Util/IR/UtilTypes.h
+++ b/iree/compiler/Dialect/Util/IR/UtilTypes.h
@@ -11,6 +11,7 @@
 #include "mlir/IR/Diagnostics.h"
 #include "mlir/IR/Location.h"
 #include "mlir/IR/OpDefinition.h"
+#include "mlir/IR/SubElementInterfaces.h"
 #include "mlir/IR/TypeSupport.h"
 #include "mlir/IR/Types.h"
 
@@ -93,7 +94,8 @@
 };
 
 /// Base for typed pointer-like references.
-class PtrType : public Type::TypeBase<PtrType, Type, detail::PtrTypeStorage> {
+class PtrType : public Type::TypeBase<PtrType, Type, detail::PtrTypeStorage,
+                                      mlir::SubElementTypeInterface::Trait> {
  public:
   static PtrType get(Type targetType);
   static PtrType getChecked(Type targetType, Location location);
@@ -102,7 +104,13 @@
 
   using Base::Base;
 
-  Type getTargetType();
+  Type getTargetType() const;
+
+  void walkImmediateSubElements(
+      llvm::function_ref<void(mlir::Attribute)> walkAttrsFn,
+      llvm::function_ref<void(mlir::Type)> walkTypesFn) const {
+    walkTypesFn(getTargetType());
+  }
 };
 
 /// A buffer of constant mapped memory.
diff --git a/iree/compiler/Dialect/Util/IR/test/BUILD b/iree/compiler/Dialect/Util/IR/test/BUILD
index 6aac574..18a5e19 100644
--- a/iree/compiler/Dialect/Util/IR/test/BUILD
+++ b/iree/compiler/Dialect/Util/IR/test/BUILD
@@ -18,9 +18,11 @@
     srcs = enforce_glob(
         [
             "byte_buffer_ops.mlir",
-            "do_not_optimize.mlir",
+            "global_folding.mlir",
+            "global_ops.mlir",
+            "hint_folding.mlir",
+            "hint_ops.mlir",
             "list_ops.mlir",
-            "parse_print.mlir",
         ],
         include = ["*.mlir"],
     ),
diff --git a/iree/compiler/Dialect/Util/IR/test/CMakeLists.txt b/iree/compiler/Dialect/Util/IR/test/CMakeLists.txt
index 2150353..69b48ea 100644
--- a/iree/compiler/Dialect/Util/IR/test/CMakeLists.txt
+++ b/iree/compiler/Dialect/Util/IR/test/CMakeLists.txt
@@ -15,9 +15,11 @@
     lit
   SRCS
     "byte_buffer_ops.mlir"
-    "do_not_optimize.mlir"
+    "global_folding.mlir"
+    "global_ops.mlir"
+    "hint_folding.mlir"
+    "hint_ops.mlir"
     "list_ops.mlir"
-    "parse_print.mlir"
   DATA
     iree::tools::IreeFileCheck
     iree::tools::iree-opt
diff --git a/iree/compiler/Dialect/Util/IR/test/global_folding.mlir b/iree/compiler/Dialect/Util/IR/test/global_folding.mlir
new file mode 100644
index 0000000..13482b6
--- /dev/null
+++ b/iree/compiler/Dialect/Util/IR/test/global_folding.mlir
@@ -0,0 +1,72 @@
+// RUN: iree-opt -split-input-file -canonicalize %s | iree-opt -split-input-file | IreeFileCheck %s
+
+// CHECK: util.global private @v_initialized = dense<4> : tensor<4xi32>
+util.global private @v_initialized initializer(@initializer) : tensor<4xi32>
+func private @initializer() -> tensor<4xi32> {
+  %0 = constant dense<4> : tensor<4xi32>
+  return %0 : tensor<4xi32>
+}
+
+// -----
+
+util.global private @v_unused : tensor<4xi32>
+// CHECK-LABEL: @unused_load
+func @unused_load() {
+  // CHECK-NEXT: return
+  %0 = util.global.load @v_unused : tensor<4xi32>
+  return
+}
+
+// -----
+
+util.global private @v_const = dense<1.0> : tensor<8xf32>
+// CHECK-LABEL: @fold_immutable_const
+func @fold_immutable_const() -> tensor<8xf32> {
+  // CHECK-NEXT: %[[CONST:.+]] = constant dense<1.{{.+}}> : tensor<8xf32>
+  %0 = util.global.load @v_const : tensor<8xf32>
+  // CHECK-NEXT: return %[[CONST]] : tensor<8xf32>
+  return %0 : tensor<8xf32>
+}
+
+// -----
+
+util.global private @v_const {noinline} = dense<1.0> : tensor<8xf32>
+// CHECK-LABEL: @no_fold_noinline_immutable_const
+func @no_fold_noinline_immutable_const() -> tensor<8xf32> {
+  // CHECK-NEXT: = util.global.load @v_const : tensor<8xf32>
+  %0 = util.global.load @v_const : tensor<8xf32>
+  return %0 : tensor<8xf32>
+}
+
+// -----
+
+util.global private mutable @v_nop : tensor<4xi32>
+// CHECK-LABEL: @nop_load_store
+func @nop_load_store() {
+  // CHECK-NEXT: return
+  %0 = util.global.load @v_nop : tensor<4xi32>
+  util.global.store %0, @v_nop : tensor<4xi32>
+  return
+}
+
+// -----
+
+util.global private @v : tensor<4xf32>
+// CHECK-LABEL: @fold_load_indirect
+func @fold_load_indirect() -> tensor<4xf32> {
+  %0 = util.global.address @v : !util.ptr<tensor<4xf32>>
+  // CHECK-NEXT: = util.global.load @v
+  %1 = util.global.load.indirect %0 : !util.ptr<tensor<4xf32>> -> tensor<4xf32>
+  return %1 : tensor<4xf32>
+}
+
+// -----
+
+util.global private mutable @v : tensor<4xf32>
+// CHECK-LABEL: @fold_store_indirect
+func @fold_store_indirect(%arg0 : tensor<4xf32>) {
+  %0 = util.global.address @v : !util.ptr<tensor<4xf32>>
+  // CHECK-NEXT: util.global.store %arg0, @v
+  util.global.store.indirect %arg0, %0 : tensor<4xf32> -> !util.ptr<tensor<4xf32>>
+  return
+}
diff --git a/iree/compiler/Dialect/Util/IR/test/global_ops.mlir b/iree/compiler/Dialect/Util/IR/test/global_ops.mlir
new file mode 100644
index 0000000..b38d3ff
--- /dev/null
+++ b/iree/compiler/Dialect/Util/IR/test/global_ops.mlir
@@ -0,0 +1,73 @@
+// RUN: iree-opt -split-input-file %s | iree-opt -split-input-file | IreeFileCheck %s
+
+// CHECK: util.global public @v_immutable : tensor<i32>
+util.global @v_immutable : tensor<i32>
+// CHECK: util.global public mutable @v_mutable : tensor<i32>
+util.global public mutable @v_mutable : tensor<i32>
+
+// -----
+
+// CHECK: util.global public @v_initialized_const0 = 4 : i32
+util.global public @v_initialized_const0 = 4 : i32
+
+// CHECK: util.global public @v_initialized_const1 = 40 : i32
+util.global public @v_initialized_const1 = 40 : i32
+
+// CHECK: util.global public @v_initialized_const2 = 40 : i64
+util.global public @v_initialized_const2 = 40 : i64
+
+// CHECK: util.global public @v_initialized_const3 = dense<4> : tensor<4xi32>
+util.global public @v_initialized_const3 = dense<4> : tensor<4xi32>
+
+// -----
+
+// CHECK: util.global private @v_initialized initializer(@initializer) : tensor<4xi32>
+util.global private @v_initialized initializer(@initializer) : tensor<4xi32>
+func private @initializer() -> tensor<4xi32>
+
+// -----
+
+util.global private @v_loaded : tensor<4xi32>
+// CHECK-LABEL: @loaded
+func @loaded() {
+  // CHECK-NEXT: = util.global.load @v_loaded : tensor<4xi32>
+  %0 = util.global.load @v_loaded : tensor<4xi32>
+  return
+}
+
+// -----
+
+util.global private mutable @v_stored : tensor<4xi32>
+// CHECK-LABEL: @stored
+func @stored() {
+  // CHECK-NEXT: %[[VAL:.+]] = constant
+  %cst = constant dense<5> : tensor<4xi32>
+  // CHECK-NEXT: util.global.store %[[VAL]], @v_stored : tensor<4xi32>
+  util.global.store %cst, @v_stored : tensor<4xi32>
+  return
+}
+
+// -----
+
+util.global private @v_loaded : tensor<4xf32>
+// CHECK-LABEL: @loaded_indirect
+func @loaded_indirect() {
+  // CHECK-NEXT: %[[ADDR:.+]] = util.global.address @v_loaded
+  %0 = util.global.address @v_loaded : !util.ptr<tensor<4xf32>>
+  // CHECK-NEXT: = util.global.load.indirect %[[ADDR]]
+  %1 = util.global.load.indirect %0 : !util.ptr<tensor<4xf32>> -> tensor<4xf32>
+  return
+}
+
+// -----
+
+util.global private mutable @v_stored : tensor<4xf32>
+// CHECK-LABEL: @stored_indirect
+// CHECK-SAME: (%[[VALUE:.+]]: tensor<4xf32>)
+func @stored_indirect(%arg0: tensor<4xf32>) {
+  // CHECK-NEXT: %[[ADDR:.+]] = util.global.address @v_stored
+  %0 = util.global.address @v_stored : !util.ptr<tensor<4xf32>>
+  // CHECK-NEXT: util.global.store.indirect %[[VALUE]], %[[ADDR]]
+  util.global.store.indirect %arg0, %0 : tensor<4xf32> -> !util.ptr<tensor<4xf32>>
+  return
+}
diff --git a/iree/compiler/Dialect/Util/IR/test/do_not_optimize.mlir b/iree/compiler/Dialect/Util/IR/test/hint_folding.mlir
similarity index 100%
rename from iree/compiler/Dialect/Util/IR/test/do_not_optimize.mlir
rename to iree/compiler/Dialect/Util/IR/test/hint_folding.mlir
diff --git a/iree/compiler/Dialect/Util/IR/test/parse_print.mlir b/iree/compiler/Dialect/Util/IR/test/hint_ops.mlir
similarity index 100%
rename from iree/compiler/Dialect/Util/IR/test/parse_print.mlir
rename to iree/compiler/Dialect/Util/IR/test/hint_ops.mlir
diff --git a/iree/compiler/Dialect/Util/Transforms/BUILD b/iree/compiler/Dialect/Util/Transforms/BUILD
index 003e977..3a0193e 100644
--- a/iree/compiler/Dialect/Util/Transforms/BUILD
+++ b/iree/compiler/Dialect/Util/Transforms/BUILD
@@ -12,13 +12,18 @@
 
 cc_library(
     name = "Transforms",
-    srcs = ["DropCompilerHints.cpp"],
+    srcs = [
+        "DropCompilerHints.cpp",
+        "SimplifyGlobalAccesses.cpp",
+    ],
     hdrs = [
         "Passes.h",
     ],
     deps = [
         "//iree/compiler/Dialect/Util/IR",
+        "@llvm-project//llvm:Support",
         "@llvm-project//mlir:IR",
         "@llvm-project//mlir:Pass",
+        "@llvm-project//mlir:Support",
     ],
 )
diff --git a/iree/compiler/Dialect/Util/Transforms/CMakeLists.txt b/iree/compiler/Dialect/Util/Transforms/CMakeLists.txt
index 77359d3..345256d 100644
--- a/iree/compiler/Dialect/Util/Transforms/CMakeLists.txt
+++ b/iree/compiler/Dialect/Util/Transforms/CMakeLists.txt
@@ -17,9 +17,12 @@
     "Passes.h"
   SRCS
     "DropCompilerHints.cpp"
+    "SimplifyGlobalAccesses.cpp"
   DEPS
+    LLVMSupport
     MLIRIR
     MLIRPass
+    MLIRSupport
     iree::compiler::Dialect::Util::IR
   PUBLIC
 )
diff --git a/iree/compiler/Dialect/Util/Transforms/Passes.h b/iree/compiler/Dialect/Util/Transforms/Passes.h
index 5a06d8a..6685256 100644
--- a/iree/compiler/Dialect/Util/Transforms/Passes.h
+++ b/iree/compiler/Dialect/Util/Transforms/Passes.h
@@ -16,8 +16,13 @@
 
 std::unique_ptr<OperationPass<void>> createDropCompilerHintsPass();
 
+std::unique_ptr<OperationPass<mlir::FuncOp>> createSimplifyGlobalAccessesPass();
+
 // Register all Passes
-inline void registerTransformPasses() { createDropCompilerHintsPass(); }
+inline void registerTransformPasses() {
+  createDropCompilerHintsPass();
+  createSimplifyGlobalAccessesPass();
+}
 
 }  // namespace Util
 }  // namespace IREE
diff --git a/iree/compiler/Dialect/Flow/Transforms/SimplifyVariableAccesses.cpp b/iree/compiler/Dialect/Util/Transforms/SimplifyGlobalAccesses.cpp
similarity index 65%
rename from iree/compiler/Dialect/Flow/Transforms/SimplifyVariableAccesses.cpp
rename to iree/compiler/Dialect/Util/Transforms/SimplifyGlobalAccesses.cpp
index cf66266..65d569b 100644
--- a/iree/compiler/Dialect/Flow/Transforms/SimplifyVariableAccesses.cpp
+++ b/iree/compiler/Dialect/Util/Transforms/SimplifyGlobalAccesses.cpp
@@ -7,66 +7,66 @@
 #include <algorithm>
 #include <iterator>
 
-#include "iree/compiler/Dialect/Flow/IR/FlowDialect.h"
-#include "iree/compiler/Dialect/Flow/IR/FlowOps.h"
-#include "iree/compiler/Dialect/Flow/Transforms/PassDetail.h"
-#include "iree/compiler/Dialect/Flow/Transforms/Passes.h"
+#include "iree/compiler/Dialect/Util/IR/UtilDialect.h"
+#include "iree/compiler/Dialect/Util/IR/UtilOps.h"
+#include "iree/compiler/Dialect/Util/IR/UtilTraits.h"
+#include "iree/compiler/Dialect/Util/Transforms/Passes.h"
 #include "llvm/ADT/SmallVector.h"
 #include "llvm/Support/Debug.h"
 #include "mlir/Pass/Pass.h"
 #include "mlir/Pass/PassRegistry.h"
 
-#define DEBUG_TYPE "iree-flow-simplify-variable-accesses"
+#define DEBUG_TYPE "iree-util-simplify-global-accesses"
 
 namespace mlir {
 namespace iree_compiler {
 namespace IREE {
-namespace Flow {
+namespace Util {
 
-// Builds symbol ref set for all immutable variables in |moduleOp|.
-static DenseSet<StringRef> gatherImmutableVariables(mlir::ModuleOp moduleOp) {
+// Builds symbol ref set for all immutable globals in |moduleOp|.
+static DenseSet<StringRef> gatherImmutableGlobals(mlir::ModuleOp moduleOp) {
   DenseSet<StringRef> set;
-  for (auto variableOp : moduleOp.getOps<IREE::Flow::VariableOp>()) {
-    if (!variableOp.is_mutable()) {
-      set.insert(variableOp.sym_name());
+  for (auto globalOp : moduleOp.getOps<IREE::Util::GlobalOp>()) {
+    if (!globalOp.is_mutable()) {
+      set.insert(globalOp.sym_name());
     }
   }
   return set;
 }
 
-// Hoists all loads of immutable variables in |funcOp| to the entry block.
-// |immutableVariables| is used for lookups of which variables are immutable.
+// Hoists all loads of immutable globals in |funcOp| to the entry block.
+// |immutableGlobals| is used for lookups of which globals are immutable.
 static void hoistImmutableLoads(mlir::FuncOp funcOp,
-                                DenseSet<StringRef> &immutableVariables) {
+                                DenseSet<StringRef> &immutableGlobals) {
   // Since CSE of loads isn't a thing yet we perform a basic deduping here by
   // folding all subsequent loads into the first one found. This works only for
-  // immutable variables as otherwise we'd have to ensure stores and
+  // immutable globals as otherwise we'd have to ensure stores and
   // side-effects were properly observed.
   DenseMap<Attribute, Operation *> loadOps;
   auto *entryBlock = &funcOp.getBlocks().front();
   Operation *lastEntryOp = nullptr;
   SmallVector<std::pair<Operation *, Operation *>> opReplacements;
   for (auto &block : funcOp) {
-    auto ops = llvm::to_vector<8>(block.getOps<IREE::Flow::VariableLoadOp>());
+    auto ops = llvm::to_vector<8>(block.getOps<IREE::Util::GlobalLoadOp>());
     for (auto &op : ops) {
-      if (!immutableVariables.contains(op.variable())) continue;
-      auto variableRef = op.variableAttr().cast<Attribute>();
-      auto it = loadOps.find(variableRef);
+      if (!immutableGlobals.contains(op.global())) continue;
+      auto globalRef = op.globalAttr().cast<Attribute>();
+      auto it = loadOps.find(globalRef);
       if (it == loadOps.end()) {
         // Move to entry block; even if it's already there (so loads are
         // hoisted at the same time).
-        LLVM_DEBUG(llvm::dbgs() << "moving immutable variable " << op.variable()
+        LLVM_DEBUG(llvm::dbgs() << "moving immutable global " << op.global()
                                 << " load to the entry block\n");
         if (lastEntryOp) {
           op->moveAfter(lastEntryOp);
         } else {
           op->moveBefore(entryBlock, entryBlock->begin());
         }
-        loadOps[variableRef] = op;
+        loadOps[globalRef] = op;
         lastEntryOp = op;
       } else {
         LLVM_DEBUG(llvm::dbgs()
-                   << "CSE'ing immutable variable " << op.variable() << "\n");
+                   << "CSE'ing immutable global " << op.global() << "\n");
         opReplacements.push_back({op, it->getSecond()});
       }
     }
@@ -107,9 +107,9 @@
     for (int i = ops.size() - 1; i >= 1; --i) {
       auto previous = ops[i - 1];
       auto current = ops[i];
-      if (isa<IREE::Flow::VariableStoreOp>(previous) &&
-          isa<IREE::Flow::VariableLoadOp>(current)) {
-        // RAW - forward the stored variable to the following use.
+      if (isa<IREE::Util::GlobalStoreOp>(previous) &&
+          isa<IREE::Util::GlobalLoadOp>(current)) {
+        // RAW - forward the stored global to the following use.
         auto storedValue = previous->getOperand(0);
         LLVM_DEBUG({
           llvm::dbgs() << "RAW: replacing load with previous store value:\n";
@@ -121,9 +121,9 @@
         ops.erase(ops.begin() + i);
         current->erase();
         didRemoveAny = true;
-      } else if (isa<IREE::Flow::VariableLoadOp>(previous) &&
-                 isa<IREE::Flow::VariableLoadOp>(current)) {
-        // RAR - forward the loaded variable to the following use.
+      } else if (isa<IREE::Util::GlobalLoadOp>(previous) &&
+                 isa<IREE::Util::GlobalLoadOp>(current)) {
+        // RAR - forward the loaded global to the following use.
         LLVM_DEBUG({
           llvm::dbgs() << "RAR: replacing subsequent load with op:\n";
           current->dump();
@@ -134,8 +134,8 @@
         ops.erase(ops.begin() + i);
         current->erase();
         didRemoveAny = true;
-      } else if (isa<IREE::Flow::VariableStoreOp>(previous) &&
-                 isa<IREE::Flow::VariableStoreOp>(current)) {
+      } else if (isa<IREE::Util::GlobalStoreOp>(previous) &&
+                 isa<IREE::Util::GlobalStoreOp>(current)) {
         // WAW - remove the first store.
         LLVM_DEBUG({
           llvm::dbgs() << "WAW: erasing source op:\n";
@@ -150,16 +150,16 @@
     }
     if (ops.empty()) continue;
 
-    if (auto loadOp = dyn_cast<IREE::Flow::VariableLoadOp>(ops.front())) {
+    if (auto loadOp = dyn_cast<IREE::Util::GlobalLoadOp>(ops.front())) {
       // If the head op is a load we can move that to the top of the block.
-      LLVM_DEBUG(llvm::dbgs() << "moving mutable variable " << loadOp.variable()
+      LLVM_DEBUG(llvm::dbgs() << "moving mutable global " << loadOp.global()
                               << " load upward\n");
       moveOpUpInBlock(block, ops.front());
     }
-    if (auto storeOp = dyn_cast<IREE::Flow::VariableStoreOp>(ops.back())) {
+    if (auto storeOp = dyn_cast<IREE::Util::GlobalStoreOp>(ops.back())) {
       // If the tail op is a store we can move that to the bottom of the block.
-      LLVM_DEBUG(llvm::dbgs() << "moving mutable variable "
-                              << storeOp.variable() << " store downward\n");
+      LLVM_DEBUG(llvm::dbgs() << "moving mutable global " << storeOp.global()
+                              << " store downward\n");
       moveOpDownInBlock(block, ops.back());
     }
   }
@@ -167,7 +167,7 @@
 }
 
 // Hoists loads and sinks stores to the boundary of |block| when safe.
-// |immutableVariables| is used for lookups of which variables are immutable.
+// |immutableGlobals| is used for lookups of which globals are immutable.
 //
 // Basic algorithm (repeat until no op removals):
 //   for each op:
@@ -185,26 +185,26 @@
 //     if (tail == store) move store to back
 //
 // Returns true if there were any removals and the block should be reprocessed.
-static bool rearrangeBlockVariableAccesses(
-    Block &block, DenseSet<StringRef> &immutableVariables) {
+static bool rearrangeBlockGlobalAccesses(
+    Block &block, DenseSet<StringRef> &immutableGlobals) {
   // Gather sequences of operations that are safe to reorder.
   // Certain ops - like calls/do_not_optimize/etc - prevent us from moving any
-  // variable operations across them.
+  // global operations across them.
   //
   // From each sequence we produce [symbol_name, [op, op, op, ...]] buckets.
   // NOTE: we use a map here so that we are deterministically ordered. This may
-  // not be needed but the variable count is low and it's nice to not care about
+  // not be needed but the global count is low and it's nice to not care about
   // op order issues.
   SmallVector<std::map<StringRef, SmallVector<Operation *>>> sequencedBuckets;
   sequencedBuckets.push_back({});  // Start in a sequence.
   block.walk([&](Operation *op) {
     auto &buckets = sequencedBuckets.back();
-    if (auto loadOp = dyn_cast<IREE::Flow::VariableLoadOp>(op)) {
-      if (!immutableVariables.contains(loadOp.variable())) {
-        buckets[loadOp.variable()].push_back(op);
+    if (auto loadOp = dyn_cast<IREE::Util::GlobalLoadOp>(op)) {
+      if (!immutableGlobals.contains(loadOp.global())) {
+        buckets[loadOp.global()].push_back(op);
       }
-    } else if (auto storeOp = dyn_cast<IREE::Flow::VariableStoreOp>(op)) {
-      buckets[storeOp.variable()].push_back(op);
+    } else if (auto storeOp = dyn_cast<IREE::Util::GlobalStoreOp>(op)) {
+      buckets[storeOp.global()].push_back(op);
     } else if (doesOpBlockMotion(op)) {
       // Split point - all accesses after this point must not assume anything
       // about accesses before it.
@@ -222,9 +222,19 @@
 
 namespace {
 
-class SimplifyVariableAccessesPass
-    : public SimplifyVariableAccessesBase<SimplifyVariableAccessesPass> {
+class SimplifyGlobalAccessesPass
+    : public PassWrapper<SimplifyGlobalAccessesPass,
+                         OperationPass<mlir::FuncOp>> {
  public:
+  StringRef getArgument() const override {
+    return "iree-util-simplify-global-accesses";
+  }
+
+  StringRef getDescription() const override {
+    return "Hoists loads and sinks stores to variables to decrease data "
+           "dependency regions.";
+  }
+
   void runOnOperation() override {
     auto funcOp = getOperation();
     if (funcOp.empty()) return;
@@ -232,22 +242,22 @@
     auto moduleOp = funcOp->getParentOfType<mlir::ModuleOp>();
     assert(moduleOp && "func not in a module");
 
-    // Build a set of all immutable variables for fast lookup.
-    auto immutableVariables = gatherImmutableVariables(moduleOp);
+    // Build a set of all immutable globals for fast lookup.
+    auto immutableGlobals = gatherImmutableGlobals(moduleOp);
 
-    // Hoist immutable variables first. These have no hazards and don't care
+    // Hoist immutable globals first. These have no hazards and don't care
     // about control flow - like `constant` - so getting them handled first
     // avoids the need for us to do the full analysis.
-    hoistImmutableLoads(funcOp, immutableVariables);
+    hoistImmutableLoads(funcOp, immutableGlobals);
 
     // We can't optimize the function if there are indirect loads/stores.
     // Note that constant loads are still ok above.
     for (auto &block : funcOp) {
       for (auto &op : block) {
-        if (isa<IREE::Flow::VariableLoadIndirectOp>(op) ||
-            isa<IREE::Flow::VariableStoreIndirectOp>(op)) {
+        if (isa<IREE::Util::GlobalLoadIndirectOp>(op) ||
+            isa<IREE::Util::GlobalStoreIndirectOp>(op)) {
           LLVM_DEBUG(llvm::dbgs()
-                     << "bailing on variable access simplification: indirect "
+                     << "bailing on global access simplification: indirect "
                         "accesses present in function\n");
           return;
         }
@@ -259,7 +269,7 @@
     // real compiler engineer sees this they'll be inspired to do this properly.
     for (auto &block : funcOp) {
       LLVM_DEBUG(llvm::dbgs() << "==== REARRANGING BLOCK ACCESSES ====\n");
-      while (rearrangeBlockVariableAccesses(block, immutableVariables)) {
+      while (rearrangeBlockGlobalAccesses(block, immutableGlobals)) {
         // NOTE: block is processed until no more ops are removed. Will always
         // end in a fixed amount of time as ops are only removed from the block.
       }
@@ -270,11 +280,13 @@
 }  // namespace
 
 std::unique_ptr<OperationPass<mlir::FuncOp>>
-createSimplifyVariableAccessesPass() {
-  return std::make_unique<SimplifyVariableAccessesPass>();
+createSimplifyGlobalAccessesPass() {
+  return std::make_unique<SimplifyGlobalAccessesPass>();
 }
 
-}  // namespace Flow
+static PassRegistration<SimplifyGlobalAccessesPass> pass;
+
+}  // namespace Util
 }  // namespace IREE
 }  // namespace iree_compiler
 }  // namespace mlir
diff --git a/iree/compiler/Dialect/Util/Transforms/test/BUILD b/iree/compiler/Dialect/Util/Transforms/test/BUILD
index 3c1bc8d..930c82c 100644
--- a/iree/compiler/Dialect/Util/Transforms/test/BUILD
+++ b/iree/compiler/Dialect/Util/Transforms/test/BUILD
@@ -16,7 +16,10 @@
 iree_lit_test_suite(
     name = "lit",
     srcs = enforce_glob(
-        ["drop_compiler_hints.mlir"],
+        [
+            "drop_compiler_hints.mlir",
+            "simplify_global_accesses.mlir",
+        ],
         include = ["*.mlir"],
     ),
     data = [
diff --git a/iree/compiler/Dialect/Util/Transforms/test/CMakeLists.txt b/iree/compiler/Dialect/Util/Transforms/test/CMakeLists.txt
index 4da7fa0..0a49eda 100644
--- a/iree/compiler/Dialect/Util/Transforms/test/CMakeLists.txt
+++ b/iree/compiler/Dialect/Util/Transforms/test/CMakeLists.txt
@@ -15,6 +15,7 @@
     lit
   SRCS
     "drop_compiler_hints.mlir"
+    "simplify_global_accesses.mlir"
   DATA
     iree::tools::IreeFileCheck
     iree::tools::iree-opt
diff --git a/iree/compiler/Dialect/Util/Transforms/test/simplify_global_accesses.mlir b/iree/compiler/Dialect/Util/Transforms/test/simplify_global_accesses.mlir
new file mode 100644
index 0000000..2b9c3a9
--- /dev/null
+++ b/iree/compiler/Dialect/Util/Transforms/test/simplify_global_accesses.mlir
@@ -0,0 +1,136 @@
+// RUN: iree-opt -split-input-file -iree-util-simplify-global-accesses %s | IreeFileCheck %s
+
+util.global private @varA = dense<1> : tensor<2xi32>
+util.global private @varB = dense<3> : tensor<2x4xi32>
+
+// CHECK-LABEL: @constants()
+func @constants() {
+  // CHECK-NEXT: %[[VAR_A:.+]] = util.global.load @varA : tensor<2xi32>
+  // CHECK-NEXT: %[[VAR_B:.+]] = util.global.load @varB : tensor<2x4xi32>
+  // CHECK-NEXT: constant 10
+  %w = constant 10 : index
+  %varA = util.global.load @varA : tensor<2xi32>
+  // CHECK-NEXT: %[[T:.+]] = flow.dispatch @ex::@dispatch0{{.+}}(%[[VAR_A]])
+  %d0 = flow.dispatch @ex::@dispatch0[%w](%varA) : (tensor<2xi32>) -> tensor<2xi32>
+  %varB = util.global.load @varB : tensor<2x4xi32>
+  // CHECK-NEXT: flow.dispatch @ex::@dispatch1{{.+}}(%[[T]], %[[VAR_B]])
+  %d1 = flow.dispatch @ex::@dispatch1[%w](%d0, %varB) : (tensor<2xi32>, tensor<2x4xi32>) -> tensor<2xi32>
+  return
+}
+
+// -----
+
+util.global private @varA = 1 : i32
+util.global private @varB = 2 : i32
+
+// CHECK-LABEL: @constants_in_cfg
+func @constants_in_cfg(%start: i32, %bound: i32) -> i32 {
+  // CHECK-NEXT: %[[VAR_A:.+]] = util.global.load @varA : i32
+  // CHECK-NEXT: %[[VAR_B:.+]] = util.global.load @varB : i32
+  // CHECK-NEXT: br ^bb1
+  br ^bb1(%start : i32)
+// CHECK: ^bb1(%[[BB1_ARG:.+]]: i32):
+^bb1(%2: i32):
+  %cmp = cmpi slt, %2, %bound : i32
+  cond_br %cmp, ^bb2(%2 : i32), ^bb3(%2 : i32)
+// CHECK: ^bb2(%[[BB2_ARG:.+]]: i32):
+^bb2(%5: i32):
+  %6 = util.global.load @varA : i32
+  // CHECK-NEXT: = addi %[[BB2_ARG]], %[[VAR_A]] : i32
+  %7 = addi %5, %6 : i32
+  br ^bb1(%7 : i32)
+// CHECK: ^bb3(%[[BB3_ARG:.+]]: i32):
+^bb3(%8: i32):
+  %9 = util.global.load @varA : i32
+  // CHECK-NEXT: %[[T0:.+]] = muli %[[BB3_ARG]], %[[VAR_A]] : i32
+  %10 = muli %8, %9 : i32
+  %11 = util.global.load @varB : i32
+  // CHECK-NEXT: %[[T1:.+]] = subi %[[T0]], %[[VAR_B]]
+  %12 = subi %10, %11 : i32
+  // CHECK-NEXT: return %[[T1]]
+  return %12 : i32
+}
+
+// -----
+
+util.global private mutable @varA = dense<1> : tensor<2xi32>
+util.global private @varB = dense<3> : tensor<2x4xi32>
+
+// CHECK-LABEL: @mixed_mutability
+func @mixed_mutability() {
+  // CHECK-DAG: %[[VAR_A:.+]] = util.global.load @varA : tensor<2xi32>
+  // CHECK-DAG: %[[VAR_B:.+]] = util.global.load @varB : tensor<2x4xi32>
+  // CHECK-NEXT: constant 10
+  %w = constant 10 : index
+  %varA = util.global.load @varA : tensor<2xi32>
+  // CHECK-NEXT: %[[T0:.+]] = flow.dispatch @ex::@dispatch0{{.+}}(%[[VAR_A]])
+  %d0 = flow.dispatch @ex::@dispatch0[%w](%varA) : (tensor<2xi32>) -> tensor<2xi32>
+  %varB = util.global.load @varB : tensor<2x4xi32>
+  // CHECK-NEXT: %[[T1:.+]] = flow.dispatch @ex::@dispatch1{{.+}}(%[[T0]], %[[VAR_B]])
+  %d1 = flow.dispatch @ex::@dispatch1[%w](%d0, %varB) : (tensor<2xi32>, tensor<2x4xi32>) -> tensor<2xi32>
+  // CHECK-NEXT: util.global.store %[[T1]], @varA : tensor<2xi32>
+  util.global.store %d1, @varA : tensor<2xi32>
+  return
+}
+
+// -----
+
+util.global private mutable @varA = dense<1> : tensor<2xi32>
+
+// CHECK-LABEL: @raw
+func @raw() {
+  // CHECK: %[[T:.+]] = util.global.load @varA {id = 0
+  %varA_0 = util.global.load @varA {id = 0} : tensor<2xi32>
+  util.global.store %varA_0, @varA {id = 0} : tensor<2xi32>
+  %varA_1 = util.global.load @varA {id = 1} : tensor<2xi32>
+  // CHECK-NEXT: util.global.store %[[T]], @varA {id = 1
+  util.global.store %varA_1, @varA {id = 1} : tensor<2xi32>
+  return
+}
+
+// -----
+
+util.global private mutable @varA = dense<1> : tensor<2xi32>
+
+// CHECK-LABEL: @rar
+func @rar() -> (tensor<2xi32>, tensor<2xi32>) {
+  // CHECK: %[[T:.+]] = util.global.load @varA {id = 0
+  %varA_0 = util.global.load @varA {id = 0} : tensor<2xi32>
+  %varA_1 = util.global.load @varA {id = 1} : tensor<2xi32>
+  // CHECK-NEXT: return %[[T]], %[[T]]
+  return %varA_0, %varA_1 : tensor<2xi32>, tensor<2xi32>
+}
+
+// -----
+
+util.global private mutable @varA = dense<1> : tensor<2xi32>
+
+// CHECK-LABEL: @waw
+// CHECK-SAME: (%[[ARG0:.+]]: tensor<2xi32>, %[[ARG1:.+]]: tensor<2xi32>)
+func @waw(%varA_0: tensor<2xi32>, %varA_1: tensor<2xi32>) {
+  util.global.store %varA_0, @varA : tensor<2xi32>
+  // CHECK-NEXT: util.global.store %[[ARG1]], @varA
+  util.global.store %varA_1, @varA : tensor<2xi32>
+  return
+}
+
+// -----
+
+util.global private mutable @varA = dense<1> : tensor<2xi32>
+
+// CHECK-LABEL: @side_effects(
+func @side_effects() {
+  // CHECK-NEXT: %[[T0:.+]] = util.global.load @varA
+  %varA_0 = util.global.load @varA : tensor<2xi32>
+  // CHECK-NEXT: util.global.store %[[T0]], @varA
+  util.global.store %varA_0, @varA : tensor<2xi32>
+  // CHECK-NEXT: call @other_fn()
+  call @other_fn() : () -> ()
+  // CHECK-NEXT: %[[T1:.+]] = util.global.load @varA
+  %varA_1 = util.global.load @varA : tensor<2xi32>
+  // CHECK-NEXT: util.global.store %[[T1]], @varA
+  util.global.store %varA_1, @varA : tensor<2xi32>
+  return
+}
+
+func private @other_fn()
diff --git a/iree/compiler/Dialect/VM/Analysis/ValueLiveness.cpp b/iree/compiler/Dialect/VM/Analysis/ValueLiveness.cpp
index f94ac9f..c716d57 100644
--- a/iree/compiler/Dialect/VM/Analysis/ValueLiveness.cpp
+++ b/iree/compiler/Dialect/VM/Analysis/ValueLiveness.cpp
@@ -264,6 +264,7 @@
       Operation *lastUse = &block.front();
       for (auto &use : value.getUses()) {
         if (use.getOwner()->getBlock() != &block) continue;
+        if (lastUse == use.getOwner()) continue;
         if (lastUse->isBeforeInBlock(use.getOwner())) {
           lastUse = use.getOwner();
         }
diff --git a/iree/compiler/Dialect/VM/Conversion/IREEToVM/BUILD b/iree/compiler/Dialect/VM/Conversion/UtilToVM/BUILD
similarity index 83%
rename from iree/compiler/Dialect/VM/Conversion/IREEToVM/BUILD
rename to iree/compiler/Dialect/VM/Conversion/UtilToVM/BUILD
index 0d9f803..d9b05b8 100644
--- a/iree/compiler/Dialect/VM/Conversion/IREEToVM/BUILD
+++ b/iree/compiler/Dialect/VM/Conversion/UtilToVM/BUILD
@@ -11,12 +11,14 @@
 )
 
 cc_library(
-    name = "IREEToVM",
+    name = "UtilToVM",
     srcs = [
-        "ConvertIREEToVM.cpp",
+        "ConvertGlobalOps.cpp",
+        "ConvertListOps.cpp",
+        "ConvertUtilToVM.cpp",
     ],
     hdrs = [
-        "ConvertIREEToVM.h",
+        "ConvertUtilToVM.h",
     ],
     deps = [
         "//iree/compiler/Dialect/Util/IR",
diff --git a/iree/compiler/Dialect/VM/Conversion/IREEToVM/CMakeLists.txt b/iree/compiler/Dialect/VM/Conversion/UtilToVM/CMakeLists.txt
similarity index 84%
rename from iree/compiler/Dialect/VM/Conversion/IREEToVM/CMakeLists.txt
rename to iree/compiler/Dialect/VM/Conversion/UtilToVM/CMakeLists.txt
index 075541c..b9946b7 100644
--- a/iree/compiler/Dialect/VM/Conversion/IREEToVM/CMakeLists.txt
+++ b/iree/compiler/Dialect/VM/Conversion/UtilToVM/CMakeLists.txt
@@ -1,6 +1,6 @@
 ################################################################################
 # Autogenerated by build_tools/bazel_to_cmake/bazel_to_cmake.py from           #
-# iree/compiler/Dialect/VM/Conversion/IREEToVM/BUILD                           #
+# iree/compiler/Dialect/VM/Conversion/UtilToVM/BUILD                           #
 #                                                                              #
 # Use iree_cmake_extra_content from iree/build_defs.oss.bzl to add arbitrary   #
 # CMake-only content.                                                          #
@@ -12,11 +12,13 @@
 
 iree_cc_library(
   NAME
-    IREEToVM
+    UtilToVM
   HDRS
-    "ConvertIREEToVM.h"
+    "ConvertUtilToVM.h"
   SRCS
-    "ConvertIREEToVM.cpp"
+    "ConvertGlobalOps.cpp"
+    "ConvertListOps.cpp"
+    "ConvertUtilToVM.cpp"
   DEPS
     MLIRIR
     MLIRPass
diff --git a/iree/compiler/Dialect/HAL/Conversion/HALToVM/ConvertVariableOps.cpp b/iree/compiler/Dialect/VM/Conversion/UtilToVM/ConvertGlobalOps.cpp
similarity index 69%
rename from iree/compiler/Dialect/HAL/Conversion/HALToVM/ConvertVariableOps.cpp
rename to iree/compiler/Dialect/VM/Conversion/UtilToVM/ConvertGlobalOps.cpp
index 4164f82..d967703 100644
--- a/iree/compiler/Dialect/HAL/Conversion/HALToVM/ConvertVariableOps.cpp
+++ b/iree/compiler/Dialect/VM/Conversion/UtilToVM/ConvertGlobalOps.cpp
@@ -4,23 +4,23 @@
 // See https://llvm.org/LICENSE.txt for license information.
 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
 
-#include "iree/compiler/Dialect/HAL/IR/HALOps.h"
-#include "iree/compiler/Dialect/HAL/IR/HALTypes.h"
+#include "iree/compiler/Dialect/Util/IR/UtilOps.h"
 #include "iree/compiler/Dialect/Util/IR/UtilTypes.h"
 #include "iree/compiler/Dialect/VM/IR/VMOps.h"
+#include "iree/compiler/Dialect/VM/IR/VMTypes.h"
 #include "mlir/Transforms/DialectConversion.h"
 
 namespace mlir {
 namespace iree_compiler {
 namespace {
 
-class VariableOpConversion : public OpConversionPattern<IREE::HAL::VariableOp> {
+class GlobalOpConversion : public OpConversionPattern<IREE::Util::GlobalOp> {
  public:
-  VariableOpConversion(MLIRContext *context, TypeConverter &typeConverter)
+  GlobalOpConversion(MLIRContext *context, TypeConverter &typeConverter)
       : OpConversionPattern(context), typeConverter(typeConverter) {}
 
   LogicalResult matchAndRewrite(
-      IREE::HAL::VariableOp op, llvm::ArrayRef<Value> operands,
+      IREE::Util::GlobalOp op, llvm::ArrayRef<Value> operands,
       ConversionPatternRewriter &rewriter) const override {
     auto convertedType = typeConverter.convertType(op.type());
     if (convertedType.isa<IREE::VM::RefType>() ||
@@ -79,25 +79,24 @@
       newOp.setVisibility(op.getVisibility());
       return success();
     }
-    return op.emitOpError("unsupported variable type");
+    return op.emitOpError("unsupported global type");
   }
 
  private:
   TypeConverter &typeConverter;
 };
 
-class VariableAddressOpConversion
-    : public OpConversionPattern<IREE::HAL::VariableAddressOp> {
+class GlobalAddressOpConversion
+    : public OpConversionPattern<IREE::Util::GlobalAddressOp> {
  public:
-  VariableAddressOpConversion(MLIRContext *context,
-                              TypeConverter &typeConverter)
+  GlobalAddressOpConversion(MLIRContext *context, TypeConverter &typeConverter)
       : OpConversionPattern(context), typeConverter(typeConverter) {}
 
   LogicalResult matchAndRewrite(
-      IREE::HAL::VariableAddressOp op, llvm::ArrayRef<Value> operands,
+      IREE::Util::GlobalAddressOp op, llvm::ArrayRef<Value> operands,
       ConversionPatternRewriter &rewriter) const override {
     rewriter.replaceOpWithNewOp<IREE::VM::GlobalAddressOp>(
-        op, typeConverter.convertType(op.getType()), op.variable());
+        op, typeConverter.convertType(op.getType()), op.global());
     return success();
   }
 
@@ -105,34 +104,34 @@
   TypeConverter &typeConverter;
 };
 
-class VariableLoadOpConversion
-    : public OpConversionPattern<IREE::HAL::VariableLoadOp> {
+class GlobalLoadOpConversion
+    : public OpConversionPattern<IREE::Util::GlobalLoadOp> {
  public:
-  VariableLoadOpConversion(MLIRContext *context, TypeConverter &typeConverter)
+  GlobalLoadOpConversion(MLIRContext *context, TypeConverter &typeConverter)
       : OpConversionPattern(context), typeConverter(typeConverter) {}
 
   LogicalResult matchAndRewrite(
-      IREE::HAL::VariableLoadOp op, llvm::ArrayRef<Value> operands,
+      IREE::Util::GlobalLoadOp op, llvm::ArrayRef<Value> operands,
       ConversionPatternRewriter &rewriter) const override {
     auto operandType = op.getType();
     auto convertedType = typeConverter.convertType(operandType);
     if (IREE::VM::RefType::isCompatible(operandType)) {
       rewriter.replaceOpWithNewOp<IREE::VM::GlobalLoadRefOp>(op, convertedType,
-                                                             op.variable());
+                                                             op.global());
     } else if (convertedType.isInteger(32)) {
       rewriter.replaceOpWithNewOp<IREE::VM::GlobalLoadI32Op>(op, convertedType,
-                                                             op.variable());
+                                                             op.global());
     } else if (convertedType.isInteger(64)) {
       rewriter.replaceOpWithNewOp<IREE::VM::GlobalLoadI64Op>(op, convertedType,
-                                                             op.variable());
+                                                             op.global());
     } else if (convertedType.isF32()) {
       rewriter.replaceOpWithNewOp<IREE::VM::GlobalLoadF32Op>(op, convertedType,
-                                                             op.variable());
+                                                             op.global());
     } else if (convertedType.isF64()) {
       rewriter.replaceOpWithNewOp<IREE::VM::GlobalLoadF64Op>(op, convertedType,
-                                                             op.variable());
+                                                             op.global());
     } else {
-      return rewriter.notifyMatchFailure(op, "unhandled variable type");
+      return rewriter.notifyMatchFailure(op, "unhandled global type");
     }
     return success();
   }
@@ -141,35 +140,35 @@
   TypeConverter &typeConverter;
 };
 
-class VariableLoadIndirectOpConversion
-    : public OpConversionPattern<IREE::HAL::VariableLoadIndirectOp> {
+class GlobalLoadIndirectOpConversion
+    : public OpConversionPattern<IREE::Util::GlobalLoadIndirectOp> {
  public:
-  VariableLoadIndirectOpConversion(MLIRContext *context,
-                                   TypeConverter &typeConverter)
+  GlobalLoadIndirectOpConversion(MLIRContext *context,
+                                 TypeConverter &typeConverter)
       : OpConversionPattern(context), typeConverter(typeConverter) {}
 
   LogicalResult matchAndRewrite(
-      IREE::HAL::VariableLoadIndirectOp op, llvm::ArrayRef<Value> operands,
+      IREE::Util::GlobalLoadIndirectOp op, llvm::ArrayRef<Value> operands,
       ConversionPatternRewriter &rewriter) const override {
     auto operandType = op.getType();
     auto convertedType = typeConverter.convertType(operandType);
     if (IREE::VM::RefType::isCompatible(operandType)) {
       rewriter.replaceOpWithNewOp<IREE::VM::GlobalLoadIndirectRefOp>(
-          op, convertedType, op.variable());
+          op, convertedType, op.global());
     } else if (convertedType.isInteger(32)) {
       rewriter.replaceOpWithNewOp<IREE::VM::GlobalLoadIndirectI32Op>(
-          op, convertedType, op.variable());
+          op, convertedType, op.global());
     } else if (convertedType.isInteger(64)) {
       rewriter.replaceOpWithNewOp<IREE::VM::GlobalLoadIndirectI64Op>(
-          op, convertedType, op.variable());
+          op, convertedType, op.global());
     } else if (convertedType.isF32()) {
       rewriter.replaceOpWithNewOp<IREE::VM::GlobalLoadIndirectF32Op>(
-          op, convertedType, op.variable());
+          op, convertedType, op.global());
     } else if (convertedType.isF64()) {
       rewriter.replaceOpWithNewOp<IREE::VM::GlobalLoadIndirectF64Op>(
-          op, convertedType, op.variable());
+          op, convertedType, op.global());
     } else {
-      return rewriter.notifyMatchFailure(op, "unhandled variable type");
+      return rewriter.notifyMatchFailure(op, "unhandled global type");
     }
     return success();
   }
@@ -178,68 +177,68 @@
   TypeConverter &typeConverter;
 };
 
-class VariableStoreOpConversion
-    : public OpConversionPattern<IREE::HAL::VariableStoreOp> {
+class GlobalStoreOpConversion
+    : public OpConversionPattern<IREE::Util::GlobalStoreOp> {
  public:
-  VariableStoreOpConversion(MLIRContext *context, TypeConverter &typeConverter)
+  GlobalStoreOpConversion(MLIRContext *context, TypeConverter &typeConverter)
       : OpConversionPattern(context) {}
 
   LogicalResult matchAndRewrite(
-      IREE::HAL::VariableStoreOp op, llvm::ArrayRef<Value> newOperands,
+      IREE::Util::GlobalStoreOp op, llvm::ArrayRef<Value> newOperands,
       ConversionPatternRewriter &rewriter) const override {
-    IREE::HAL::VariableStoreOp::Adaptor operands(newOperands);
+    IREE::Util::GlobalStoreOp::Adaptor operands(newOperands);
     auto operandType = operands.value().getType();
     if (operandType.isa<IREE::VM::RefType>()) {
       rewriter.replaceOpWithNewOp<IREE::VM::GlobalStoreRefOp>(
-          op, operands.value(), op.variable());
+          op, operands.value(), op.global());
     } else if (operandType.isInteger(32)) {
       rewriter.replaceOpWithNewOp<IREE::VM::GlobalStoreI32Op>(
-          op, operands.value(), op.variable());
+          op, operands.value(), op.global());
     } else if (operandType.isInteger(64)) {
       rewriter.replaceOpWithNewOp<IREE::VM::GlobalStoreI64Op>(
-          op, operands.value(), op.variable());
+          op, operands.value(), op.global());
     } else if (operandType.isF32()) {
       rewriter.replaceOpWithNewOp<IREE::VM::GlobalStoreF32Op>(
-          op, operands.value(), op.variable());
+          op, operands.value(), op.global());
     } else if (operandType.isF64()) {
       rewriter.replaceOpWithNewOp<IREE::VM::GlobalStoreF64Op>(
-          op, operands.value(), op.variable());
+          op, operands.value(), op.global());
     } else {
-      return rewriter.notifyMatchFailure(op, "unhandled variable type");
+      return rewriter.notifyMatchFailure(op, "unhandled global type");
     }
     return success();
   }
 };
 
-class VariableStoreIndirectOpConversion
-    : public OpConversionPattern<IREE::HAL::VariableStoreIndirectOp> {
+class GlobalStoreIndirectOpConversion
+    : public OpConversionPattern<IREE::Util::GlobalStoreIndirectOp> {
  public:
-  VariableStoreIndirectOpConversion(MLIRContext *context,
-                                    TypeConverter &typeConverter)
+  GlobalStoreIndirectOpConversion(MLIRContext *context,
+                                  TypeConverter &typeConverter)
       : OpConversionPattern(context) {}
 
   LogicalResult matchAndRewrite(
-      IREE::HAL::VariableStoreIndirectOp op, llvm::ArrayRef<Value> newOperands,
+      IREE::Util::GlobalStoreIndirectOp op, llvm::ArrayRef<Value> newOperands,
       ConversionPatternRewriter &rewriter) const override {
-    IREE::HAL::VariableStoreIndirectOp::Adaptor operands(newOperands);
+    IREE::Util::GlobalStoreIndirectOp::Adaptor operands(newOperands);
     auto operandType = operands.value().getType();
     if (operandType.isa<IREE::VM::RefType>()) {
       rewriter.replaceOpWithNewOp<IREE::VM::GlobalStoreIndirectRefOp>(
-          op, operands.value(), op.variable());
+          op, operands.value(), op.global());
     } else if (operandType.isInteger(32)) {
       rewriter.replaceOpWithNewOp<IREE::VM::GlobalStoreIndirectI32Op>(
-          op, operands.value(), op.variable());
+          op, operands.value(), op.global());
     } else if (operandType.isInteger(64)) {
       rewriter.replaceOpWithNewOp<IREE::VM::GlobalStoreIndirectI64Op>(
-          op, operands.value(), op.variable());
+          op, operands.value(), op.global());
     } else if (operandType.isF32()) {
       rewriter.replaceOpWithNewOp<IREE::VM::GlobalStoreIndirectF32Op>(
-          op, operands.value(), op.variable());
+          op, operands.value(), op.global());
     } else if (operandType.isF64()) {
       rewriter.replaceOpWithNewOp<IREE::VM::GlobalStoreIndirectF64Op>(
-          op, operands.value(), op.variable());
+          op, operands.value(), op.global());
     } else {
-      return rewriter.notifyMatchFailure(op, "unhandled variable type");
+      return rewriter.notifyMatchFailure(op, "unhandled global type");
     }
     return success();
   }
@@ -247,13 +246,17 @@
 
 }  // namespace
 
-void populateHALVariableToVMPatterns(MLIRContext *context,
-                                     SymbolTable &importSymbols,
-                                     TypeConverter &typeConverter,
-                                     OwningRewritePatternList &patterns) {
-  patterns.insert<VariableOpConversion, VariableAddressOpConversion,
-                  VariableLoadOpConversion, VariableLoadIndirectOpConversion,
-                  VariableStoreOpConversion, VariableStoreIndirectOpConversion>(
+void populateUtilGlobalToVMPatterns(MLIRContext *context,
+                                    ConversionTarget &conversionTarget,
+                                    TypeConverter &typeConverter,
+                                    OwningRewritePatternList &patterns) {
+  conversionTarget.addIllegalOp<
+      IREE::Util::GlobalOp, IREE::Util::GlobalAddressOp,
+      IREE::Util::GlobalLoadOp, IREE::Util::GlobalLoadIndirectOp,
+      IREE::Util::GlobalStoreOp, IREE::Util::GlobalStoreIndirectOp>();
+  patterns.insert<GlobalOpConversion, GlobalAddressOpConversion,
+                  GlobalLoadOpConversion, GlobalLoadIndirectOpConversion,
+                  GlobalStoreOpConversion, GlobalStoreIndirectOpConversion>(
       context, typeConverter);
 }
 
diff --git a/iree/compiler/Dialect/VM/Conversion/IREEToVM/ConvertIREEToVM.cpp b/iree/compiler/Dialect/VM/Conversion/UtilToVM/ConvertListOps.cpp
similarity index 65%
rename from iree/compiler/Dialect/VM/Conversion/IREEToVM/ConvertIREEToVM.cpp
rename to iree/compiler/Dialect/VM/Conversion/UtilToVM/ConvertListOps.cpp
index 97240aa..3c846ce 100644
--- a/iree/compiler/Dialect/VM/Conversion/IREEToVM/ConvertIREEToVM.cpp
+++ b/iree/compiler/Dialect/VM/Conversion/UtilToVM/ConvertListOps.cpp
@@ -4,11 +4,10 @@
 // See https://llvm.org/LICENSE.txt for license information.
 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
 
-#include "iree/compiler/Dialect/VM/Conversion/IREEToVM/ConvertIREEToVM.h"
-
 #include "iree/compiler/Dialect/Util/IR/UtilOps.h"
 #include "iree/compiler/Dialect/Util/IR/UtilTypes.h"
 #include "iree/compiler/Dialect/VM/Conversion/TypeConverter.h"
+#include "iree/compiler/Dialect/VM/Conversion/UtilToVM/ConvertUtilToVM.h"
 #include "iree/compiler/Dialect/VM/IR/VMOps.h"
 #include "mlir/Dialect/StandardOps/IR/Ops.h"
 #include "mlir/IR/Attributes.h"
@@ -21,67 +20,6 @@
 namespace iree_compiler {
 namespace {
 
-//===----------------------------------------------------------------------===//
-// util.null
-//===----------------------------------------------------------------------===//
-
-class NullOpConversion : public OpConversionPattern<IREE::Util::NullOp> {
-  using OpConversionPattern::OpConversionPattern;
-
-  LogicalResult matchAndRewrite(
-      IREE::Util::NullOp op, ArrayRef<Value> operands,
-      ConversionPatternRewriter &rewriter) const override {
-    rewriter.replaceOpWithNewOp<IREE::VM::ConstRefZeroOp>(
-        op, IREE::VM::RefType::get(op.getType()));
-    return success();
-  }
-};
-
-//===----------------------------------------------------------------------===//
-// util.byte_buffer.*
-//===----------------------------------------------------------------------===//
-
-class ByteBufferConstantOpConversion
-    : public OpConversionPattern<IREE::Util::ByteBufferConstantOp> {
-  using OpConversionPattern::OpConversionPattern;
-
-  LogicalResult matchAndRewrite(
-      IREE::Util::ByteBufferConstantOp op, ArrayRef<Value> operands,
-      ConversionPatternRewriter &rewriter) const override {
-    rewriter.replaceOpWithNewOp<IREE::VM::RodataInlineOp>(
-        op,
-        IREE::VM::RefType::get(
-            IREE::VM::BufferType::get(rewriter.getContext())),
-        op.value());
-    return success();
-  }
-};
-
-//===----------------------------------------------------------------------===//
-// Compiler hints
-//===----------------------------------------------------------------------===//
-
-class UnreachableOpConversion
-    : public OpConversionPattern<IREE::Util::UnreachableOp> {
-  using OpConversionPattern::OpConversionPattern;
-
-  LogicalResult matchAndRewrite(
-      IREE::Util::UnreachableOp srcOp, ArrayRef<Value> operands,
-      ConversionPatternRewriter &rewriter) const override {
-    rewriter.replaceOpWithNewOp<IREE::VM::FailOp>(
-        srcOp,
-        rewriter.createOrFold<IREE::VM::ConstI32Op>(
-            srcOp.getLoc(),
-            static_cast<int32_t>(IREE::Util::StatusCode::Unknown)),
-        srcOp.message());
-    return success();
-  }
-};
-
-//===----------------------------------------------------------------------===//
-// Lists
-//===----------------------------------------------------------------------===//
-
 class ListCreateOpConversion
     : public OpConversionPattern<IREE::Util::ListCreateOp> {
   using OpConversionPattern::OpConversionPattern;
@@ -183,24 +121,9 @@
 
 }  // namespace
 
-void populateIREEToVMPatterns(MLIRContext *context,
-                              TypeConverter &typeConverter,
-                              OwningRewritePatternList &patterns) {
-  patterns.insert<NullOpConversion>(typeConverter, context);
-  patterns.insert<ByteBufferConstantOpConversion>(typeConverter, context);
-  patterns.insert<UnreachableOpConversion>(typeConverter, context);
-
-  typeConverter.addConversion(
-      [](IREE::Util::ByteBufferType type) -> Optional<Type> {
-        return IREE::VM::RefType::get(
-            IREE::VM::BufferType::get(type.getContext()));
-      });
-  typeConverter.addConversion(
-      [](IREE::Util::MutableByteBufferType type) -> Optional<Type> {
-        return IREE::VM::RefType::get(
-            IREE::VM::BufferType::get(type.getContext()));
-      });
-
+void populateUtilListToVMPatterns(MLIRContext *context,
+                                  TypeConverter &typeConverter,
+                                  OwningRewritePatternList &patterns) {
   typeConverter.addConversion(
       [&typeConverter](IREE::Util::ListType type) -> Optional<Type> {
         Type elementType;
diff --git a/iree/compiler/Dialect/VM/Conversion/UtilToVM/ConvertUtilToVM.cpp b/iree/compiler/Dialect/VM/Conversion/UtilToVM/ConvertUtilToVM.cpp
new file mode 100644
index 0000000..d08e885
--- /dev/null
+++ b/iree/compiler/Dialect/VM/Conversion/UtilToVM/ConvertUtilToVM.cpp
@@ -0,0 +1,117 @@
+// Copyright 2019 The IREE Authors
+//
+// Licensed under the Apache License v2.0 with LLVM Exceptions.
+// See https://llvm.org/LICENSE.txt for license information.
+// SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
+
+#include "iree/compiler/Dialect/VM/Conversion/UtilToVM/ConvertUtilToVM.h"
+
+#include "iree/compiler/Dialect/Util/IR/UtilOps.h"
+#include "iree/compiler/Dialect/Util/IR/UtilTypes.h"
+#include "iree/compiler/Dialect/VM/Conversion/TypeConverter.h"
+#include "iree/compiler/Dialect/VM/IR/VMOps.h"
+#include "mlir/Dialect/StandardOps/IR/Ops.h"
+#include "mlir/IR/Attributes.h"
+#include "mlir/IR/Builders.h"
+#include "mlir/IR/BuiltinOps.h"
+#include "mlir/IR/Matchers.h"
+#include "mlir/Transforms/DialectConversion.h"
+
+namespace mlir {
+namespace iree_compiler {
+
+void populateUtilGlobalToVMPatterns(MLIRContext *context,
+                                    ConversionTarget &conversionTarget,
+                                    TypeConverter &typeConverter,
+                                    OwningRewritePatternList &patterns);
+void populateUtilListToVMPatterns(MLIRContext *context,
+                                  TypeConverter &typeConverter,
+                                  OwningRewritePatternList &patterns);
+
+namespace {
+
+//===----------------------------------------------------------------------===//
+// util.null
+//===----------------------------------------------------------------------===//
+
+class NullOpConversion : public OpConversionPattern<IREE::Util::NullOp> {
+  using OpConversionPattern::OpConversionPattern;
+
+  LogicalResult matchAndRewrite(
+      IREE::Util::NullOp op, ArrayRef<Value> operands,
+      ConversionPatternRewriter &rewriter) const override {
+    rewriter.replaceOpWithNewOp<IREE::VM::ConstRefZeroOp>(
+        op, IREE::VM::RefType::get(op.getType()));
+    return success();
+  }
+};
+
+//===----------------------------------------------------------------------===//
+// util.byte_buffer.*
+//===----------------------------------------------------------------------===//
+
+class ByteBufferConstantOpConversion
+    : public OpConversionPattern<IREE::Util::ByteBufferConstantOp> {
+  using OpConversionPattern::OpConversionPattern;
+
+  LogicalResult matchAndRewrite(
+      IREE::Util::ByteBufferConstantOp op, ArrayRef<Value> operands,
+      ConversionPatternRewriter &rewriter) const override {
+    rewriter.replaceOpWithNewOp<IREE::VM::RodataInlineOp>(
+        op,
+        IREE::VM::RefType::get(
+            IREE::VM::BufferType::get(rewriter.getContext())),
+        op.value());
+    return success();
+  }
+};
+
+//===----------------------------------------------------------------------===//
+// Compiler hints
+//===----------------------------------------------------------------------===//
+
+class UnreachableOpConversion
+    : public OpConversionPattern<IREE::Util::UnreachableOp> {
+  using OpConversionPattern::OpConversionPattern;
+
+  LogicalResult matchAndRewrite(
+      IREE::Util::UnreachableOp srcOp, ArrayRef<Value> operands,
+      ConversionPatternRewriter &rewriter) const override {
+    rewriter.replaceOpWithNewOp<IREE::VM::FailOp>(
+        srcOp,
+        rewriter.createOrFold<IREE::VM::ConstI32Op>(
+            srcOp.getLoc(),
+            static_cast<int32_t>(IREE::Util::StatusCode::Unknown)),
+        srcOp.message());
+    return success();
+  }
+};
+
+}  // namespace
+
+void populateUtilToVMPatterns(MLIRContext *context,
+                              ConversionTarget &conversionTarget,
+                              TypeConverter &typeConverter,
+                              OwningRewritePatternList &patterns) {
+  patterns.insert<NullOpConversion>(typeConverter, context);
+  patterns.insert<ByteBufferConstantOpConversion>(typeConverter, context);
+  patterns.insert<UnreachableOpConversion>(typeConverter, context);
+
+  typeConverter.addConversion(
+      [](IREE::Util::ByteBufferType type) -> Optional<Type> {
+        return IREE::VM::RefType::get(
+            IREE::VM::BufferType::get(type.getContext()));
+      });
+  typeConverter.addConversion(
+      [](IREE::Util::MutableByteBufferType type) -> Optional<Type> {
+        return IREE::VM::RefType::get(
+            IREE::VM::BufferType::get(type.getContext()));
+      });
+
+  populateUtilGlobalToVMPatterns(context, conversionTarget, typeConverter,
+                                 patterns);
+  populateUtilListToVMPatterns(context, typeConverter, patterns);
+}
+
+}  // namespace iree_compiler
+}  // namespace mlir
diff --git a/iree/compiler/Dialect/VM/Conversion/IREEToVM/ConvertIREEToVM.h b/iree/compiler/Dialect/VM/Conversion/UtilToVM/ConvertUtilToVM.h
similarity index 64%
rename from iree/compiler/Dialect/VM/Conversion/IREEToVM/ConvertIREEToVM.h
rename to iree/compiler/Dialect/VM/Conversion/UtilToVM/ConvertUtilToVM.h
index 2700e72..df82ffc 100644
--- a/iree/compiler/Dialect/VM/Conversion/IREEToVM/ConvertIREEToVM.h
+++ b/iree/compiler/Dialect/VM/Conversion/UtilToVM/ConvertUtilToVM.h
@@ -4,8 +4,8 @@
 // See https://llvm.org/LICENSE.txt for license information.
 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
 
-#ifndef IREE_COMPILER_DIALECT_VM_CONVERSION_IREETOVM_CONVERTIREETOVM_H_
-#define IREE_COMPILER_DIALECT_VM_CONVERSION_IREETOVM_CONVERTIREETOVM_H_
+#ifndef IREE_COMPILER_DIALECT_VM_CONVERSION_UTILTOVM_CONVERTUTILTOVM_H_
+#define IREE_COMPILER_DIALECT_VM_CONVERSION_UTILTOVM_CONVERTUTILTOVM_H_
 
 #include "mlir/IR/PatternMatch.h"
 #include "mlir/Transforms/DialectConversion.h"
@@ -14,11 +14,12 @@
 namespace iree_compiler {
 
 // Appends IREE special hint ops to VM dialect patterns.
-void populateIREEToVMPatterns(MLIRContext *context,
+void populateUtilToVMPatterns(MLIRContext *context,
+                              ConversionTarget &conversionTarget,
                               TypeConverter &typeConverter,
                               OwningRewritePatternList &patterns);
 
 }  // namespace iree_compiler
 }  // namespace mlir
 
-#endif  // IREE_COMPILER_DIALECT_VM_CONVERSION_IREETOVM_CONVERTIREETOVM_H_
+#endif  // IREE_COMPILER_DIALECT_VM_CONVERSION_UTILTOVM_CONVERTUTILTOVM_H_
diff --git a/iree/compiler/Dialect/VM/Conversion/IREEToVM/test/BUILD b/iree/compiler/Dialect/VM/Conversion/UtilToVM/test/BUILD
similarity index 95%
rename from iree/compiler/Dialect/VM/Conversion/IREEToVM/test/BUILD
rename to iree/compiler/Dialect/VM/Conversion/UtilToVM/test/BUILD
index 74ded09..38e1d21 100644
--- a/iree/compiler/Dialect/VM/Conversion/IREEToVM/test/BUILD
+++ b/iree/compiler/Dialect/VM/Conversion/UtilToVM/test/BUILD
@@ -18,6 +18,7 @@
     srcs = enforce_glob(
         [
             "byte_buffer_ops.mlir",
+            "global_ops.mlir",
             "hint_ops.mlir",
             "list_ops.mlir",
         ],
diff --git a/iree/compiler/Dialect/VM/Conversion/IREEToVM/test/CMakeLists.txt b/iree/compiler/Dialect/VM/Conversion/UtilToVM/test/CMakeLists.txt
similarity index 91%
rename from iree/compiler/Dialect/VM/Conversion/IREEToVM/test/CMakeLists.txt
rename to iree/compiler/Dialect/VM/Conversion/UtilToVM/test/CMakeLists.txt
index 4403530..56b0767 100644
--- a/iree/compiler/Dialect/VM/Conversion/IREEToVM/test/CMakeLists.txt
+++ b/iree/compiler/Dialect/VM/Conversion/UtilToVM/test/CMakeLists.txt
@@ -1,6 +1,6 @@
 ################################################################################
 # Autogenerated by build_tools/bazel_to_cmake/bazel_to_cmake.py from           #
-# iree/compiler/Dialect/VM/Conversion/IREEToVM/test/BUILD                      #
+# iree/compiler/Dialect/VM/Conversion/UtilToVM/test/BUILD                      #
 #                                                                              #
 # Use iree_cmake_extra_content from iree/build_defs.oss.bzl to add arbitrary   #
 # CMake-only content.                                                          #
@@ -15,6 +15,7 @@
     lit
   SRCS
     "byte_buffer_ops.mlir"
+    "global_ops.mlir"
     "hint_ops.mlir"
     "list_ops.mlir"
   DATA
diff --git a/iree/compiler/Dialect/VM/Conversion/IREEToVM/test/byte_buffer_ops.mlir b/iree/compiler/Dialect/VM/Conversion/UtilToVM/test/byte_buffer_ops.mlir
similarity index 100%
rename from iree/compiler/Dialect/VM/Conversion/IREEToVM/test/byte_buffer_ops.mlir
rename to iree/compiler/Dialect/VM/Conversion/UtilToVM/test/byte_buffer_ops.mlir
diff --git a/iree/compiler/Dialect/VM/Conversion/UtilToVM/test/global_ops.mlir b/iree/compiler/Dialect/VM/Conversion/UtilToVM/test/global_ops.mlir
new file mode 100644
index 0000000..fdc41b6
--- /dev/null
+++ b/iree/compiler/Dialect/VM/Conversion/UtilToVM/test/global_ops.mlir
@@ -0,0 +1,59 @@
+// RUN: iree-opt -split-input-file -iree-vm-conversion %s | IreeFileCheck %s
+
+// CHECK: vm.global.i32 public @v_initialized_const = 4 : i32
+util.global @v_initialized_const = 4 : i32
+
+// CHECK: vm.global.i32 private @v_private_const = 5 : i32
+util.global private @v_private_const = 5 : i32
+
+// -----
+
+// CHECK: vm.global.ref public @v_initialized initializer(@initializer) : !vm.ref<!hal.buffer>
+util.global public @v_initialized initializer(@initializer) : !hal.buffer
+func private @initializer() -> !hal.buffer
+
+// -----
+
+// CHECK: vm.global.ref public @v_loaded : !vm.ref<!hal.buffer>
+util.global public @v_loaded : !hal.buffer
+// CHECK-LABEL: vm.func private @loaded
+func @loaded() {
+  // CHECK: %v_loaded = vm.global.load.ref @v_loaded : !vm.ref<!hal.buffer>
+  %0 = util.global.load @v_loaded : !hal.buffer
+  return
+}
+
+// -----
+
+// CHECK: vm.global.ref public mutable @v_stored : !vm.ref<!hal.buffer>
+util.global public mutable @v_stored : !hal.buffer
+// CHECK-LABEL: vm.func private @stored
+func @stored(%arg0 : !hal.buffer) {
+  // CHECK: vm.global.store.ref %arg0, @v_stored : !vm.ref<!hal.buffer>
+  util.global.store %arg0, @v_stored : !hal.buffer
+  return
+}
+
+// -----
+
+util.global @v_loaded : !hal.buffer
+// CHECK-LABEL: @loaded_indirect
+func @loaded_indirect() -> !hal.buffer {
+  // CHECK-NEXT: %[[ADDR:.+]] = vm.global.address @v_loaded
+  %0 = util.global.address @v_loaded : !util.ptr<!hal.buffer>
+  // CHECK-NEXT: = vm.global.load.indirect.ref %[[ADDR]]
+  %1 = util.global.load.indirect %0 : !util.ptr<!hal.buffer> -> !hal.buffer
+  return %1 : !hal.buffer
+}
+
+// -----
+
+util.global mutable @v_stored : !hal.buffer
+// CHECK-LABEL: @stored_indirect
+func @stored_indirect(%arg0 : !hal.buffer) {
+  // CHECK-NEXT: %[[ADDR:.+]] = vm.global.address @v_stored
+  %0 = util.global.address @v_stored : !util.ptr<!hal.buffer>
+  // CHECK-NEXT: vm.global.store.indirect.ref %arg0, %[[ADDR]]
+  util.global.store.indirect %arg0, %0 : !hal.buffer -> !util.ptr<!hal.buffer>
+  return
+}
diff --git a/iree/compiler/Dialect/VM/Conversion/IREEToVM/test/hint_ops.mlir b/iree/compiler/Dialect/VM/Conversion/UtilToVM/test/hint_ops.mlir
similarity index 100%
rename from iree/compiler/Dialect/VM/Conversion/IREEToVM/test/hint_ops.mlir
rename to iree/compiler/Dialect/VM/Conversion/UtilToVM/test/hint_ops.mlir
diff --git a/iree/compiler/Dialect/VM/Conversion/IREEToVM/test/list_ops.mlir b/iree/compiler/Dialect/VM/Conversion/UtilToVM/test/list_ops.mlir
similarity index 100%
rename from iree/compiler/Dialect/VM/Conversion/IREEToVM/test/list_ops.mlir
rename to iree/compiler/Dialect/VM/Conversion/UtilToVM/test/list_ops.mlir
diff --git a/iree/compiler/Dialect/VM/Conversion/VMToEmitC/CMakeLists.txt b/iree/compiler/Dialect/VM/Conversion/VMToEmitC/CMakeLists.txt
index 759ecbc..32dde54 100644
--- a/iree/compiler/Dialect/VM/Conversion/VMToEmitC/CMakeLists.txt
+++ b/iree/compiler/Dialect/VM/Conversion/VMToEmitC/CMakeLists.txt
@@ -23,7 +23,7 @@
       MLIRPass
       MLIRStandard
       MLIRTransforms
-      iree::compiler::Dialect::Util::Conversion::PreserveCompilerHints
+      iree::compiler::Dialect::Util::Conversion
       iree::compiler::Dialect::Util::IR
       iree::compiler::Dialect::VM::Analysis
       iree::compiler::Dialect::VM::IR
diff --git a/iree/compiler/Dialect/VM/Conversion/VMToEmitC/ConvertVMToEmitC.cpp b/iree/compiler/Dialect/VM/Conversion/VMToEmitC/ConvertVMToEmitC.cpp
index 541e499..cad307f 100644
--- a/iree/compiler/Dialect/VM/Conversion/VMToEmitC/ConvertVMToEmitC.cpp
+++ b/iree/compiler/Dialect/VM/Conversion/VMToEmitC/ConvertVMToEmitC.cpp
@@ -6,7 +6,7 @@
 
 #include "iree/compiler/Dialect/VM/Conversion/VMToEmitC/ConvertVMToEmitC.h"
 
-#include "iree/compiler/Dialect/Util/Conversion/PreserveCompilerHints.h"
+#include "iree/compiler/Dialect/Util/Conversion/ConversionPatterns.h"
 #include "iree/compiler/Dialect/Util/IR/UtilDialect.h"
 #include "iree/compiler/Dialect/Util/IR/UtilOps.h"
 #include "iree/compiler/Dialect/VM/IR/VMOps.h"
@@ -1935,7 +1935,7 @@
                                IREE::VM::EmitCTypeConverter &typeConverter,
                                OwningRewritePatternList &patterns,
                                VMAnalysisCache &vmAnalysisCache) {
-  IREE::Util::populatePreserveCompilerHintsPatterns(context, patterns);
+  populateUtilConversionPatterns(context, typeConverter, patterns);
 
   // CFG
   patterns.insert<BranchOpConversion>(context);
diff --git a/iree/compiler/Dialect/VM/IR/VMOps.td b/iree/compiler/Dialect/VM/IR/VMOps.td
index 3dc94c2..6abda0c 100644
--- a/iree/compiler/Dialect/VM/IR/VMOps.td
+++ b/iree/compiler/Dialect/VM/IR/VMOps.td
@@ -269,7 +269,7 @@
     (`mutable` $is_mutable^)?
     $sym_name
     attr-dict
-    (`initializer` `(` $initializer^ `)`)?
+    (`initializer` `(` $initializer^ `)`):(``)?
     custom<TypeOrAttr>($type, $initial_value)
   }];
 
@@ -404,7 +404,7 @@
     VM_GlobalRefAttr:$global
   );
   let results = (outs
-    AnyPtr:$result
+    Util_AnyPtr:$result
   );
 
   let assemblyFormat = "$global attr-dict `:` type($result)";
@@ -478,7 +478,7 @@
       DeclareOpInterfaceMethods<VM_SerializableOpInterface>,
     ])> {
   let arguments = (ins
-    AnyTypeOf<[VM_Ptr, PtrOf<type>]>:$global
+    AnyTypeOf<[VM_Ptr, Util_PtrOf<type>]>:$global
   );
   let results = (outs
     type:$value
@@ -509,7 +509,7 @@
     ])> {
   let arguments = (ins
     type:$value,
-    AnyTypeOf<[VM_Ptr, PtrOf<type>]>:$global
+    AnyTypeOf<[VM_Ptr, Util_PtrOf<type>]>:$global
   );
 
   let assemblyFormat = "$value `,` $global attr-dict `:` type($value) `->` type($global)";
diff --git a/iree/compiler/Dialect/VM/Transforms/BUILD b/iree/compiler/Dialect/VM/Transforms/BUILD
index 4a9067f..fd4d30a 100644
--- a/iree/compiler/Dialect/VM/Transforms/BUILD
+++ b/iree/compiler/Dialect/VM/Transforms/BUILD
@@ -26,13 +26,13 @@
     ],
     deps = [
         "//iree/compiler/Dialect/Shape/IR",
-        "//iree/compiler/Dialect/Util/Conversion:PreserveCompilerHints",
+        "//iree/compiler/Dialect/Util/Conversion",
         "//iree/compiler/Dialect/Util/IR",
         "//iree/compiler/Dialect/VM/Conversion",
-        "//iree/compiler/Dialect/VM/Conversion/IREEToVM",
         "//iree/compiler/Dialect/VM/Conversion/MathToVM",
         "//iree/compiler/Dialect/VM/Conversion/MemRefToVM",
         "//iree/compiler/Dialect/VM/Conversion/StandardToVM",
+        "//iree/compiler/Dialect/VM/Conversion/UtilToVM",
         "//iree/compiler/Dialect/VM/IR",
         "@llvm-project//llvm:Support",
         "@llvm-project//mlir:Affine",
diff --git a/iree/compiler/Dialect/VM/Transforms/CMakeLists.txt b/iree/compiler/Dialect/VM/Transforms/CMakeLists.txt
index 971b3c4..5558889 100644
--- a/iree/compiler/Dialect/VM/Transforms/CMakeLists.txt
+++ b/iree/compiler/Dialect/VM/Transforms/CMakeLists.txt
@@ -37,13 +37,13 @@
     MLIRTransformUtils
     MLIRTransforms
     iree::compiler::Dialect::Shape::IR
-    iree::compiler::Dialect::Util::Conversion::PreserveCompilerHints
+    iree::compiler::Dialect::Util::Conversion
     iree::compiler::Dialect::Util::IR
     iree::compiler::Dialect::VM::Conversion
-    iree::compiler::Dialect::VM::Conversion::IREEToVM
     iree::compiler::Dialect::VM::Conversion::MathToVM
     iree::compiler::Dialect::VM::Conversion::MemRefToVM
     iree::compiler::Dialect::VM::Conversion::StandardToVM
+    iree::compiler::Dialect::VM::Conversion::UtilToVM
     iree::compiler::Dialect::VM::IR
   PUBLIC
 )
diff --git a/iree/compiler/Dialect/VM/Transforms/Conversion.cpp b/iree/compiler/Dialect/VM/Transforms/Conversion.cpp
index 7dc52c3..77e686c 100644
--- a/iree/compiler/Dialect/VM/Transforms/Conversion.cpp
+++ b/iree/compiler/Dialect/VM/Transforms/Conversion.cpp
@@ -8,16 +8,16 @@
 #include <tuple>
 
 #include "iree/compiler/Dialect/Shape/IR/ShapeOps.h"
-#include "iree/compiler/Dialect/Util/Conversion/PreserveCompilerHints.h"
+#include "iree/compiler/Dialect/Util/Conversion/ConversionPatterns.h"
 #include "iree/compiler/Dialect/Util/IR/UtilDialect.h"
 #include "iree/compiler/Dialect/VM/Conversion/ConversionDialectInterface.h"
 #include "iree/compiler/Dialect/VM/Conversion/ConversionTarget.h"
-#include "iree/compiler/Dialect/VM/Conversion/IREEToVM/ConvertIREEToVM.h"
 #include "iree/compiler/Dialect/VM/Conversion/ImportUtils.h"
 #include "iree/compiler/Dialect/VM/Conversion/MathToVM/ConvertMathToVM.h"
 #include "iree/compiler/Dialect/VM/Conversion/MemRefToVM/ConvertMemRefToVM.h"
 #include "iree/compiler/Dialect/VM/Conversion/StandardToVM/ConvertStandardToVM.h"
 #include "iree/compiler/Dialect/VM/Conversion/TypeConverter.h"
+#include "iree/compiler/Dialect/VM/Conversion/UtilToVM/ConvertUtilToVM.h"
 #include "llvm/ADT/STLExtras.h"
 #include "mlir/Conversion/AffineToStandard/AffineToStandard.h"
 #include "mlir/Dialect/Affine/IR/AffineOps.h"
@@ -129,7 +129,8 @@
     }
 
     OwningRewritePatternList conversionPatterns(&getContext());
-    populateIREEToVMPatterns(context, typeConverter, conversionPatterns);
+    populateUtilToVMPatterns(context, conversionTarget, typeConverter,
+                             conversionPatterns);
     populateStandardToVMPatterns(context, typeConverter, conversionPatterns);
     populateMathToVMPatterns(context, typeConverter, conversionPatterns);
     populateMemRefToVMPatterns(context, conversionTarget, typeConverter,
@@ -149,10 +150,8 @@
           importSymbols, conversionPatterns, typeConverter);
     }
     Shape::populateFoldConversionPatterns(context, conversionPatterns);
-    IREE::Util::populatePreserveCompilerHintsPatterns(context,
-                                                      conversionPatterns);
-    IREE::Util::setupCompilerHintsLegality(context, conversionTarget,
-                                           typeConverter);
+    populateUtilConversionPatterns(context, conversionTarget, typeConverter,
+                                   conversionPatterns);
 
     if (failed(applyPartialConversion(outerModuleOp, conversionTarget,
                                       std::move(conversionPatterns)))) {
diff --git a/iree/samples/models/mnist.mlir b/iree/samples/models/mnist.mlir
index f408e3a..fa05796 100644
--- a/iree/samples/models/mnist.mlir
+++ b/iree/samples/models/mnist.mlir
@@ -12,22 +12,22 @@
 // Output: a tensor<1x10xf32> containing prediction confidence values for each digit in [0, 9]
 
 module {
-  flow.variable @"__iree_flow___sm_node17__model.layer-1.kernel" dense<"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D6B5C4D3C57E241BDB4609ABD3E2B1A3D9369513CC6EF4A3CE4560C3D5150053DD878613DE3AB103DB91F323C2CC066BD72A0013DEA629FBD58E3DDBCA911653DAB99143D95B0103BE9B25ABD6F2B99BC0CF626BC2CE9A3BD0FBBDE3C871F9ABC3ACB923DFA3BFF3BC1BA92BD7F9E2C3D384C963D94AE933D951874BCCA88A6BDB0033BBDDE8CA33C4B75833D5C899FBCBBF9643D6054F73C6122C9BC5CCB3E3CAE78BBBC0DA793BD2978733D1A887EBD49AB693CD01401BC7D5B543DDA83533C74D4633DD9B852BDB781A13D996CF33BCE8B6ABDB614EE3CD1F825BC42716ABD42E1333D089B9BBDC6D3603DD34B323DEA9F3BBB68D72F3DDE34883B8A228C3DD93C90BDCFD4883BD6B3EC3C04688D3C23988ABD5B464ABD4AC9093D4972AB3C83BD7F3DAC66703CDFBC173DE76D413D03E72A3AF3F1003D1CE911BD86FFD43C9650C0BC72355EBD2E620F3D17377ABD03061CBD4007483DA951083DBC03003D9271163DAEEB0DBDB21E623D7E40A63D6402AEBCC18B9E3DF7EB5EBCFC3ECF3C2C9503BDC7816D3DC765213D0A90A33CD24F4F3D4EAA8E3DF2D8793DEDFD70BD53C64BBD1C46773DF677C2BCDB31A7BD8B8E653AA07C663C5DA8613DEBFF33BD61E75D3D5B924B3CD86C9FBDF5381B3DDAD1243C9FFC52BD55C7A3BDE3F0193C02D693BC73BA363DC9F2413B5596A33D0E88BEBA6B54FABBBB71DF3CAF4098BDF1878FBDBFB0593D416E723C980BCDBB3D1A4A3D252635BDBA626CBB1DF5863D496955BDEECF92BD41F2A33D472278BD17CFA33C85ED70BDD9CA3B3DC0A24FBDA5A575BDBC8A5ABDFBB5133D3220D1BC932AF43BCBBE89BD7BA38ABD545A5C3D77A2A03DCAAC113DBCB539BC2D20783D615D84BB6494DF3BFBD3A13D4462153DAD07D73C788B3ABD2FA0563C87D59BBD96335DBDAD198DBD564E72BC09F25CBD928DC6BB523CE73CDE1A853D3A5D03BC6CA78ABD658C98BD33DE8BBD0112B83C1416F4BC38A91ABD69A7C93C9C6D803A842A23BDBBD5983DB0E805BDF8817F3B5BBB8B3C5F7B8EBD1ACA6C3C72C2BEBC1665833DE2C1243D82A341BC84BD11BD0941E63C28D89E3D0A7C51BD9E5490BD208953BDD7B178BD57A8A53DB6FCB83A52068CBD4725693D604A933D0D8E3EBC01918CBCF7F1A2BD32D95CBD6EDC9BBCFB8AA3BB1A6291BC3838F9BCDE84ACBC77B06EBDB19570BDCD18213DA6A13C3D28338C3D5FF372BC6C73E3BB54E37B3DF6C7AEBC0630B5BCB2727B3D2A1D44BD25AA6F3C635067BC92C098BD8F9840BDEDFD73BC39BB07BDADD09C3D3769FD3CC3378BBA5993E6BBCC38BFBBFBF99F3DFF17593D13E9053DBF8E153C8658DBBB0E7B0F3D10CC5F3D5F3995BD3BBB0EBD6EFE5DBDB5434D3C5329A2BDDC2C3E3D236B57BD66C39CBDAF4E803D223E1DBC604F393D19B0573B8016923C37B051BD8E076A3DA2019BBDAA1E67BD7D39A6BD00AAF13AA860923D6D1E02BD4DDD5B3D29B7423D6674203DC93D073C09E93C3DFC786F3B4C69A43D7D3823BDA5EA9A3DC6B4A5BDDEC0FD3CD52396BD201F953C3EFA9B3DFF3F903D2D4C1EBD06FB953B6C818D3D5A45693D1D4D413D77DE813DBC645F3B81AF993B57BD5ABCB5ABC1BC53AECEBC5B0A8EBDEF2D86BC0422EEBCDC1B89BDB6F1A1BDD6B12C3CFA1F5E3D1E9FF53CA354883DC377903D87C1453D4E02063D15F29D3DDF44993AC85437BD332D473CBE75183D61F6F73C755C26BCCD8332BD044CFBBC93D725BDD0B9293DF19E773D9CDA8ABDBE46A0BBAF69593D0921403D8BCB2F3A3F69FBBC54A4743D39852F3D9B1494BDE46FA4BDF312013D2936823D06251CBD1BC9463C8989503DFF9EE3BCD8D87DBD29497FBD799225BD02DD993D451B2B3DD273923D3B3E18BD2EB258BDA0CE3A3D0DDC893DF39B6D3D6C0E7BBD6E52953D58505BBCDAE40DBD2339733DA6FE0C3C9861303C0A3E20BDAB6286BC88F75ABC307606BD1DAB443C066C26BC958F92BDC40149BB1A755B3DBA9F91BC9A4E22BDD1D4903D60EA97BA7275A5BD9188A5BD727004BD6B48883D3BFB833DA0D352BC76D26EBD3B8A00BD946A7B3D11987EBD506EC03CC783A13D06EE2BBCBFB76C3D5776593DE1289CBC1C93AC3BF0E2F6BB0C3B6BBDC5F48D3DA5ADCE3C9A487ABDF00F203D57A4913D1AE07CBD472C18BD2303653DFDD8333D2B7813BD4B67A13D6A4E04BDC8CFA1BDCE87943DA8510D3C5F24103C344C03BC1F69893DC610113DCCFA6EBD9C7B91BD3E4817BD89C7903C9043463DC07AA4BD13AB5FBC25DD80BD32128B3D9025A2BD7A3B8D3D764D4D3DC43895BDB0EC83BCED6AA03DE73F0C3DE58637BD13128EBD12EF4B3D0ECAE6BC953B9E3C7C3E7A3D8C0E193B261F3A3DABE28EBD609AE5BC18E9F03C8F7892BDBE09373D0AF375BD00FEC63A80EF923C47FE0EBD480D11BC8C278B3C74B8B7BC20D589BDF40896BD31EF87BDAAFE56BD71EB04BDA1C8A1BD43DEA13D68664CBD1B0062BD8702A5BD30E0E0BB8E2E693DB1D4993D789CE63CA459C73C67D1823D007D2ABB8078693B2CB600BD630114BD60F7C83BFC8DB23CA14539BD5F4707BD90FD31BCB0D1253C1EAD023D429843BD86708CBD150A0CBDC050833AA0B63F3CDA55473DB45CA5BD8022B4BBC8D1253C42D80F3D7773973D96315A3D698C803DA28083BDFD0408BDDEB899BD0A13433D90218F3C004F7A3C86ECC2BC15BA0EBDAA4672BDF0A63CBD500BAFBC80BC353BE05885BBBCF180BD4668013D8689773D47B973BD62A1D2BCEE853F3D24B8D23C10AE223CDE5A253DB505913D9890323D647D0ABDEF0DA3BD1CA48CBCE82A0BBCCBC4843DEB7C9E3D8C5FFABC4CF9093D3925903D580615BC0080593CDCD5E93C601F62BB6F35933D6D6B883D2049983CE1318E3DC8AAD33CB1868B3D97A3933D8AD15FBD92B68FBDE4689EBD3CFAE03C18489FBC07998F3D2405C63C9B4A833D1FBC8A3D76F054BD5A82783D3871003C6FACA5BD999477BDB17779BD26043D3D4A5FDFBC8BCF93BDC565873DD636023D580ECC3C31109A3DACC99FBD129C4EBD68FFB83CDDBFA03DE02CC1BCC0ED66BB00B646BD496185BDC010CB3C0475E3BC7D224BBDCDF99ABD48EF483C6FCB963DA8DB20BC9BD201BDBE09E3BC3877B53C7E2980BDC86FA63CDCDEE3BC20B98EBCA42EA43CB074023D9E595C3D080444BD9D7B8A3DF6C58ABD7AF7113DF60E5E3D437613BD901C3B3CBA264E3DC080ACBB1973A3BD6F3B9C3D7A762E3D24EDC73CB05E1F3D867D80BDE7EE833D875544BD20740E3DC6B6F2BC261C33BDA38315BD70770DBCFB014EBDF046D33C43489ABD1F489E3DAEF0013D2EE5703D062A183D31F7943D9A9F4FBD924D6D3D00F658BA124A20BD806DF7BCB2787D3D8A7DDDBC51AA3EBDCE1C223D102BB53CC08ACDBAF862CD3CAFFD26BD90974BBCB06631BC3E8B583D128BB7BC628DD8BCD6F54E3DF8DB583C4385A03D74A947BDF28384BDB8FA793C1DB98A3D7D6876BDA4ED2D3D4068103DA6A7153D0813553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D35B135BD6D6349BBF0A6893DE5541FBD928E5D3D9670FBBB88D3A63C6834303D1768243D4A840BBC0A07783C6DA5A13CA568243C6DC698BD9FD3C7BC3AA6A9BD9C6CE3BC35301E3D6B763DBD7CCC8EBC41A8963D81D6D83BB511503CC800233D34F8743D522525BD4D57C93CD59262BD1C54D53C0F576B3D426CAABDB682F23C0FE9B2BD83029ABDD0EE0D3D45B4DBBCC588CB3DC23830BC7DD3893DF792243D3637BB3D849D903B4E0D6C3D5323C73D60609BBC160646BDB76429BDB84361BD066EFD3CCE6B40BD088F43BDEC0DC33D9B0ABE3D3DAB02BD400F463DADBF593BF514683DE2C53D3C5E7C50BC970C3B3DACB94C3D54F919BD9EBC503D8319433D219A04BDD12110BCA174DDBDDF6B603D1524AA3C93549D3C73B4CCBC55C1A63C09FB7FBC490C613DBFF387BD4D92C6BB9C958ABCE9EEB03DB724933C8DABA9BDAE1D61BC039267BDEAD88A3C749CEF3D73F5293DBCFFD2BCBCFFE83C197A0B3DEADF14BD85E79D3D0292B4BC4691FABC1F16D03C03E209BC9412CDBC6A2AA7BD6CAEFC3CD038F03C8E73FDBC7FF3073D14749EBCE57D843D0342573DE43244BD28A0323D5B37A33D0CB8EEBC47BA9D3DCAC7E63C0CE8163DE014C53C08F729BD7FB7593D487D253D439A48BD0163A2BD402D503DD8650F3D66DC4D3D174ED23A57F09D3C2C67413D39BC17BDD9C4D6BD83D0763DB5CEFBBC81DAC4BCCCFA9F3DF87D8ABB3EADB63C0D610BBD2BD673BC96463C3DA5268FBCFDAB90BD32F52A3D11357A3CB81D84BD357279BC7FC5853D975F8B3B74F009BDFFA4DCBC8A4BFF3A8018CC3D7B4639BC5B19C8BC873D5B3CD23C9A3DA644103D65A246BD0B37BB3DE91FB83DD62190BD4F3DA7BD649ED7BC5C71D3BD477E76BD0622A13C15E1753D9E8E87BC3E2979BD6532EB3B0BB78BBCC9AD103D25AB5D3D0B052E3D3BE8293CE88E003EA55A57BD528E973CD04160BBDBCA8BBDAF3485BD127172BDBE9E48BB75B004BDEB8ACEBCDE8DE83C19223B3D4607C13DB48690BC03DEDBBD02A6613D7B4ABD3D30C61DBB6602C0BDAECB13BD305BF23B71618CBC53DD53BCEA57873CF1F847BD336B1E3D579D39BD584D713DECC1B2BC971A94BC9571003D0A170EBDABD5B4BC0F8EB6BDE79F09BD1C66593C55629CBD97C0BA3D60F57FBD1575883C4ACED9BC591754BD72DA4DBDBAAE8C3D13301D3C33D4CCBD509B153D699FC83D28919D3D604E8F3CCCB70FBD6C46F23D43A267BD43E890BDCFB80F3CAC91233CBB84E13CD54FC43D43F123BD1D569B3D05FAFAB9212D48BC40F245BDDDA059BD018128BDFD7E2ABD253914BCC7331C3DB21DD1BB8F24ACBBDAFCBFBDB99E7D3C5E93803D3C99013DAF22893D80536CBC78EBB5BD0E97793C4CED823D2467863DB6DC5D3CB0EDFEBCB74E633DC0B1043DA0512FBD45E81C3D0E9E91BDB2175FBD6D92EC3C5523F63D9EBC8FBDD2343F3D8073523D3752903C9AE886BD0AC1F93CD5BF623C18DEC03D744AD6BC5637A33D96D737BD1BA5BE3D5D0EA33D7CBB10BD41292F3D69CF24BD4B0BA73D81A9373D6A85A1BD0D4E923D50568B3DF814743DD46E15BD6AF048BDEFD393BB988EF43CCCA03ABA517987BDDC7840BDE497DD3DBC9BF4BCA2F8093D4F5890BC2EB46C3DFA22E83D1AFD933C7BAC36BD520E383D66CE883DE9BDE6BC35DDAB3D8490063EE5836A3D566F393DBED303BDBC34A73C3FDB113C29B524BC4B92173DCB490C3EE83F963DA971B53D51E3A3BDF4049DBB8C4E8D3C7C6A293C9215493DBCABA83D560481BD92A50FBDB8FE91BADE755A3D6CB811BD702683BC2CDA483DE04D913CF7AD203D57374FBDA34B8ABDCDEE4DBD0B99A6BDA549423DC075A73D331C1BBD984AB53CBE95993D2647103D17EC083DC53A88BD812D8D3C8296A7BDB7E3B83D5DB7053D6A4BBBBD3E625A3D53215EBD9A7F093D5009583C24BE29BD5D5C1E3C892EC93D63CC3B3D226D9DBDE53CD0BD577F71BB4EA8A63D7EA775BD4390E4BCAEDE24BDF66E673CA782823C17681FBD1356D93C10378F3DA30C89BD82C2A23DEC92173D3385043DA9E2F2BD1D3888BDD896B3BD26E1003DE22FA63D8EBF313D5FE37E3CDDA4873D44BB2F3C5F25D93DF1242CBD50D5513D799FCEBC8A88A9BC19CF18BD093C943D8D6CA8B90E13B13C7F8372BBCE09383D1840F2BDC73C1EBDC24D4BBB5F4E2A3C7652BABC35F8973DA2F2C5BC24A8F8BCB16C393DFF56E33C6B2BBBBCAD74473DFBBF843CBF98363D5AFF583DDACA39BDF1109B3DE8E66DBD3D34E0BDFE18D03C6F55A6BC91141F3E66D2783CB8E1893D3A548DBD914727BD016089BDE7EDA7BDD3CDA0BB588B133ECC98F4BDC9D2163D5342233C12AD17BD2D809B3DB7E7943CEC86B93CC4CCB63C373B213E19FE53BDBCDEE73DB25D3D3DC1C2B9BCF737C2BD9D7F99BDB22DCF3DFA6E91BD1052783D4DD3E93B24471A3DAB7B623DEE3BCEBCAB24D0BDFFFDF9BC95A2453C5E86B3BC790CB2BD5CE1703C064AE03CF00CA63DEA44383DBA0CD53D118F5BBD89E6933DF697783D8001B9BB96915F3C5EC7A7BBAFAA763DAACFDFBC515BBCBD5F7241BDAF00DF3C9B66493C207E4F3D6A07C0BA358E84BD2EA654BCA59F81BD881F0DBD185B453DF798A53DF16763BD1874BABCFA7599BD1B20D83ABE679DBC42F7CFBC57C463BB6330D03D301BB9BC9735133D8747D7BDD6CD793CD10A54BDC188803B3E1CB0BD9E1D8E3DC122AEBCC521B03B818D41BD114C323C369B873DB50D783D15A097BD550A043D32789ABDFE80A3BDBC16AFBD33E7A0BDECE4653C919A8A3CC24B413CA4BB513DD40F85BDA10BED3BE86882BDC7E97A3DB2D0DB3CEF2E74BD829616BC566889BC45F125BDF3DA4BBB515370BC34B01C3D41066E3DF4FD8FBCFE64D8BD11322DBC999C9E3DC16F3BBDB46D333CAFCCD73D35401EBD7E041F3CFDE181BD12D54D3D73D84E3D9AF83FBDBB81723CB6C0A1BDA29BAE3C990095BDAFC0013E874021BD1945C5BDA8B592BCFFEDBD3DA094EE3DC5E4C83860F36F3D537E333D61568A3C6FF21C3DC1BBA93BAB8888BC1D20793DEB57A5BD3386593D70B2FDBD3DFD25BD4F7A143D0D050DBC718EB63DCBB3073D47220D3ED85DF5BC27A749BDE203A03D53C38B3D0099EBBCC727CCBD31C5703D7439DCBCC8547A3D640C62BD14DE0C3E1670FD3CFCA6053C2B24323C8392FAB92104183DD32D303D8ADD53BCE6969B3DC7F9AF3C1FADD1BC5752CA3D38E4993D0BD444BD64DA0D3CA82DF03B54E205BD08173DBB1AEF1ABD46088FBDC9A19CBD5AFC6CBDCB888EBCDB42AC3DFD4B3FBD801A1A3D0B6A83BD3DF5063D2DBC27BD66E32D3D3F8712BD52D1823DDD2C183EFA00DD3BC14342BDDC47C73C70A45EBD52D1DB3B3BAE383C71520ABE4AC7553D78D53B3CC0B13F3DD84A91BD52FB1A3DBC7948BC83F585BD666B383D2484993CE76E533D2AB5F13C9BF6AFBDE00BCDBB3C8D40BDBA40943C6A3C153D14E89C3D36E08EBBB50EC93CCC2100BD054FA3BD53F284B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D02667B3DC11F6A3D5C663A3B716A00BDCA16F0BC0D40023C8A6531BDB9E447BDC40487BD1EDC6EBD7F508CBC4CEC25BD56EC353D040D86BCF0CCD23D734C873C1CEF9BBDFD7582BD949FF83DE41E573DA6A7323D719EB2BD1391863DC70FCEBA66D3A9BD3A82603DE4EDC23C715B773BE16F5F3DB28D90BC622990BDAD1BE53D81F917BDC879543D4B8314BD8A4532BDAA879BBD6B80903D4B8D533DBE9373BD1368A53D3E91903C4C66A43A0A85263D4EACE4BB8AE181BD179DD23B0A4A9DBC1A901F3D7EEF6FBA1349B43CD08A93BA1A75553D3FF4183DEA1D6E3D2421233BA3B724BDD2D6A73DE53A82BDD80880BC5FF28FBD2479EA3BC2065EBDCC32B4BAFD502DBDD82AB23D49B8F2BD5ABCF23C2EA1A43B1C7D443DE7A9123DFC42723D8C126EBD24CD2D3DD714223C871A86BDCE97BD3D5DFF083CC57B72BC6604C13C04DE7B3DE4CAA83D714995BDA6ED363DDE88A2BD8636983D7BB89EBDC85D9BBD65DFEFBCB2E41ABEBDE021BD3D8E80BD5AF09DBB3A6919BC1E0B8C3DE2D5213CDDD174BC5148253DBA86E7BD1D9A573DEC14C9BC4094DEBC5F6A893D595B173DC284C2BCD4EFBE3D2776E1BCCE27C63D2A4A3C3DDF5DF1BB28C97EBDC284B5BD3AC75E3DC2623CBCFD398E3D633C283D540988BC0F52413D471FADBDA062A13C0370B43C04B1A03D9073AFBD7D4DB93D2C98B63B0F3AB83D94DB9FBBDB8CA43D1DA5A5BBF272F0BC28DD0A3DB1CE04BCCC8073BD7AA16A3D0F96D6BBF75DAD3C07D41D3DC07D343C8D094D3DAFFD85BDCAC3BBBDF2CCA33B34F4163DF569BE3C720C2B3D0D725CBC7A1642BC54C3293D69B72C3DDD0E14BC428ABABB212BDABC1FBE1BB9670CF13DDDBF2C3D94714ABDB18BF93C725D98BD8A1A743DC171CC3D4A8AE53CA359BF3D44C1133D66CE7DBD5227E53B0C51AABD1FF4053D854C4D3D1C0190BD178E2D3CDA2D6EBD32B2183D94C6933C4B566ABD786E0EBD9B82783B2ED5183D37B336BDB18A2B3D387FD43DCFA4553D0CD2993D1973223DFE581F3D21FFADBB6C2228BCFAE6123C4E085A3DC7132DBDC9F6B03DD2256ABD0F3F283D1279E83DCE187ABCE962A7BD17AC273C3C9B673D8A3615BCFB3983BDEAD3443D49A87CBCE36F59BD3190F03C10FC9ABD69A73DBC40B8973DFCA156BDB427E5BD70E29F3B0560883DA629D9BC4FF5ED3C10154E3DB26F8C3D6B8BC0BDB599F33A5719F23C524D3EBDC0AF01BC5AE0013D8E825C3C9967A1BD64AB393DC0EF33BDA14E9E3DC35CD2BCDE9FC8BD1F69583DC7A1573C381B59BDE2C0E83C824CD6BDF4E382BD74E5953D1AFA03BD64E8443D54908139C48838BD09618B3D88ECC03C83EA26BDE2F4023CACA98ABD9C94E3BB7D7790BDC6FEBFBC37352D3DF06B883D453FAABDAE9EFE3D4DDE1B3D75E8B23DB90AE73C18355DBDA83B253DEA53B4BCCDC3653DA325983C5E105F3D85187C3D9F46213D4E05ECBB2A152EBD8A370DBBF405EEBC932690BB34F0BE3BF17E923D5B84AABD79CF1C3DEACF15BDBFE53BBD6E5E3B3D8A490EBE52BDBA3D0B88D8BC7EE1A63C5C00373DFFBE2EBDE821F93CD09E63BA67AFFF3DCB89533D7C706CBD3B2706BD15BE6E3D6DAF68BD5A63E23DD636E73D7094953D9B80C7B85DEE8F3D9D73AEBD880685BDE580AB3D22F4A6BDF1B730BCAFB10FBD11748ABD03CF6D3D2AB6153DEE32A4BB8B12CFBBE0AC2B3CD23137BD2E1A7E3D40D1A63A9CE3703D00AF773CB1E1213EF5DDF63BC2920B3C8A3490B9AEE349BC1D09E2BD0041C1BD9B704DBDAB6249BD3BBA0ABDAE7F6B3CF4874F3D9CA8343D61FFB1BD40A3E8BDDDA0A53CCBFF793D9F118BBDD934E6BD73AD473DD30A393CF28F18BD17728A3D8EA38F3D8541AB3D9D23263B1F8410BE8BA52C3D59B696BD96CBE6BB74621D3D2D52F0BCE4C3A6BCC72812BD80588FBD1BC8843C990632BDDBB1DB3C55FDE6BC13551ABD19EB6E3CB558A63DC7EA9A3CB04ACB3B1602373DD3D2153D69EA54BDDBE9B33BB9838E3CEED475BDE26668BDEF38D9BD765139BD9E84B53D452DF1BC177EA9BC1E77CF3BB21D77BD6B6887BD346902BDE2958FBCD88646BD4D62FF3B3B3607BDD99587BCB0BD80BD76C3E63DE0DB2EBD3CBE373C0CACCC3C6E6D6ABD4128FEBCFFCFBF3DFC3884BD03A2EB3D1FDBEFBC06805EBDA3E4133D59B721BDBEFB343D7ED6ACBB0120FFBC14DA813D15D758BC0B5B9C3D2663C03B57497E3DAB754F3C624188BD80384C3D0517913C39408FBDDFB71ABD584CD43DE89271BDB931B33DB79157BD5A97033DA6D4BB3D260B143DC4C1903C50B283BCA176453D8699BC3B13678A3BBFA8323D409C4F3DC662083B0F1A2CBD0F848ABC0D4BCDBD47E3A4BDA21952BDA139893DE4093A3CBDDF46BD1DF9313C3508243DDA24AD3DEC96E7BCA066A8BD1351253D9A908EBC82F2BC3C6882603D1DD7593C0579DA3D22553BBC3E43FABB2D42ADBDBAC201BC074F9C3DD480A5BD2F4E2B3DC6CC7CBD59CD6D3D012E163C491D3DBD44DAFDBCBD7C9F3C5ACDED3D8074EDBD42ECF8BD20AE6A3DA0FC8E3D3CF1D3BCD92B02BDFD2434BD85AD8C3D64F639BC83FA27BDD0FE72BC87C9E53CA4EB83BD438936BDA78AADBCDB57A8BC71457FBC737EB13CF3F08CBDDF796F3BB111DFBDB1E124BDC127A13DD3A98BBDA554F53CF4EF103D3E1E32BDC8AE153D71B768BD6D8B413C92EC86BCCB0D14BCBA9C9E3C370D7ABD2B010F3D5CCC0A3B3180383D623D29BD3C4C40398FD82A3D13A21D3D39BDFE3B6EA4B93DD4CADC3CB222BB3C5095FFBCC5D19EBC5D9C89BCBDE0493D2E16F13CF9F3603DD9668E3CCBBC663D235C86BB877E3ABD512B2DBDEB6941BD011A1EBDFAE8103DA661C8BC514A56BC63BA09BD4242F1BB2BEA27BC6C3B2D3BD8BEA43D140387BBBCDC283DE45DBE3CA2D5383D3485443CB3A1163DFE7FB33CB28062BBF93389BD5E47D2BB841247BD8B8006BBCD8490BDAA6190BDC708313D2F873CBD6F7E583C4FA3C53D1AFBAA3D352370BDAB8D8BBD70C2853D33D979BDB32A5ABB956F5EBD6528CC3C0895F73CEB922B3D1D361B3DE7A4A13D950DA13DFF88CBBD8C5996BD531E273D2F6AD7BCDADDFBBCEAB5CB3B41D28A3C94718B3B107ECC3DDFBAB63C9AD4C3BBF72184BDD3F6153CFAFA3A3DB881E2BC47E88DBCE551DC3CE3E909BDB24AA63D22B16CBD311C8BBD958B483D8EE8B4BD5490F0BB1263623D8F1D8CBC4694693CFAC3CEBC5656A93DFAAB063C9BCCB33DF5D819BD152ADE3C455BCB3CC4127E3D1E93C93D4B0242BC6F7841B965D5CABCFD802ABD281FFA3C8D7983BD3F0E8BBC6B92D5BC368C843DDA90603D30665C3D9E4A1CBD3B82A1BDB0133F3DBD1F973DE6619CBDB6C893BD0FEE18BD0136E13BF1CDEABB800A053DEE11043BD74888BC80385EBD230423BD8E78883C935D583D51C8B9BC099E8FBB3EE49CBC2C5899BDB5DD75BD8F83D63C64013A3C2A44963D12574B3D53B59D3CA9599B3C3F69E7B98D397DBDEF9A6F3B0B573A3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C98E0D43D043EB63D07E5A53DC484093DFF73883D513C38BDF50994BCD0B1853B924F0FBD8178BB3C728D86BD183BD7BB3FFE1FBDF54ADABD45F870BC46FC8D3D363A82BD084F613C42239B3CD2C45F3D678041BDD0D0983CDFD4713D2486BEBB6420263C911A943D845B00BD82E4343CB0AEFC3B6EAF4CBD74FD4EBC68BE563B0EC62B3D2363993C238EB8BD6334EA3CAC88BBBD2B1633BC38821E3A982EAF3D94A1F53C5FEA1F3E4914A83D3D148ABDE810AA3D824C263E022BB33C0BD8E3BCF76492BD1E55AE3DF89CE9BB04CCE73D023AB53DF3652BBDC78C99BD844F98BD4D7BB8BD0461F53D3CB00F3DA40604BD54A426BD3B11D73C73F2993C1318C43DEEA42BBD382DB93DCE0B003C4853933DF5E792BDB3B6CE3DE33D8B3D8B150C3CE8ED45BD8F15263D1FD77A3D5CDE91BDD1B31C3DAB04A0BDE9C57D3D97B0193D678E9F3CA5BE93BD1D3B99BD17B38E3D083B633D6A721ABD437BFE3D1A0180BDB6C8183D672730BD6E988C3DF57B15BC68FFB63D27CEB53C4EBAD93C217CA03D0FCFE33CB9220C3DC7D855BDFFD49DBC4517D0BDEC19CABD0EBD773DCDDA0BBD9E0EE13C7EA17DBD1830A33D7BDD03BDDFFB84BD0D82503D1A9985BCB8EE643D84C65E3D7013963CE901A2BC79DDD13DFD5F1D3D7E8B283C3A7CC03CB18A83BD578CC2BC4D3AFABB62F997BC03B8D63C9245D23CBE34E0BC4DCADA3DE560A03DD49C293D46439B3D63F217BD97F8853DECE8E43D90F8CB3CD2DEF33DBAA7A23CD89415BD4C26AFBCDAC0F6BCDF0AD6BC9EE66BBD0667CFBB0388A93DCC53BD3D430C243D0E22EE3B47A3103D39D5AA3DCF81DABD08602ABB13A2C73D8CF44CBD32B099BDE5597ABDAF49CD3D33D6283D4E6A83BD0E85A4BDC15F2BBD5A3618BDCCFAC33C7541F53C0C59563D0DCFA73D2F5FE23C0DF5E43BD52169BBA458EF3AE0D3D23D0550073EBBAE353D2A3F5ABD3A3B28BCB7C65ABD9A7B3D3C7AA312BD0F567EBD6D31143C400EAE3D2482963C9B0326BCA71192BD8FB82F3C5C9E86BDB9F3BBBC3DECC0BC64A4A63DC4B8883D63471BBDD7F798394ADA6ABC9B1D71BB1AE8973D73992BBD6F50C73DE98516BD6C12063D7CA6043E6A44A83DE15688BD4043433D4F0DE5BA8D5B8DBD78AE473DE7A6A8BC7D53E33C471E393C02382B3D35E2323DB3CF2ABDA60FAEBD146C8C3D0379C83DF30F2ABD4742C03D0DBC55BC02A088BD2D3B833D2C48FE3C329E153DA2BB913DFAB38E3D66C0C23DDFDF953D96B794BD88B8F73CFFF090BD54D8A93D5E9B18BDE3B3C9BD5541083D6840B3BD2BEEC0BD9C1295BCA51A243D0DA857BD92158EBD9B35243DE0112EBD79ED933DAEC84BBD969F34BD354CB8BD8085EE3DFFDFFABCD6E5FBBC236B4E3A5DC2623C4258693DFC3F6C3D5F75633CF8E3A3BC2C687BBC1D0932BCCA9107BDFE9452BDEC4BA53D4B04483D1FD6A93DD2583CBD1B9D823C83E8353DBA5C8B3D607BA2BDD9CD5CBCE3C264BC93E3D6BC97AA30BD8DB871BD6D61013D029CF03D23BE983DE8C04C3CC828443D2F41ED3C5B7081BBF6FADBBC99550EBD26FF083EFA82773CB291243D3992293D405BCA3DA74832BC0B2F6E3D1C56533C5BBB2BBDE011783C9D62A73D8ED354BDAC860FBDB086663D31D8013DC2F8EABC69B5D93BAA1837BCA276233B20DD2F3D2847B73C044384BD72D0AABB77CBD53C516C873B614D7A3CC6040DBEF7D830BD9977FE3CBAFCD6BCB546A2BC3FC1623D15FCC03DAA209CBC73CE373DEFB8283DDBAF5D3DC60138BDBE8FAC3CCE7B2DBD44DEC7BD0946E3BB5B0C963D49E05ABDCCF737BCB6ECAC3C34CEFE3C7EDD363C3221793BBB201CBD3327273C24776E3D44BA2A3CF23244BD7857393BD1B6593D35F253BD6693353DDE97733D328AEFB8E9E8BF3B4867E43D7F94003E3AF3AA3BD24BFE3D8F7515BD170FC83D9C39DA3CD05CDD3CCFB480BD4B2A71BC1371F2BAE1789C3DFDA1143DD73224BD8BEBBA3C8DAC88BCDB6C683D259BCD3BF0B18BBDFBD8A4BD78A8FF3C3125173D80FD31BDE9D0053DFEC2EABD5CF8A23D9BEAD43C2B5E473DCE43373DE428C6BD350290BDACEC8EBD8EE0FD3C887F28BD393788BC0CE087BA0689B73CD5F738BC6FE937BB0A874EBD6BEF853C070A0D3DAC308A3BB7AEBBBC1B12FE3C84504C3D8F058CBDFC96293D4FBCBCBDD867DC3C2FA87BBD1376353D8AA8603DB7A21EBC146E05BCF28A9F3D721534BD507748BD20E0503CBC95DB3D7B029C3D4C395FBC4C15013DB45D153CFBDCE23B86B5463DBFB3173C952AC63CC11393BD1E2C34BDB51EB13DE64F1ABCAE79AABC97B3563CBAD65F3D6142C33D32A93CBC92521CBDFD0217BBD842D0BD89F3B2BDADD4543DA329403D077B2D3C0DAA2E3DCF061B3D3E35AC3C228F7F3D30D2973BBA4E99BC8277D1BD4DD596BD48F217BC5F45F7BD5F951B3C3D61193C8BE3BBBC4CA3A13C867B7A3D2D5B643DCA7E29BD55460EBD9A81D83C62C6633DF15179BCD9117EBC1CFA46BD3D3480BD270913BD6E1F703DFC7B19BD49D1D43D7646A8BCAF8D573C29777B3B14560D3C7EA5893DACE84E3D997A443D26579ABDAAEBA63DEC8E4DBD2F6C89BD61911E3DEE066FBD6E7F60BDF9D6A1BC6886103C1F9D853D7DCB553D4402943C420E073EF8645CBCC4409C3D643034BC3776AABC3445CD3B0BEEECBC0EA49EBD5456F93D80A0BFBDA25C4A3DC4A35CBDE28F70BD66B15A3DE2E4E3BC1884CCBD8565953CA3E6593B162A8D3CC53A61BDEBC4DE3D0AEE9DBD0E5DA53AEFD0EFBCA772243DE3F207BDCAE925BD194202BE27D6C5BDEBB088BD04DE513C884DC6BDE16F953C3971773DD10880BC0430693CCAB6523C236D6D3DC18F913D052AB03C57E1473D5E1981BB3DDC9E3C4F3F6DBDD0D531BDF60D2D3C7A942CBB498055BD217C49BD3AFEB6BC58FF0ABD043EC3BDE59E83BD9EDA4BBD21CC783D89A8803CF96BFA3D97F2BB3C25759EBCD0D342BD936699BD17E204BE133E943C3DDB1BBC7103843DD1821CBDE3F55E3DF81A773DDDCF7C3D209A6F3D913E4A3C6A4CD73DC40BE33BED01843DDAAD97BDE5EC2A3B29C9693C0CD22A3D7691D13DB2D675BD49668F3C29FA96BDA5C3B83D0C8344BDBE9E53BDBCA128BD5DE7AABC0ECA9EBC984F553B820D0D3B4CA1213C2E87CD3C21309BBCF1C7123D2CE6593D6099E83CAE7FF23D9F520CBD3174303D51A5363D88491ABD8EB0BC3D09B35C3DB91C373D270330BC95081DBD8864B8BC0B4D903DABDCB73DAD6513BD10DFD63C0DBE513C7CE006BC963F2ABD87C8193DF6255FBDBA3B933D013B9D3C7F8EDABCEBD8A23D40FBB3BD8BE9A4BD0D04F6BCEFF4E4BC97A474BDF95B50BDB6D056BBC8CB7C3D62A5C03D527024BC0B6C6B3DC9C74B3D65709EBCE5753EBDFCB1A4383BEF0D3D5CE3FB3D28B27D3CE93EF8BC824B763DAD3F83BDBC39123CE08D5F3D2F20E83CB2EDF93CA794073DC78D2ABD3F5C2EBC65CD9D3CAEC8433C98FED0BD8F47493B957FCD3D1B81F23CBFEDDC3B36CE5F3CBC64823C7E6D2BBD2EAF713D2ED483BDC4D58BBB7EFA9D3CFFAB523D82FDAB3D483D51BC0BF25E3C5AA15CBCB9497F3D04495DBB03C7F9BCFB0E863D1CF9AFBC6B7DA6BDC10CA3BC027532BCDF9E8FBD800143BC5875453D7EF293BDFA0EC0BDDA632A3D1758333DC38908BDBCA21A3D7783AD3D58319B3C241C8CBDE6950ABD92C192BDE12099BDF6AD363B2703D73CF7DD8BBC642B30BBF78E55BD1F3A983D4BEC913DB9160A3D553ACC3D1C48D6BC4477B83D348FA6BC337151BD5FC7763A028DB9BCC3DA293D683323BD1255813DEDB544BDF4A10EBDFF58653C2BC6B03CDF0556BDED6A6B3AEC0674BC718989BD60A4E63CE4890B3D03229EBB394C8CBC87CF893D3FE520BD4B35FD3C5F8405BC6582AE3CEB5011BC5E9A9EBD3733933D3F7F893D9D65B23B4AC352BD2F8D24BDC2C347BD229013BDC6698F3C6F5B1F3D826B513D061C1F3D528D76BD376215B923DF8ABC7907DB3CDFE8CA3CC70336BD26EEA13B44599BBCF0658BBD571D593DC91441BDCF2A973CC8A9933C85B308BD250A51BDAAE3FA3CBF70793D93C445BDCEA1853C824497BCE4179F3D0E446DBD885C763CC4F00C3DDF23B9BB4FCC66BD5193D53DF5EFE0BD2A6BDB3C8167A13CB46188BD38ADDC3C784E5F3A0B25C93CEC9D12BCD067A33D6DEE3D3CAF975E3C05FD81BDF564A1BD89EBB6BCBDF44BBD8D9BCE3DEC64C13C4474E9BCE73EFABDB811BEBD1D87123C2C2DDC3D567B483D1AD4973D76F8533DD067313DB63AAF3CA52243BDC72A9F3BF494043D7E990D3D540273BD7BE76DBD9807DF3D8D6685BCFBACF93BDB3F94BDF136AEBBCA0A483DC69502BB5D49D7BA3DE7BDBD03B378BD748B55BD99F747BD7AD01ABD252797BD487A4B3D49ED9CBD714C7B3DF4254F3C1476CD3B8F7EAB3C79D0893D344D71BD2D94763D7196643D563D9B3AC4CB193D7FE84B3DAEA3A93B4E0E36BD2B29CD3D5B5B69BC331A34BD550E173C1F46553D93FFC5BC5F0ED23C9EBA33BD2BF52C3D07C0233DC8DEB93B3863B33DA4BD7CBDDF709A3C673986BDE37834BD66148C3CC48C56BC7A6D5FBDE6E4343DEF669D3D53843BBD3016C0BBE1A92C3D3D9C623D74B5103EC0823F3D8E31CBBCE9FF88BDB110A13D583312BDF47C013CCD91063CF227DEBCD02F86BD3B67AB39D933D13CF3C368BDCB29D4BCEE9F3CBDFFD110BD52A9AFBDBBCAE3B9B301193D61A587BDB3E5673CF9B55B3DD3F0633D5B294B3D42660F3D04EB783DBE9CE0BA54CC1ABD99AD1BBD50FB7B3DB687993D726B0E3CA6C4963D668F8EBDA5D7043D1347B9BDD7B298BDCA8E133A8F2B67BD0FB420BD4CC8C53C8CB8E73CE5B2833DE6B5DCBD6CCF88BD16450DBD656FAB3D7DB133BD6B73ACBC2F742FBD0DBFFC3CF45C973D7469A0BDC773073D9DA5F1BCB2F41CBDD785F93D04CB63BC3A4A3CBD95E0E4BC44A4F4BB3573AFBD6E29CD3DFCEE22BCD658A73D70FEE13C3CBD9DBD95FF013C860694BDD5042BBB2085373DA634543D4F6116BD241B89BCE2FF833B7A0556BB7B2313BD991B22BD538B423DB6975C3D11A5C4BD51A2FEBCAE4355BD402D0C3DE1D886BD0F9849BD99F189BD7A56803D033CD4BCDAFFF1BD195BC03C38EA623D1D17CCBB3385FB3A6A1459BCFBDB81BA018C373C560738BD8C5356BD4BAA03BB88B157BCB5FA103D46DF85BD32E938BCE76F47BD19C816BD301EAC3CFB51A7BD9FBE0BBD9988C93CFA0188BD4012893D41C6803DCB87ECBC20A0053D7855E73C18C7D7BD9AD8993DA851DABC436965BC67DC9E3D85BE2CBDF453863DE6C301BD65D9033DF54D73BDA7B08B3DE57A82BC4FEC1B3D730F55BDF28C653D6DBBBC3C2F4AEF398ED4C83D20A1723D0005C43D74A3F33C7E74A0BD9ED1583D206ED9BC2BEBEDBB2D59803D72F6A63DE9DD853D3C118F3CBC07B1BC1AD663BDF1B4FFBC6D2D9FBDE0E1D4BC7E3577BD9156863C2BF8C63D6B42DFBC7C2B55BDB514293C6C39D0BC04D583BC5C632D3D620991BC28CE123C26E7A1BD1829CBBC5A8DAEBD773CBEBCF0FD25BD15E6053D46A18ABD479963BD62AB3C3D71458BBD1BB4D3BC8B238BBD63349EBC65370C3DBBA0883D77C29A3B8BAAEBBCE93C1A3D4145C4BC9BE893BDAB36AE3DDC25E1BD86837A3D3D6A8BBC17437EBDEE7C913C4B2E05BCC242913BB6CF8ABDA5E8703D829034BACBD2353DA7BB00BDA0259C3DD20F353DACCA9ABD750F80BD2B2D4B3C95A1C93DA8BC013DEC6EED3AEB27B6BC1DBF103D1C3B15BD2389BCBB2AD4F7B858F5333D9B9AAA3CFCB5A3BC64F390BBB1AD51BB6CE0233D4547AA3D0263A43D909DFD3C380E5D3D27301ABD0DC6763DB835B9BD06E6D83CE2332F3D58BDC93DB1FB90BD0CBE4FBDCBA32FBD62367C3D337385BD99CFC73D9BC6813CF91C353D150A1CBD592AAC3D340B02BC642F263D94672ABD9AF8C8BC3D799A3B39A539BD25CFA2BB96F065BD7B0E943DB82D793D3BB530BDBDDC13BCE7F675BD882A8EBD39C090BA6648A93C8358A6BD498B2CBDDCF5CE3C4F764CBC6127AABD1DC36E3C24B98ABD38106E3DD3AA473D1142B8BB444AB5BC87B10DBA31779DBC9B68823DA84D413DCB72933D6CEC14BC4213123D7755B4BDBB525A3DD60EA7BD4F05593DF35B9FBD05D67CBD771B86BD07DD4CBDD59D3ABDB17526BDD31F8FBB9AD6483D4EC096BDB31027BD3578CC3D9922FABC1D1133BD567C723D3E95AFBD6F5625BD72DEB63C19E513BDE09D80BDEBFFA03BF96594BD48302E3D61CE8FBD8C43893C6FC05B3DE87330BD80C79B3CE74E913A5B1578BDB157B63C0AE9B63C4D1C33BD00ACB53CFC022ABD048244BCEB5B98BD39E08A3C3F9D503BB429763B963CC2BDD17A7B3D02981DBD01BA8DBDA9DFBABDEDD8EDBA0411B23C490B90BC21516CBC67A15DBDA99903BD722CDBBB47F68FBD1FFB743BA0C183BDC2911F3D89007D3CC5667EBD6FD0573CF273013DA9ED63BC132E91BD978E7CBD70CB39BD8191B6BD3C351ABD9A53B2BD619E58BCC0318CBDEE10C2BDFFD9863DA764F63C3DEA853C8439B2BC82B00B3C75EA8E3CD5CA773CA01A17BC0EFD5EBCABAE30BDC365D43CF5784A3D323CDDBC7390883DF2E0113D707CFEBB03C6073D7799443DEFF156BD811ECFBB38734B3C1C6B98BC2F8E93BDC34C033DCC46E93C3B8130BD489D763DBA0E513D36AFA3BD3A5B453D29E682BC5ABF8A3CCFC7B3BD7120CB3AB4833C3BAEA9CFBCEE079DBDC5239BBD37846DBB134CCABCAEFB163D46755FBD7505AABDD45B00BD9A4A19BDEF42633D9F50723D5B5294BD86EC90BCE0489F3DD3B7933D92C9B03D65AA753D24FFC1BC677E3BBD0A85603C3452CEBCE6B431BD3E1416BD2FBDDA3A68C1C03CA79D71BDAFEE3DBDE6318D3CA941953DC23C903DFFE7603D7C0F803DEF22BE3D5A7C393D3E73CFBC19B2FEBC384CC33DEF8D89BDEBC5D63CC1A0963C5BFD4B3D98C53C3DF97E5E3D85A7533C94C8883D9CC3653D75FA67BD39B7EEBC040B0BBBCC2A763D0F0AA53D80428B3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: tensor<784x128xf32> attributes {sym_visibility = "private"}
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-  flow.variable @"__iree_flow___sm_node24__model.layer-2.kernel" dense<"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tensor<128x10xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node25__model.layer-2.bias" dense<[-0.11818973, 0.115988247, 0.0210834835, -0.0308276638, 0.0101165017, 0.119799189, 0.00523598073, 0.117924452, -0.217200637, -0.0239296928]> : tensor<10xf32> attributes {sym_visibility = "private"}
+  util.global private @"__iree_flow___sm_node17__model.layer-1.kernel" = dense<"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C2DE4F23DC327783DD7DAE3BCB2EEC63DB689BC3D9C8B273DE71AE9BC6D15923DD84102BDB02154BD4AC1B03D4A93AFBC95446ABC39C089BDB2510DBEBB7DE0BCAEDBEABB266F6B3B533F323CB9E38CBD21B6E73D87BF8EBDC69D383D6EECA63D87B01B3B0F8AADBDC0AE013DD682013D83F464BD447B74BDE37AAB3C833762BDDB5E8CBC4E1A8D3CE822F6BD6C6E15BD637876BC8B84FABAF98B2C3EDF34CF3CEB5EC9BB3EF7453D49870E3D4E05DEBC177F5BBDC57C09BD059B373D65CCA1BD0EC2AEBDC443A3BD0182AD3BEE77483DA078163EDB8FD1BD1F76773CBE22813DB816B4BC5ADA5F3D90ACE33DC949823D3ADA2DBDFD628BBDF44B14BCF7832A3D13A9CDBB9FB949BD3A24443A0652943D1A00D13D3910A63D1492A83CE5A450BDCE48A1BDE9A7AD3BA59DA0BDD066A73D809100BDD8E172BD88CCB1BB5A4A1A3E33A7493CB59171BDBC7DDCBD24F4A3BD9E262E3D346918BDDA5028BDEC38973D7059D73D6625603D860BDB3BF721B53D4881B33DBC57A6BD6952E9BD084F473DB1D6543D09236A3B581735BD0D8C42BD4C426C3CC698193D5B681FBD7A2840BD75D084BD7A02D0BD92EC0E3DEC072F3DEE9B27BD2908C3BD8B0BBC3CC81C46BCBF2660BC2803BBBD94B8B0BC3E2D83BD2CBB3A3DFDF5F53B848B68BCF2678FBD5BC62DBCE10D7DBCE1A1A8BCDFB2E9BC2F1EF1BCE48EB13DEA9EB8BD41CF333DF6624EBDBBA5633DC55A813C99B4023C73A1553DD7840F3D52C424BDE3EBC63CC4365D3D04ED85BC6967983D185BA03DE95516BD3D575DBD91B948BD534400BDF609D83DA59A573DAC96A2BD90C930BD626CC43D7606123DD3D7813C6F78593AF6688B3BE02BA2BD9FCFC93C7C91823DE025B93D6817763DAEE62BBDA5E21DBD673948BDEED4773D9F5397BDCD1395BDD8616CBDC3957BBB0C78C33DEDCE983D9B911C3CF013DABC6695063DD2F283BD91CA28BC2ED875BD716ABA3B3EF3C9BB75F7A5BD978B803B19A01D3E71FFE83C19F2853DC98CC8BD27E1CC3DB2598CB919ACFDBC88927E39BC6FD73CDDA0A63D782B463DF2C183BD3CB5A5BB75063EBD96C4C23D5151D5BBA1A1ED3C9E56143C1DCC8C3D8B569DBC5815E23D6C35803DCB0A7E3C0D2F10BC907E01BEA0F5343B8B540BBDC7B109BDA5C2B8BBFC10053EA3B8E13C60E9C0BC7449963BC61067BCE609A93D890FEA3DD9E051BC7B54143E08C1103E56F518BC9356063CDB57C1BCB9D96D3DF9BAACBDCC460DBEEA0E023D153B55BD7352B03C6C2CD13C9F84A7BD31FEDABCC3729E3D8AB9FABC8D12C9BCA9AA3BBD8D3281BB7DECCBBB8F9C813C69E926BD27AF353DA1CE81BC0969C8BC00D4A6BDC872033B24EDD0BC9FC27B399279013D1D49D43CA17289BD95A53A3DF7D8A0BD8CD63ABDA9BBB5BC4F6B60BD33880CBDF4C1723B6F0767BDF812F93B7C086CBB246DF23D2EB963BDC253A13C82CA953DEFD156BD9771C13CEF9CA2BCB5A05E3D85FB6C3D9FB6113CE513443DC4A506BD6043A83CAC85D8BDAC3640BD9512C6BCAE69AFBB12B8523C18A7C4BBDBFC8E3DB17653BD32F4A33C01FB953C80CA293DE6DA1DBC3B52BDBC5B66123CEBCF653D307649BD19E6C33DD98387BD9B888E3C468EB53D1A399BBD741C47BD7EBAB5BDCA72713D2DD0093EB10127BCE0C5FFBCA3EC7DBCCB5F913D8AA4F23B89087C3D7B88B4BDF9FEAB3B414C48BDFA3F04BC2FFD063D8A2BEE3D2D6E013D2B73463C9673EABD0CC5B13DECB4043EDCF0E7BC3D41A43DD7382ABC7E591DBC930A89BD948E15BD5ADD92BB656B73BD63EE4CBDF2B999BDB1A95A3D421FA33CDE6E693D7C1D813D1D64223D1EAEA33CF1202DBD77062EBD0ED1EDBD032D453C8B97513DE3B76F3DA1AB783DE13B15BD7A3B09BC953DD2BC6299F43C0402A7BC6C95F53C26CB4C3CB61338BD5B4B963D16E46B3DE725033EC684513D2F24643DE4E16C3D2995EEBCA82096BD106A293CC5F8F93C78F2E4BC1DC069BC8DABDA3C06620ABC75DBA33D4D22303D48C8D5BDF99B9FBCB8984D3D21D6D1BCF6CED23CA217A2BD2D94243DB25BC6BC923B333DCFADED3CE5E973BDCC2852BD7A00713DB8A21EBD74E8723D3547623C99423DBD9FFFB13D94051CBD677260BCCF3D1F3D0537043DA74C07BDD9BB30BDF1D7603D8256853D5D2D9D3B88F0B73B946CE33C1B5970BD461B523DFD6AFC3B33DC9DBC5BB1C9BD9EF9D5BCBBEA32BD0AEE8DBDE281CDBC41B56DBDF1446A3DE7EF6A3D9523443D6BFB9CBCA23D05BDA801B13C33A147BDFD0BAD3D725B87BC42E1C53C0B933D3D3786AF3DB5834BBAFE9E7BBDC5D5D4BC2EEA4BBD3072FEBCC95BA8BCA7044BBC09C205BC610286BBFD960BBD8B1868BDEB4DA73D93CDD33CD697CE3C30449D3C717D7F3B5EE0953D318D85BB2CF529BC1A7D013C65FF00BDA769EBBCB8D3CB3D484017BD8A1A403D6871A13D4546AD3DE038B4BC902F98BCADC7D23D210AA03CB78775BD3994943D873578BDDA9E86BD3C9657BD8C52873D431C893C110BE33B894D94BDFE64BBBC75B1AB3DE08DB7BD1950C63C436E46BDA1B46CBCDFAF793CD18259BC7F6994BDEC071A3D6089313D56DB1FBDFD572B3DD847B4BD4DA3D7BD8B030D3D015CFABC482C92BD43B3263DC17C163E860E9D3D235023BCB7DB0A3EA2B0D33D2F508F3B8DC19E3C06450B3CB20181BD0FA0413C8743643D233AD13C302DB6BD00217039D40B70BDCE6135BC47730A3D3D5A893BAA5BD43C9EEB243D1886BABD09FC5BBD4FE38ABD4AC9213D7D65AD3DCB7AB0BD2DE985BDB54193BDC6E7863D566E063D4D4592BDC992343DD677033D1A48F7BA99702A3DA3F0013D640E6F3CB0FFC4BC9F725BBDA906613D1CD5F43CCEFEAA3D523F2CBD2E22E23B4C620CBC61E75CBDF1CE0DBD57D2CCBC7E5BCCBD3878263C18A6093D909C283CFFF1EFBDD74FFF3BD41944BD76806A3DD2570D3D3F42A33D2D6CE13CA766ECBCB96ABD3C20E94DBD6232513CA08FA5BDFC18A4BC6452DBBC4293C4BC53DF423C422F10BD44AB6DBD2FBC583DBEAECBBDDF7700BDECC1833DD87417BB78B66E3D25F289BDF26CF2BC662980BD905A4ABD9C10903CA648D13CEE8E8ABD9A205F3DD7B1DDBBE0CEC13D4EA18BBC6850063D4CDB313CCA9F073DB2A687BDB729913D3EDB1FBDD0EE5A3DBD1A803D3685B03D60A3083D500A443C8B2A473C74130ABDBB8F153D9539AD3DA0E9B2BD6856C2BCF273D73C65F1B83D50E36DBD0E647BBD2F7FDD3C58BE8D3D05D239BD4607B3BD1B64103D1FB36EBD20C0DCBC7B8FA13DF99AB8BD72262EBCAED9C13C585A2B3D51F436BD113F32BDBF0B44BC75D9C0BD25E914BD5E4ACABD956D793C62782FBD95A04E3DA46B513D4DFA83BD68CAE53AC8E8873D7B0321BC740B27BD29194EBDF3852E3DC7545CBDA60E873CC9B8E23D18ABD43C00CFB43DB23C713D4D180CBCF44DB23D375852394ED70ABD8C3A393D692DCABD4FA9523DD756DD3C4CAE0E3B79DE143DD2C511BD54BE18BD8D422CB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"> : tensor<784x128xf32>
+  util.global private @"__iree_flow___sm_node18__model.layer-1.bias" = dense<"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tensor<128xf32>
+  util.global private @"__iree_flow___sm_node24__model.layer-2.kernel" = dense<"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tensor<128x10xf32>
+  util.global private @"__iree_flow___sm_node25__model.layer-2.bias" = dense<[-0.11818973, 0.115988247, 0.0210834835, -0.0308276638, 0.0101165017, 0.119799189, 0.00523598073, 0.117924452, -0.217200637, -0.0239296928]> : tensor<10xf32>
   func @predict(%arg0: tensor<1x28x28x1xf32>) -> tensor<1x10xf32> attributes {iree.module.export, iree.reflection = {abi = "sip", abiv = 1 : i32, sip = "I8!S5!k0_0R3!_0"}} {
-    %0 = flow.variable.address @"__iree_flow___sm_node17__model.layer-1.kernel" : !util.ptr<tensor<784x128xf32>>
-    %1 = flow.variable.address @"__iree_flow___sm_node18__model.layer-1.bias" : !util.ptr<tensor<128xf32>>
-    %2 = flow.variable.address @"__iree_flow___sm_node24__model.layer-2.kernel" : !util.ptr<tensor<128x10xf32>>
-    %3 = flow.variable.address @"__iree_flow___sm_node25__model.layer-2.bias" : !util.ptr<tensor<10xf32>>
+    %0 = util.global.address @"__iree_flow___sm_node17__model.layer-1.kernel" : !util.ptr<tensor<784x128xf32>>
+    %1 = util.global.address @"__iree_flow___sm_node18__model.layer-1.bias" : !util.ptr<tensor<128xf32>>
+    %2 = util.global.address @"__iree_flow___sm_node24__model.layer-2.kernel" : !util.ptr<tensor<128x10xf32>>
+    %3 = util.global.address @"__iree_flow___sm_node25__model.layer-2.bias" : !util.ptr<tensor<10xf32>>
     %4 = mhlo.constant dense<0.000000e+00> : tensor<1x128xf32>
     %5 = mhlo.constant dense<0xFF800000> : tensor<f32>
     %6 = mhlo.constant dense<0.000000e+00> : tensor<f32>
-    %7 = flow.variable.load.indirect %3 : !util.ptr<tensor<10xf32>> -> tensor<10xf32>
-    %8 = flow.variable.load.indirect %2 : !util.ptr<tensor<128x10xf32>> -> tensor<128x10xf32>
-    %9 = flow.variable.load.indirect %1 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %10 = flow.variable.load.indirect %0 : !util.ptr<tensor<784x128xf32>> -> tensor<784x128xf32>
+    %7 = util.global.load.indirect %3 : !util.ptr<tensor<10xf32>> -> tensor<10xf32>
+    %8 = util.global.load.indirect %2 : !util.ptr<tensor<128x10xf32>> -> tensor<128x10xf32>
+    %9 = util.global.load.indirect %1 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %10 = util.global.load.indirect %0 : !util.ptr<tensor<784x128xf32>> -> tensor<784x128xf32>
     %11 = "mhlo.reshape"(%arg0) : (tensor<1x28x28x1xf32>) -> tensor<1x784xf32>
     %12 = "mhlo.dot"(%11, %10) : (tensor<1x784xf32>, tensor<784x128xf32>) -> tensor<1x128xf32>
     %13 = "mhlo.broadcast_in_dim"(%9) {broadcast_dimensions = dense<1> : tensor<1xi64>} : (tensor<128xf32>) -> tensor<1x128xf32>
diff --git a/iree/samples/variables_and_state/variables_and_state.ipynb b/iree/samples/variables_and_state/variables_and_state.ipynb
index 03732d9..3c16e93 100644
--- a/iree/samples/variables_and_state/variables_and_state.ipynb
+++ b/iree/samples/variables_and_state/variables_and_state.ipynb
@@ -172,7 +172,7 @@
         "clear_output()  # Skip over TensorFlow's output.\n",
         "\n",
         "# Print the imported MLIR to see how the compiler views this TensorFlow program.\n",
-        "# Note IREE's `flow.variable` ops and the public (exported) functions.\n",
+        "# Note IREE's `util.global` ops and the public (exported) functions.\n",
         "print(\"Counter MLIR:\\n```\\n%s```\\n\" % compiler_module.decode(\"utf-8\"))\n",
         "\n",
         "# Save the imported MLIR to disk.\n",
@@ -190,36 +190,36 @@
             "```\n",
             "#map = affine_map<() -> ()>\n",
             "module  {\n",
-            "  flow.variable @counter mutable dense<0> : tensor<i32> attributes {sym_visibility = \"private\"}\n",
+            "  util.global private mutable @counter = dense<0> : tensor<i32>\n",
             "  func @add_to_value(%arg0: !hal.buffer_view) attributes {iree.abi = \"{\\22a\\22:[[\\22ndarray\\22,\\22i32\\22,0]],\\22r\\22:[],\\22v\\22:1}\"} {\n",
             "    %0 = hal.tensor.cast %arg0 : !hal.buffer_view -> tensor<i32>\n",
             "    call @__inference_add_to_value_100(%0) : (tensor<i32>) -> ()\n",
             "    return\n",
             "  }\n",
             "  func private @__inference_add_to_value_100(%arg0: tensor<i32> {tf._user_specified_name = \"x\"}) attributes {tf._construction_context = \"kEagerRuntime\", tf._input_shapes = [#tf.shape<>, #tf.shape<>], tf.signature.is_stateful} {\n",
-            "    %0 = flow.variable.load @counter : tensor<i32>\n",
+            "    %0 = util.global.load @counter : tensor<i32>\n",
             "    %1 = linalg.init_tensor [] : tensor<i32>\n",
             "    %2 = linalg.generic {indexing_maps = [#map, #map, #map], iterator_types = []} ins(%0, %arg0 : tensor<i32>, tensor<i32>) outs(%1 : tensor<i32>) {\n",
             "    ^bb0(%arg1: i32, %arg2: i32, %arg3: i32):  // no predecessors\n",
             "      %3 = addi %arg1, %arg2 : i32\n",
             "      linalg.yield %3 : i32\n",
             "    } -> tensor<i32>\n",
-            "    flow.variable.store %2, @counter : tensor<i32>\n",
+            "    util.global.store %2, @counter : tensor<i32>\n",
             "    return\n",
             "  }\n",
             "  func @get_value() -> !hal.buffer_view attributes {iree.abi = \"{\\22a\\22:[],\\22r\\22:[[\\22ndarray\\22,\\22i32\\22,0]],\\22v\\22:1}\"} {\n",
-            "    %0 = flow.variable.load @counter : tensor<i32>\n",
+            "    %0 = util.global.load @counter : tensor<i32>\n",
             "    %1 = hal.tensor.cast %0 : tensor<i32> -> !hal.buffer_view\n",
             "    return %1 : !hal.buffer_view\n",
             "  }\n",
             "  func @reset_value() attributes {iree.abi = \"{\\22a\\22:[],\\22r\\22:[],\\22v\\22:1}\"} {\n",
             "    %cst = constant dense<0> : tensor<i32>\n",
-            "    flow.variable.store %cst, @counter : tensor<i32>\n",
+            "    util.global.store %cst, @counter : tensor<i32>\n",
             "    return\n",
             "  }\n",
             "  func @set_value(%arg0: !hal.buffer_view) attributes {iree.abi = \"{\\22a\\22:[[\\22ndarray\\22,\\22i32\\22,0]],\\22r\\22:[],\\22v\\22:1}\"} {\n",
             "    %0 = hal.tensor.cast %arg0 : !hal.buffer_view -> tensor<i32>\n",
-            "    flow.variable.store %0, @counter : tensor<i32>\n",
+            "    util.global.store %0, @counter : tensor<i32>\n",
             "    return\n",
             "  }\n",
             "}\n",
@@ -410,4 +410,4 @@
       "outputs": []
     }
   ]
-}
\ No newline at end of file
+}
diff --git a/iree/samples/vision/CMakeLists.txt b/iree/samples/vision/CMakeLists.txt
index 7f99950..5762b5b 100644
--- a/iree/samples/vision/CMakeLists.txt
+++ b/iree/samples/vision/CMakeLists.txt
@@ -17,7 +17,7 @@
   C_IDENTIFIER
     "mnist_bytecode_module_c"
   FLAGS
-    "--iree-input-type=mhlo"
+    "-iree-input-type=mhlo"
     "-iree-mlir-to-vm-bytecode-module"
     "-iree-hal-target-backends=dylib-llvm-aot"
   PUBLIC
diff --git a/iree/test/e2e/models/bert_encoder_unrolled_fake_weights.mlir b/iree/test/e2e/models/bert_encoder_unrolled_fake_weights.mlir
index 4fc01be..7d01f2f 100644
--- a/iree/test/e2e/models/bert_encoder_unrolled_fake_weights.mlir
+++ b/iree/test/e2e/models/bert_encoder_unrolled_fake_weights.mlir
@@ -1,2236 +1,2236 @@
 // MobileBert encoder model with placeholder weights, for testing.
 
 module {
-  flow.variable @"__iree_flow_bert/embeddings/FakeLayerNorm/beta" dense<1.0> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/embeddings/FakeLayerNorm/gamma" dense<0.4> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/embeddings/embedding_transformation/bias" dense<0.1> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/embeddings/embedding_transformation/kernel" dense<0.0001> : tensor<384x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/embeddings/position_embeddings" dense<0.0> : tensor<512x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/embeddings/token_type_embeddings" dense<0.0> : tensor<2x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/embeddings/word_embeddings" dense<0.0> : tensor<30522x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/attention/output/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/attention/output/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/attention/output/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/attention/output/dense/kernel" dense<0.0001> : tensor<128x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/attention/self/key/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/attention/self/key/kernel" dense<0.0001> : tensor<128x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/attention/self/query/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/attention/self/query/kernel" dense<0.0001> : tensor<128x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/attention/self/value/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/attention/self/value/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/bottleneck/attention/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/bottleneck/attention/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/bottleneck/attention/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/bottleneck/attention/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/bottleneck/input/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/bottleneck/input/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/bottleneck/input/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/bottleneck/input/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/ffn_layer_0/intermediate/dense/bias" dense<0.1> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/ffn_layer_0/intermediate/dense/kernel" dense<0.0001> : tensor<128x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/ffn_layer_0/output/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/ffn_layer_0/output/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/ffn_layer_0/output/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/ffn_layer_0/output/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/ffn_layer_1/intermediate/dense/bias" dense<0.1> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/ffn_layer_1/intermediate/dense/kernel" dense<0.0001> : tensor<128x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/ffn_layer_1/output/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/ffn_layer_1/output/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/ffn_layer_1/output/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/ffn_layer_1/output/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/ffn_layer_2/intermediate/dense/bias" dense<0.1> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/ffn_layer_2/intermediate/dense/kernel" dense<0.0001> : tensor<128x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/ffn_layer_2/output/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/ffn_layer_2/output/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/ffn_layer_2/output/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/ffn_layer_2/output/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/intermediate/dense/bias" dense<0.1> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/intermediate/dense/kernel" dense<0.0001> : tensor<128x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/output/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/output/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/output/bottleneck/FakeLayerNorm/beta" dense<1.0> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/output/bottleneck/FakeLayerNorm/gamma" dense<0.4> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/output/bottleneck/dense/bias" dense<0.1> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/output/bottleneck/dense/kernel" dense<0.0001> : tensor<128x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/output/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_0/output/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/attention/output/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/attention/output/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/attention/output/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/attention/output/dense/kernel" dense<0.0001> : tensor<128x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/attention/self/key/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/attention/self/key/kernel" dense<0.0001> : tensor<128x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/attention/self/query/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/attention/self/query/kernel" dense<0.0001> : tensor<128x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/attention/self/value/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/attention/self/value/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/bottleneck/attention/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/bottleneck/attention/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/bottleneck/attention/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/bottleneck/attention/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/bottleneck/input/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/bottleneck/input/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/bottleneck/input/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/bottleneck/input/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/ffn_layer_0/intermediate/dense/bias" dense<0.1> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/ffn_layer_0/intermediate/dense/kernel" dense<0.0001> : tensor<128x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/ffn_layer_0/output/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/ffn_layer_0/output/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/ffn_layer_0/output/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/ffn_layer_0/output/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/ffn_layer_1/intermediate/dense/bias" dense<0.1> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/ffn_layer_1/intermediate/dense/kernel" dense<0.0001> : tensor<128x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/ffn_layer_1/output/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/ffn_layer_1/output/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/ffn_layer_1/output/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/ffn_layer_1/output/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/ffn_layer_2/intermediate/dense/bias" dense<0.1> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/ffn_layer_2/intermediate/dense/kernel" dense<0.0001> : tensor<128x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/ffn_layer_2/output/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/ffn_layer_2/output/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/ffn_layer_2/output/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/ffn_layer_2/output/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/intermediate/dense/bias" dense<0.1> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/intermediate/dense/kernel" dense<0.0001> : tensor<128x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/output/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/output/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/output/bottleneck/FakeLayerNorm/beta" dense<1.0> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/output/bottleneck/FakeLayerNorm/gamma" dense<0.4> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/output/bottleneck/dense/bias" dense<0.1> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/output/bottleneck/dense/kernel" dense<0.0001> : tensor<128x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/output/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_1/output/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_10/attention/output/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_10/attention/output/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_10/attention/output/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_10/attention/output/dense/kernel" dense<0.0001> : tensor<128x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_10/attention/self/key/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_10/attention/self/key/kernel" dense<0.0001> : tensor<128x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_10/attention/self/query/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_10/attention/self/query/kernel" dense<0.0001> : tensor<128x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_10/attention/self/value/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_10/attention/self/value/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_10/bottleneck/attention/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_10/bottleneck/attention/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_10/bottleneck/attention/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_10/bottleneck/attention/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_10/bottleneck/input/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_10/bottleneck/input/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_10/bottleneck/input/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_10/bottleneck/input/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_10/ffn_layer_0/intermediate/dense/bias" dense<0.1> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_10/ffn_layer_0/intermediate/dense/kernel" dense<0.0001> : tensor<128x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_10/ffn_layer_0/output/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_10/ffn_layer_0/output/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_10/ffn_layer_0/output/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_10/ffn_layer_0/output/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_10/ffn_layer_1/intermediate/dense/bias" dense<0.1> : tensor<512xf32> attributes {sym_visibility = "private"}
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-  flow.variable @"__iree_flow_bert/encoder/layer_7/attention/output/dense/kernel" dense<0.0001> : tensor<128x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/attention/self/key/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/attention/self/key/kernel" dense<0.0001> : tensor<128x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/attention/self/query/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/attention/self/query/kernel" dense<0.0001> : tensor<128x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/attention/self/value/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/attention/self/value/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/bottleneck/attention/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/bottleneck/attention/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/bottleneck/attention/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/bottleneck/attention/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/bottleneck/input/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/bottleneck/input/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/bottleneck/input/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/bottleneck/input/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/ffn_layer_0/intermediate/dense/bias" dense<0.1> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/ffn_layer_0/intermediate/dense/kernel" dense<0.0001> : tensor<128x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/ffn_layer_0/output/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/ffn_layer_0/output/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/ffn_layer_0/output/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/ffn_layer_0/output/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/ffn_layer_1/intermediate/dense/bias" dense<0.1> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/ffn_layer_1/intermediate/dense/kernel" dense<0.0001> : tensor<128x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/ffn_layer_1/output/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/ffn_layer_1/output/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/ffn_layer_1/output/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/ffn_layer_1/output/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/ffn_layer_2/intermediate/dense/bias" dense<0.1> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/ffn_layer_2/intermediate/dense/kernel" dense<0.0001> : tensor<128x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/ffn_layer_2/output/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/ffn_layer_2/output/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/ffn_layer_2/output/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/ffn_layer_2/output/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/intermediate/dense/bias" dense<0.1> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/intermediate/dense/kernel" dense<0.0001> : tensor<128x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/output/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/output/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/output/bottleneck/FakeLayerNorm/beta" dense<1.0> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/output/bottleneck/FakeLayerNorm/gamma" dense<0.4> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/output/bottleneck/dense/bias" dense<0.1> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/output/bottleneck/dense/kernel" dense<0.0001> : tensor<128x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/output/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_7/output/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/attention/output/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/attention/output/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/attention/output/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/attention/output/dense/kernel" dense<0.0001> : tensor<128x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/attention/self/key/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/attention/self/key/kernel" dense<0.0001> : tensor<128x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/attention/self/query/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/attention/self/query/kernel" dense<0.0001> : tensor<128x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/attention/self/value/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/attention/self/value/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/bottleneck/attention/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/bottleneck/attention/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/bottleneck/attention/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/bottleneck/attention/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/bottleneck/input/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/bottleneck/input/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/bottleneck/input/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/bottleneck/input/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/ffn_layer_0/intermediate/dense/bias" dense<0.1> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/ffn_layer_0/intermediate/dense/kernel" dense<0.0001> : tensor<128x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/ffn_layer_0/output/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/ffn_layer_0/output/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/ffn_layer_0/output/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/ffn_layer_0/output/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/ffn_layer_1/intermediate/dense/bias" dense<0.1> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/ffn_layer_1/intermediate/dense/kernel" dense<0.0001> : tensor<128x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/ffn_layer_1/output/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/ffn_layer_1/output/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/ffn_layer_1/output/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/ffn_layer_1/output/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/ffn_layer_2/intermediate/dense/bias" dense<0.1> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/ffn_layer_2/intermediate/dense/kernel" dense<0.0001> : tensor<128x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/ffn_layer_2/output/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/ffn_layer_2/output/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/ffn_layer_2/output/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/ffn_layer_2/output/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/intermediate/dense/bias" dense<0.1> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/intermediate/dense/kernel" dense<0.0001> : tensor<128x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/output/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/output/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/output/bottleneck/FakeLayerNorm/beta" dense<1.0> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/output/bottleneck/FakeLayerNorm/gamma" dense<0.4> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/output/bottleneck/dense/bias" dense<0.1> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/output/bottleneck/dense/kernel" dense<0.0001> : tensor<128x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/output/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_8/output/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/attention/output/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/attention/output/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/attention/output/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/attention/output/dense/kernel" dense<0.0001> : tensor<128x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/attention/self/key/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/attention/self/key/kernel" dense<0.0001> : tensor<128x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/attention/self/query/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/attention/self/query/kernel" dense<0.0001> : tensor<128x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/attention/self/value/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/attention/self/value/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/bottleneck/attention/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/bottleneck/attention/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/bottleneck/attention/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/bottleneck/attention/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/bottleneck/input/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/bottleneck/input/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/bottleneck/input/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/bottleneck/input/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/ffn_layer_0/intermediate/dense/bias" dense<0.1> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/ffn_layer_0/intermediate/dense/kernel" dense<0.0001> : tensor<128x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/ffn_layer_0/output/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/ffn_layer_0/output/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/ffn_layer_0/output/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/ffn_layer_0/output/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/ffn_layer_1/intermediate/dense/bias" dense<0.1> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/ffn_layer_1/intermediate/dense/kernel" dense<0.0001> : tensor<128x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/ffn_layer_1/output/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/ffn_layer_1/output/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/ffn_layer_1/output/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/ffn_layer_1/output/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/ffn_layer_2/intermediate/dense/bias" dense<0.1> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/ffn_layer_2/intermediate/dense/kernel" dense<0.0001> : tensor<128x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/ffn_layer_2/output/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/ffn_layer_2/output/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/ffn_layer_2/output/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/ffn_layer_2/output/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/intermediate/dense/bias" dense<0.1> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/intermediate/dense/kernel" dense<0.0001> : tensor<128x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/output/FakeLayerNorm/beta" dense<1.0> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/output/FakeLayerNorm/gamma" dense<0.4> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/output/bottleneck/FakeLayerNorm/beta" dense<1.0> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/output/bottleneck/FakeLayerNorm/gamma" dense<0.4> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/output/bottleneck/dense/bias" dense<0.1> : tensor<512xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/output/bottleneck/dense/kernel" dense<0.0001> : tensor<128x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/output/dense/bias" dense<0.1> : tensor<128xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_bert/encoder/layer_9/output/dense/kernel" dense<0.0001> : tensor<512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow_cls/squad/output_bias" dense<0.1> : tensor<2xf32> attributes {sym_visibility = "private"}
-  flow.variable @"__iree_flow_cls/squad/output_weights" dense<1.0> : tensor<2x512xf32> attributes {sym_visibility = "private"}
+  util.global private @"__iree_flow_bert/embeddings/FakeLayerNorm/beta" = dense<1.0> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/embeddings/FakeLayerNorm/gamma" = dense<0.4> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/embeddings/embedding_transformation/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/embeddings/embedding_transformation/kernel" {noinline} = dense<0.0001> : tensor<384x512xf32>
+  util.global private @"__iree_flow_bert/embeddings/position_embeddings" {noinline} = dense<0.0> : tensor<512x512xf32>
+  util.global private @"__iree_flow_bert/embeddings/token_type_embeddings" {noinline} = dense<0.0> : tensor<2x512xf32>
+  util.global private @"__iree_flow_bert/embeddings/word_embeddings" {noinline} = dense<0.0> : tensor<30522x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/attention/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/attention/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/attention/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/attention/output/dense/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/attention/self/key/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/attention/self/key/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/attention/self/query/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/attention/self/query/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/attention/self/value/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/attention/self/value/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/bottleneck/attention/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/bottleneck/attention/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/bottleneck/attention/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/bottleneck/attention/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/bottleneck/input/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/bottleneck/input/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/bottleneck/input/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/bottleneck/input/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/ffn_layer_0/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/ffn_layer_0/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/ffn_layer_0/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/ffn_layer_0/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/ffn_layer_0/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/ffn_layer_0/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/ffn_layer_1/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/ffn_layer_1/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/ffn_layer_1/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/ffn_layer_1/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/ffn_layer_1/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/ffn_layer_1/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/ffn_layer_2/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/ffn_layer_2/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/ffn_layer_2/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/ffn_layer_2/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/ffn_layer_2/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/ffn_layer_2/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/output/bottleneck/FakeLayerNorm/beta" = dense<1.0> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/output/bottleneck/FakeLayerNorm/gamma" = dense<0.4> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/output/bottleneck/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/output/bottleneck/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_0/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/attention/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/attention/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/attention/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/attention/output/dense/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/attention/self/key/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/attention/self/key/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/attention/self/query/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/attention/self/query/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/attention/self/value/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/attention/self/value/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/bottleneck/attention/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/bottleneck/attention/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/bottleneck/attention/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/bottleneck/attention/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/bottleneck/input/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/bottleneck/input/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/bottleneck/input/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/bottleneck/input/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/ffn_layer_0/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/ffn_layer_0/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/ffn_layer_0/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/ffn_layer_0/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/ffn_layer_0/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/ffn_layer_0/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/ffn_layer_1/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/ffn_layer_1/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/ffn_layer_1/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/ffn_layer_1/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/ffn_layer_1/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/ffn_layer_1/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/ffn_layer_2/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/ffn_layer_2/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/ffn_layer_2/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/ffn_layer_2/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/ffn_layer_2/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/ffn_layer_2/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/output/bottleneck/FakeLayerNorm/beta" = dense<1.0> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/output/bottleneck/FakeLayerNorm/gamma" = dense<0.4> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/output/bottleneck/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/output/bottleneck/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_1/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/attention/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/attention/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/attention/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/attention/output/dense/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/attention/self/key/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/attention/self/key/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/attention/self/query/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/attention/self/query/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/attention/self/value/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/attention/self/value/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/bottleneck/attention/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/bottleneck/attention/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/bottleneck/attention/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/bottleneck/attention/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/bottleneck/input/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/bottleneck/input/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/bottleneck/input/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/bottleneck/input/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/ffn_layer_0/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/ffn_layer_0/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/ffn_layer_0/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/ffn_layer_0/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/ffn_layer_0/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/ffn_layer_0/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/ffn_layer_1/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/ffn_layer_1/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/ffn_layer_1/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/ffn_layer_1/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/ffn_layer_1/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/ffn_layer_1/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/ffn_layer_2/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/ffn_layer_2/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/ffn_layer_2/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/ffn_layer_2/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/ffn_layer_2/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/ffn_layer_2/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/output/bottleneck/FakeLayerNorm/beta" = dense<1.0> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/output/bottleneck/FakeLayerNorm/gamma" = dense<0.4> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/output/bottleneck/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/output/bottleneck/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_10/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/attention/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/attention/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/attention/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/attention/output/dense/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/attention/self/key/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/attention/self/key/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/attention/self/query/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/attention/self/query/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/attention/self/value/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/attention/self/value/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/bottleneck/attention/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/bottleneck/attention/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/bottleneck/attention/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/bottleneck/attention/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/bottleneck/input/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/bottleneck/input/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/bottleneck/input/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/bottleneck/input/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/ffn_layer_0/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/ffn_layer_0/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/ffn_layer_0/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/ffn_layer_0/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/ffn_layer_0/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/ffn_layer_0/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/ffn_layer_1/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/ffn_layer_1/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/ffn_layer_1/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/ffn_layer_1/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/ffn_layer_1/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/ffn_layer_1/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/ffn_layer_2/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/ffn_layer_2/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/ffn_layer_2/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/ffn_layer_2/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/ffn_layer_2/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/ffn_layer_2/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/output/bottleneck/FakeLayerNorm/beta" = dense<1.0> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/output/bottleneck/FakeLayerNorm/gamma" = dense<0.4> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/output/bottleneck/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/output/bottleneck/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_11/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/attention/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/attention/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/attention/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/attention/output/dense/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/attention/self/key/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/attention/self/key/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/attention/self/query/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/attention/self/query/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/attention/self/value/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/attention/self/value/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/bottleneck/attention/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/bottleneck/attention/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/bottleneck/attention/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/bottleneck/attention/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/bottleneck/input/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/bottleneck/input/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/bottleneck/input/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/bottleneck/input/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/ffn_layer_0/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/ffn_layer_0/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/ffn_layer_0/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/ffn_layer_0/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/ffn_layer_0/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/ffn_layer_0/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/ffn_layer_1/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/ffn_layer_1/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/ffn_layer_1/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/ffn_layer_1/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/ffn_layer_1/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/ffn_layer_1/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/ffn_layer_2/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/ffn_layer_2/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/ffn_layer_2/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/ffn_layer_2/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/ffn_layer_2/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/ffn_layer_2/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/output/bottleneck/FakeLayerNorm/beta" = dense<1.0> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/output/bottleneck/FakeLayerNorm/gamma" = dense<0.4> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/output/bottleneck/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/output/bottleneck/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_12/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/attention/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/attention/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/attention/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/attention/output/dense/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/attention/self/key/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/attention/self/key/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/attention/self/query/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/attention/self/query/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/attention/self/value/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/attention/self/value/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/bottleneck/attention/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/bottleneck/attention/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/bottleneck/attention/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/bottleneck/attention/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/bottleneck/input/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/bottleneck/input/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/bottleneck/input/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/bottleneck/input/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/ffn_layer_0/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/ffn_layer_0/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/ffn_layer_0/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/ffn_layer_0/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/ffn_layer_0/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/ffn_layer_0/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/ffn_layer_1/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/ffn_layer_1/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/ffn_layer_1/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/ffn_layer_1/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/ffn_layer_1/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/ffn_layer_1/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/ffn_layer_2/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/ffn_layer_2/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/ffn_layer_2/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/ffn_layer_2/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/ffn_layer_2/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/ffn_layer_2/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/output/bottleneck/FakeLayerNorm/beta" = dense<1.0> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/output/bottleneck/FakeLayerNorm/gamma" = dense<0.4> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/output/bottleneck/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/output/bottleneck/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_13/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/attention/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/attention/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/attention/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/attention/output/dense/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/attention/self/key/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/attention/self/key/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/attention/self/query/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/attention/self/query/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/attention/self/value/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/attention/self/value/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/bottleneck/attention/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/bottleneck/attention/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/bottleneck/attention/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/bottleneck/attention/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/bottleneck/input/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/bottleneck/input/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/bottleneck/input/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/bottleneck/input/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/ffn_layer_0/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/ffn_layer_0/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/ffn_layer_0/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/ffn_layer_0/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/ffn_layer_0/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/ffn_layer_0/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/ffn_layer_1/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/ffn_layer_1/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/ffn_layer_1/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/ffn_layer_1/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/ffn_layer_1/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/ffn_layer_1/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/ffn_layer_2/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/ffn_layer_2/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/ffn_layer_2/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/ffn_layer_2/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/ffn_layer_2/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/ffn_layer_2/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/output/bottleneck/FakeLayerNorm/beta" = dense<1.0> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/output/bottleneck/FakeLayerNorm/gamma" = dense<0.4> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/output/bottleneck/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/output/bottleneck/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_14/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/attention/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/attention/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/attention/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/attention/output/dense/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/attention/self/key/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/attention/self/key/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/attention/self/query/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/attention/self/query/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/attention/self/value/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/attention/self/value/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/bottleneck/attention/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/bottleneck/attention/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/bottleneck/attention/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/bottleneck/attention/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/bottleneck/input/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/bottleneck/input/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/bottleneck/input/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/bottleneck/input/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/ffn_layer_0/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/ffn_layer_0/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/ffn_layer_0/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/ffn_layer_0/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/ffn_layer_0/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/ffn_layer_0/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/ffn_layer_1/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/ffn_layer_1/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/ffn_layer_1/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/ffn_layer_1/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/ffn_layer_1/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/ffn_layer_1/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/ffn_layer_2/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/ffn_layer_2/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/ffn_layer_2/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/ffn_layer_2/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/ffn_layer_2/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/ffn_layer_2/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/output/bottleneck/FakeLayerNorm/beta" = dense<1.0> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/output/bottleneck/FakeLayerNorm/gamma" = dense<0.4> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/output/bottleneck/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/output/bottleneck/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_15/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/attention/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/attention/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/attention/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/attention/output/dense/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/attention/self/key/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/attention/self/key/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/attention/self/query/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/attention/self/query/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/attention/self/value/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/attention/self/value/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/bottleneck/attention/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/bottleneck/attention/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/bottleneck/attention/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/bottleneck/attention/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/bottleneck/input/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/bottleneck/input/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/bottleneck/input/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/bottleneck/input/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/ffn_layer_0/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/ffn_layer_0/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/ffn_layer_0/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/ffn_layer_0/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/ffn_layer_0/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/ffn_layer_0/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/ffn_layer_1/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/ffn_layer_1/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/ffn_layer_1/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/ffn_layer_1/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/ffn_layer_1/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/ffn_layer_1/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/ffn_layer_2/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/ffn_layer_2/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/ffn_layer_2/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/ffn_layer_2/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/ffn_layer_2/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/ffn_layer_2/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/output/bottleneck/FakeLayerNorm/beta" = dense<1.0> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/output/bottleneck/FakeLayerNorm/gamma" = dense<0.4> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/output/bottleneck/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/output/bottleneck/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_16/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/attention/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/attention/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/attention/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/attention/output/dense/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/attention/self/key/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/attention/self/key/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/attention/self/query/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/attention/self/query/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/attention/self/value/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/attention/self/value/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/bottleneck/attention/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/bottleneck/attention/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/bottleneck/attention/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/bottleneck/attention/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/bottleneck/input/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/bottleneck/input/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/bottleneck/input/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/bottleneck/input/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/ffn_layer_0/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/ffn_layer_0/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/ffn_layer_0/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/ffn_layer_0/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/ffn_layer_0/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/ffn_layer_0/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/ffn_layer_1/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/ffn_layer_1/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/ffn_layer_1/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/ffn_layer_1/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/ffn_layer_1/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/ffn_layer_1/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/ffn_layer_2/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/ffn_layer_2/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/ffn_layer_2/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/ffn_layer_2/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/ffn_layer_2/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/ffn_layer_2/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/output/bottleneck/FakeLayerNorm/beta" = dense<1.0> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/output/bottleneck/FakeLayerNorm/gamma" = dense<0.4> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/output/bottleneck/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/output/bottleneck/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_17/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/attention/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/attention/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/attention/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/attention/output/dense/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/attention/self/key/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/attention/self/key/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/attention/self/query/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/attention/self/query/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/attention/self/value/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/attention/self/value/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/bottleneck/attention/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/bottleneck/attention/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/bottleneck/attention/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/bottleneck/attention/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/bottleneck/input/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/bottleneck/input/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/bottleneck/input/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/bottleneck/input/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/ffn_layer_0/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/ffn_layer_0/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/ffn_layer_0/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/ffn_layer_0/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/ffn_layer_0/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/ffn_layer_0/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/ffn_layer_1/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/ffn_layer_1/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/ffn_layer_1/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/ffn_layer_1/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/ffn_layer_1/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/ffn_layer_1/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/ffn_layer_2/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/ffn_layer_2/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/ffn_layer_2/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/ffn_layer_2/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/ffn_layer_2/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/ffn_layer_2/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/output/bottleneck/FakeLayerNorm/beta" = dense<1.0> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/output/bottleneck/FakeLayerNorm/gamma" = dense<0.4> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/output/bottleneck/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/output/bottleneck/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_18/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/attention/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/attention/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/attention/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/attention/output/dense/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/attention/self/key/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/attention/self/key/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/attention/self/query/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/attention/self/query/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/attention/self/value/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/attention/self/value/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/bottleneck/attention/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/bottleneck/attention/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/bottleneck/attention/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/bottleneck/attention/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/bottleneck/input/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/bottleneck/input/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/bottleneck/input/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/bottleneck/input/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/ffn_layer_0/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/ffn_layer_0/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/ffn_layer_0/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/ffn_layer_0/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/ffn_layer_0/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/ffn_layer_0/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/ffn_layer_1/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/ffn_layer_1/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/ffn_layer_1/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/ffn_layer_1/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/ffn_layer_1/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/ffn_layer_1/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/ffn_layer_2/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/ffn_layer_2/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/ffn_layer_2/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/ffn_layer_2/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/ffn_layer_2/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/ffn_layer_2/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/output/bottleneck/FakeLayerNorm/beta" = dense<1.0> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/output/bottleneck/FakeLayerNorm/gamma" = dense<0.4> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/output/bottleneck/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/output/bottleneck/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_19/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/attention/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/attention/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/attention/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/attention/output/dense/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/attention/self/key/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/attention/self/key/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/attention/self/query/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/attention/self/query/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/attention/self/value/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/attention/self/value/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/bottleneck/attention/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/bottleneck/attention/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/bottleneck/attention/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/bottleneck/attention/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/bottleneck/input/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/bottleneck/input/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/bottleneck/input/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/bottleneck/input/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/ffn_layer_0/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/ffn_layer_0/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/ffn_layer_0/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/ffn_layer_0/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/ffn_layer_0/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/ffn_layer_0/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/ffn_layer_1/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/ffn_layer_1/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/ffn_layer_1/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/ffn_layer_1/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/ffn_layer_1/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/ffn_layer_1/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/ffn_layer_2/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/ffn_layer_2/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/ffn_layer_2/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/ffn_layer_2/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/ffn_layer_2/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/ffn_layer_2/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/output/bottleneck/FakeLayerNorm/beta" = dense<1.0> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/output/bottleneck/FakeLayerNorm/gamma" = dense<0.4> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/output/bottleneck/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/output/bottleneck/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_2/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/attention/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/attention/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/attention/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/attention/output/dense/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/attention/self/key/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/attention/self/key/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/attention/self/query/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/attention/self/query/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/attention/self/value/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/attention/self/value/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/bottleneck/attention/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/bottleneck/attention/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/bottleneck/attention/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/bottleneck/attention/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/bottleneck/input/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/bottleneck/input/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/bottleneck/input/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/bottleneck/input/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/ffn_layer_0/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/ffn_layer_0/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/ffn_layer_0/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/ffn_layer_0/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/ffn_layer_0/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/ffn_layer_0/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/ffn_layer_1/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/ffn_layer_1/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/ffn_layer_1/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/ffn_layer_1/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/ffn_layer_1/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/ffn_layer_1/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/ffn_layer_2/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/ffn_layer_2/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/ffn_layer_2/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/ffn_layer_2/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/ffn_layer_2/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/ffn_layer_2/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/output/bottleneck/FakeLayerNorm/beta" = dense<1.0> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/output/bottleneck/FakeLayerNorm/gamma" = dense<0.4> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/output/bottleneck/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/output/bottleneck/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_20/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/attention/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/attention/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/attention/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/attention/output/dense/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/attention/self/key/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/attention/self/key/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/attention/self/query/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/attention/self/query/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/attention/self/value/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/attention/self/value/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/bottleneck/attention/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/bottleneck/attention/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/bottleneck/attention/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/bottleneck/attention/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/bottleneck/input/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/bottleneck/input/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/bottleneck/input/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/bottleneck/input/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/ffn_layer_0/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/ffn_layer_0/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/ffn_layer_0/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/ffn_layer_0/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/ffn_layer_0/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/ffn_layer_0/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/ffn_layer_1/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/ffn_layer_1/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/ffn_layer_1/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/ffn_layer_1/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/ffn_layer_1/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/ffn_layer_1/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/ffn_layer_2/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/ffn_layer_2/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/ffn_layer_2/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/ffn_layer_2/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/ffn_layer_2/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/ffn_layer_2/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/output/bottleneck/FakeLayerNorm/beta" = dense<1.0> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/output/bottleneck/FakeLayerNorm/gamma" = dense<0.4> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/output/bottleneck/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/output/bottleneck/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_21/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/attention/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/attention/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/attention/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/attention/output/dense/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/attention/self/key/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/attention/self/key/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/attention/self/query/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/attention/self/query/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/attention/self/value/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/attention/self/value/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/bottleneck/attention/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/bottleneck/attention/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/bottleneck/attention/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/bottleneck/attention/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/bottleneck/input/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/bottleneck/input/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/bottleneck/input/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/bottleneck/input/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/ffn_layer_0/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/ffn_layer_0/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/ffn_layer_0/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/ffn_layer_0/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/ffn_layer_0/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/ffn_layer_0/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/ffn_layer_1/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/ffn_layer_1/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/ffn_layer_1/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/ffn_layer_1/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/ffn_layer_1/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/ffn_layer_1/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/ffn_layer_2/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/ffn_layer_2/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/ffn_layer_2/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/ffn_layer_2/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/ffn_layer_2/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/ffn_layer_2/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/output/bottleneck/FakeLayerNorm/beta" = dense<1.0> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/output/bottleneck/FakeLayerNorm/gamma" = dense<0.4> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/output/bottleneck/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/output/bottleneck/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_22/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/attention/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/attention/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/attention/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/attention/output/dense/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/attention/self/key/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/attention/self/key/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/attention/self/query/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/attention/self/query/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/attention/self/value/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/attention/self/value/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/bottleneck/attention/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/bottleneck/attention/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/bottleneck/attention/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/bottleneck/attention/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/bottleneck/input/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/bottleneck/input/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/bottleneck/input/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/bottleneck/input/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/ffn_layer_0/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/ffn_layer_0/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/ffn_layer_0/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/ffn_layer_0/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/ffn_layer_0/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/ffn_layer_0/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/ffn_layer_1/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/ffn_layer_1/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/ffn_layer_1/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/ffn_layer_1/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/ffn_layer_1/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/ffn_layer_1/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/ffn_layer_2/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/ffn_layer_2/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/ffn_layer_2/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/ffn_layer_2/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/ffn_layer_2/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/ffn_layer_2/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/output/bottleneck/FakeLayerNorm/beta" = dense<1.0> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/output/bottleneck/FakeLayerNorm/gamma" = dense<0.4> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/output/bottleneck/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/output/bottleneck/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_23/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/attention/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/attention/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/attention/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/attention/output/dense/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/attention/self/key/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/attention/self/key/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/attention/self/query/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/attention/self/query/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/attention/self/value/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/attention/self/value/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/bottleneck/attention/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/bottleneck/attention/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/bottleneck/attention/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/bottleneck/attention/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/bottleneck/input/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/bottleneck/input/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/bottleneck/input/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/bottleneck/input/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/ffn_layer_0/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/ffn_layer_0/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/ffn_layer_0/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/ffn_layer_0/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/ffn_layer_0/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/ffn_layer_0/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/ffn_layer_1/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/ffn_layer_1/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/ffn_layer_1/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/ffn_layer_1/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/ffn_layer_1/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/ffn_layer_1/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/ffn_layer_2/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/ffn_layer_2/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/ffn_layer_2/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/ffn_layer_2/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/ffn_layer_2/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/ffn_layer_2/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/output/bottleneck/FakeLayerNorm/beta" = dense<1.0> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/output/bottleneck/FakeLayerNorm/gamma" = dense<0.4> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/output/bottleneck/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/output/bottleneck/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_3/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/attention/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/attention/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/attention/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/attention/output/dense/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/attention/self/key/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/attention/self/key/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/attention/self/query/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/attention/self/query/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/attention/self/value/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/attention/self/value/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/bottleneck/attention/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/bottleneck/attention/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/bottleneck/attention/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/bottleneck/attention/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/bottleneck/input/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/bottleneck/input/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/bottleneck/input/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/bottleneck/input/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/ffn_layer_0/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/ffn_layer_0/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/ffn_layer_0/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/ffn_layer_0/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/ffn_layer_0/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/ffn_layer_0/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/ffn_layer_1/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/ffn_layer_1/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/ffn_layer_1/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/ffn_layer_1/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/ffn_layer_1/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/ffn_layer_1/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/ffn_layer_2/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/ffn_layer_2/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/ffn_layer_2/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/ffn_layer_2/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/ffn_layer_2/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/ffn_layer_2/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/output/bottleneck/FakeLayerNorm/beta" = dense<1.0> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/output/bottleneck/FakeLayerNorm/gamma" = dense<0.4> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/output/bottleneck/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/output/bottleneck/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_4/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/attention/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/attention/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/attention/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/attention/output/dense/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/attention/self/key/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/attention/self/key/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/attention/self/query/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/attention/self/query/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/attention/self/value/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/attention/self/value/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/bottleneck/attention/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/bottleneck/attention/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/bottleneck/attention/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/bottleneck/attention/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/bottleneck/input/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/bottleneck/input/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/bottleneck/input/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/bottleneck/input/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/ffn_layer_0/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/ffn_layer_0/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/ffn_layer_0/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/ffn_layer_0/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/ffn_layer_0/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/ffn_layer_0/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/ffn_layer_1/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/ffn_layer_1/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/ffn_layer_1/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/ffn_layer_1/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/ffn_layer_1/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/ffn_layer_1/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/ffn_layer_2/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/ffn_layer_2/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/ffn_layer_2/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/ffn_layer_2/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/ffn_layer_2/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/ffn_layer_2/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/output/bottleneck/FakeLayerNorm/beta" = dense<1.0> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/output/bottleneck/FakeLayerNorm/gamma" = dense<0.4> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/output/bottleneck/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/output/bottleneck/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_5/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/attention/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/attention/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/attention/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/attention/output/dense/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/attention/self/key/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/attention/self/key/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/attention/self/query/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/attention/self/query/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/attention/self/value/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/attention/self/value/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/bottleneck/attention/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/bottleneck/attention/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/bottleneck/attention/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/bottleneck/attention/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/bottleneck/input/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/bottleneck/input/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/bottleneck/input/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/bottleneck/input/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/ffn_layer_0/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/ffn_layer_0/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/ffn_layer_0/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/ffn_layer_0/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/ffn_layer_0/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/ffn_layer_0/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/ffn_layer_1/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/ffn_layer_1/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/ffn_layer_1/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/ffn_layer_1/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/ffn_layer_1/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/ffn_layer_1/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/ffn_layer_2/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/ffn_layer_2/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/ffn_layer_2/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/ffn_layer_2/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/ffn_layer_2/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/ffn_layer_2/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/output/bottleneck/FakeLayerNorm/beta" = dense<1.0> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/output/bottleneck/FakeLayerNorm/gamma" = dense<0.4> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/output/bottleneck/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/output/bottleneck/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_6/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/attention/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/attention/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/attention/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/attention/output/dense/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/attention/self/key/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/attention/self/key/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/attention/self/query/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/attention/self/query/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/attention/self/value/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/attention/self/value/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/bottleneck/attention/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/bottleneck/attention/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/bottleneck/attention/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/bottleneck/attention/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/bottleneck/input/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/bottleneck/input/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/bottleneck/input/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/bottleneck/input/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/ffn_layer_0/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/ffn_layer_0/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/ffn_layer_0/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/ffn_layer_0/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/ffn_layer_0/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/ffn_layer_0/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/ffn_layer_1/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/ffn_layer_1/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/ffn_layer_1/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/ffn_layer_1/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/ffn_layer_1/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/ffn_layer_1/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/ffn_layer_2/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/ffn_layer_2/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/ffn_layer_2/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/ffn_layer_2/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/ffn_layer_2/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/ffn_layer_2/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/output/bottleneck/FakeLayerNorm/beta" = dense<1.0> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/output/bottleneck/FakeLayerNorm/gamma" = dense<0.4> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/output/bottleneck/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/output/bottleneck/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_7/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/attention/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/attention/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/attention/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/attention/output/dense/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/attention/self/key/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/attention/self/key/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/attention/self/query/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/attention/self/query/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/attention/self/value/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/attention/self/value/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/bottleneck/attention/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/bottleneck/attention/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/bottleneck/attention/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/bottleneck/attention/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/bottleneck/input/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/bottleneck/input/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/bottleneck/input/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/bottleneck/input/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/ffn_layer_0/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/ffn_layer_0/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/ffn_layer_0/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/ffn_layer_0/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/ffn_layer_0/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/ffn_layer_0/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/ffn_layer_1/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/ffn_layer_1/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/ffn_layer_1/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/ffn_layer_1/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/ffn_layer_1/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/ffn_layer_1/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/ffn_layer_2/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/ffn_layer_2/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/ffn_layer_2/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/ffn_layer_2/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/ffn_layer_2/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/ffn_layer_2/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/output/bottleneck/FakeLayerNorm/beta" = dense<1.0> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/output/bottleneck/FakeLayerNorm/gamma" = dense<0.4> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/output/bottleneck/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/output/bottleneck/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_8/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/attention/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/attention/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/attention/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/attention/output/dense/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/attention/self/key/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/attention/self/key/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/attention/self/query/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/attention/self/query/kernel" {noinline} = dense<0.0001> : tensor<128x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/attention/self/value/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/attention/self/value/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/bottleneck/attention/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/bottleneck/attention/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/bottleneck/attention/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/bottleneck/attention/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/bottleneck/input/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/bottleneck/input/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/bottleneck/input/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/bottleneck/input/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/ffn_layer_0/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/ffn_layer_0/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/ffn_layer_0/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/ffn_layer_0/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/ffn_layer_0/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/ffn_layer_0/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/ffn_layer_1/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/ffn_layer_1/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/ffn_layer_1/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/ffn_layer_1/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/ffn_layer_1/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/ffn_layer_1/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/ffn_layer_2/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/ffn_layer_2/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/ffn_layer_2/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/ffn_layer_2/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/ffn_layer_2/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/ffn_layer_2/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/intermediate/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/intermediate/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/output/FakeLayerNorm/beta" = dense<1.0> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/output/FakeLayerNorm/gamma" = dense<0.4> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/output/bottleneck/FakeLayerNorm/beta" = dense<1.0> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/output/bottleneck/FakeLayerNorm/gamma" = dense<0.4> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/output/bottleneck/dense/bias" = dense<0.1> : tensor<512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/output/bottleneck/dense/kernel" {noinline} = dense<0.0001> : tensor<128x512xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/output/dense/bias" = dense<0.1> : tensor<128xf32>
+  util.global private @"__iree_flow_bert/encoder/layer_9/output/dense/kernel" {noinline} = dense<0.0001> : tensor<512x128xf32>
+  util.global private @"__iree_flow_cls/squad/output_bias" = dense<0.1> : tensor<2xf32>
+  util.global private @"__iree_flow_cls/squad/output_weights" = dense<1.0> : tensor<2x512xf32>
   func @serving_default() attributes { iree.module.export} {
     %arg0 = util.unfoldable_constant dense<0> : tensor<1x384xi32>
     %arg1 = util.unfoldable_constant dense<0> : tensor<1x384xi32>
     %arg2 = util.unfoldable_constant dense<0> : tensor<1x384xi32>
-    %0 = flow.variable.address @"__iree_flow_bert/embeddings/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
-    %1 = flow.variable.address @"__iree_flow_bert/embeddings/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
-    %2 = flow.variable.address @"__iree_flow_bert/embeddings/embedding_transformation/bias" : !util.ptr<tensor<512xf32>>
-    %3 = flow.variable.address @"__iree_flow_bert/embeddings/embedding_transformation/kernel" : !util.ptr<tensor<384x512xf32>>
-    %4 = flow.variable.address @"__iree_flow_bert/embeddings/position_embeddings" : !util.ptr<tensor<512x512xf32>>
-    %5 = flow.variable.address @"__iree_flow_bert/embeddings/token_type_embeddings" : !util.ptr<tensor<2x512xf32>>
-    %6 = flow.variable.address @"__iree_flow_bert/embeddings/word_embeddings" : !util.ptr<tensor<30522x128xf32>>
-    %7 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %8 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %9 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %10 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
-    %11 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
-    %12 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
-    %13 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
-    %14 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
-    %15 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
-    %16 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
-    %17 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %18 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %19 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
-    %20 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %21 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %22 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %23 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
-    %24 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %25 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %26 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %27 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %28 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %29 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %30 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %31 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %32 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %33 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %34 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %35 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %36 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %37 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %38 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
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-    %40 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %41 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %42 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
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-    %44 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
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-    %46 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %47 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
-    %48 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
-    %49 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
-    %50 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %51 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %52 = flow.variable.address @"__iree_flow_bert/encoder/layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %53 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %54 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %55 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
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-    %57 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
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-    %61 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
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-    %63 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %64 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %65 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
-    %66 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %67 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %68 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %69 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
-    %70 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %71 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %72 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %73 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %74 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %75 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %76 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %77 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %78 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %79 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %80 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %81 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %82 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %83 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %84 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %85 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %86 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %87 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %88 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %89 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %90 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
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-    %92 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %93 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
-    %94 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
-    %95 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
-    %96 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %97 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %98 = flow.variable.address @"__iree_flow_bert/encoder/layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
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-    %100 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
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-    %103 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
-    %104 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
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-    %106 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
-    %107 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
-    %108 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
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-    %110 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
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-    %114 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
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-    %118 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
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-    %120 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %121 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %122 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %123 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %124 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %125 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %126 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %127 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %128 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %129 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %130 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
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-    %132 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %133 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %134 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
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-    %136 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %137 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %138 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %139 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
-    %140 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
-    %141 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
-    %142 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %143 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %144 = flow.variable.address @"__iree_flow_bert/encoder/layer_10/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %145 = flow.variable.address @"__iree_flow_bert/encoder/layer_11/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %146 = flow.variable.address @"__iree_flow_bert/encoder/layer_11/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %147 = flow.variable.address @"__iree_flow_bert/encoder/layer_11/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %148 = flow.variable.address @"__iree_flow_bert/encoder/layer_11/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
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-    %154 = flow.variable.address @"__iree_flow_bert/encoder/layer_11/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
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-    %156 = flow.variable.address @"__iree_flow_bert/encoder/layer_11/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %157 = flow.variable.address @"__iree_flow_bert/encoder/layer_11/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
-    %158 = flow.variable.address @"__iree_flow_bert/encoder/layer_11/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
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-    %160 = flow.variable.address @"__iree_flow_bert/encoder/layer_11/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %161 = flow.variable.address @"__iree_flow_bert/encoder/layer_11/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
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-    %163 = flow.variable.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %164 = flow.variable.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %165 = flow.variable.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %166 = flow.variable.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %167 = flow.variable.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %168 = flow.variable.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %169 = flow.variable.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %170 = flow.variable.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %171 = flow.variable.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %172 = flow.variable.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %173 = flow.variable.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %174 = flow.variable.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %175 = flow.variable.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %176 = flow.variable.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %177 = flow.variable.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
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-    %179 = flow.variable.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
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-    %266 = flow.variable.address @"__iree_flow_bert/encoder/layer_13/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
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-    %276 = flow.variable.address @"__iree_flow_bert/encoder/layer_13/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
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-    %278 = flow.variable.address @"__iree_flow_bert/encoder/layer_13/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
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-    %284 = flow.variable.address @"__iree_flow_bert/encoder/layer_14/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
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-    %306 = flow.variable.address @"__iree_flow_bert/encoder/layer_14/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
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-    %322 = flow.variable.address @"__iree_flow_bert/encoder/layer_14/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %323 = flow.variable.address @"__iree_flow_bert/encoder/layer_14/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
-    %324 = flow.variable.address @"__iree_flow_bert/encoder/layer_14/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
-    %325 = flow.variable.address @"__iree_flow_bert/encoder/layer_14/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
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-    %330 = flow.variable.address @"__iree_flow_bert/encoder/layer_15/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
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-    %334 = flow.variable.address @"__iree_flow_bert/encoder/layer_15/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
-    %335 = flow.variable.address @"__iree_flow_bert/encoder/layer_15/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
-    %336 = flow.variable.address @"__iree_flow_bert/encoder/layer_15/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
-    %337 = flow.variable.address @"__iree_flow_bert/encoder/layer_15/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
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-    %657 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
-    %658 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
-    %659 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
-    %660 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
-    %661 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %662 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %663 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
-    %664 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %665 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %666 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %667 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
-    %668 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %669 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %670 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %671 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %672 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %673 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %674 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %675 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %676 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %677 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %678 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %679 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %680 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %681 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %682 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %683 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %684 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %685 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %686 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %687 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %688 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %689 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %690 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %691 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
-    %692 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
-    %693 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
-    %694 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %695 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %696 = flow.variable.address @"__iree_flow_bert/encoder/layer_21/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %697 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %698 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %699 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %700 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
-    %701 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
-    %702 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
-    %703 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
-    %704 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
-    %705 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
-    %706 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
-    %707 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %708 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %709 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
-    %710 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %711 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %712 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %713 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
-    %714 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %715 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %716 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %717 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %718 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %719 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %720 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %721 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %722 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %723 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %724 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %725 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %726 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %727 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %728 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %729 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %730 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %731 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %732 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %733 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %734 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %735 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %736 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %737 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
-    %738 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
-    %739 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
-    %740 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %741 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %742 = flow.variable.address @"__iree_flow_bert/encoder/layer_22/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %743 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %744 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %745 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %746 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
-    %747 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
-    %748 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
-    %749 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
-    %750 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
-    %751 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
-    %752 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
-    %753 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %754 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %755 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
-    %756 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %757 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %758 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %759 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
-    %760 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %761 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %762 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %763 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %764 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %765 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %766 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %767 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %768 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %769 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %770 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %771 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %772 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %773 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %774 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %775 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %776 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %777 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %778 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %779 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %780 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %781 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %782 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %783 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
-    %784 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
-    %785 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
-    %786 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %787 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %788 = flow.variable.address @"__iree_flow_bert/encoder/layer_23/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %789 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %790 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %791 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %792 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
-    %793 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
-    %794 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
-    %795 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
-    %796 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
-    %797 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
-    %798 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
-    %799 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %800 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %801 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
-    %802 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %803 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %804 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %805 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
-    %806 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %807 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %808 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %809 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %810 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %811 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %812 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %813 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %814 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %815 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %816 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %817 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %818 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %819 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %820 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %821 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %822 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %823 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %824 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %825 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %826 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %827 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %828 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %829 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
-    %830 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
-    %831 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
-    %832 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %833 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %834 = flow.variable.address @"__iree_flow_bert/encoder/layer_3/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %835 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %836 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %837 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %838 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
-    %839 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
-    %840 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
-    %841 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
-    %842 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
-    %843 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
-    %844 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
-    %845 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %846 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %847 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
-    %848 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %849 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %850 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %851 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
-    %852 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %853 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %854 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %855 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %856 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %857 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %858 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %859 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %860 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %861 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %862 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %863 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %864 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %865 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %866 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %867 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %868 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %869 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %870 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %871 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %872 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %873 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %874 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %875 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
-    %876 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
-    %877 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
-    %878 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %879 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %880 = flow.variable.address @"__iree_flow_bert/encoder/layer_4/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %881 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %882 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %883 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %884 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
-    %885 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
-    %886 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
-    %887 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
-    %888 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
-    %889 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
-    %890 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
-    %891 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %892 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %893 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
-    %894 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %895 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %896 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %897 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
-    %898 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %899 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %900 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %901 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %902 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %903 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %904 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %905 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %906 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %907 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %908 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %909 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %910 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %911 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %912 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %913 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %914 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %915 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %916 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %917 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %918 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %919 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %920 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %921 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
-    %922 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
-    %923 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
-    %924 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %925 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %926 = flow.variable.address @"__iree_flow_bert/encoder/layer_5/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %927 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %928 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %929 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %930 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
-    %931 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
-    %932 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
-    %933 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
-    %934 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
-    %935 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
-    %936 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
-    %937 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %938 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %939 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
-    %940 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %941 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %942 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %943 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
-    %944 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %945 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %946 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %947 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %948 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %949 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %950 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %951 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %952 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %953 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %954 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %955 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %956 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %957 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %958 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %959 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %960 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %961 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %962 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %963 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %964 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %965 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %966 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %967 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
-    %968 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
-    %969 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
-    %970 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %971 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %972 = flow.variable.address @"__iree_flow_bert/encoder/layer_6/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %973 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %974 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %975 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %976 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
-    %977 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
-    %978 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
-    %979 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
-    %980 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
-    %981 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
-    %982 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
-    %983 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %984 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %985 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
-    %986 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %987 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %988 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %989 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
-    %990 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %991 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %992 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %993 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %994 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %995 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %996 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %997 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %998 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %999 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %1000 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %1001 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %1002 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %1003 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %1004 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %1005 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %1006 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %1007 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %1008 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %1009 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %1010 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %1011 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %1012 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %1013 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
-    %1014 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
-    %1015 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
-    %1016 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %1017 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %1018 = flow.variable.address @"__iree_flow_bert/encoder/layer_7/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %1019 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %1020 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %1021 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %1022 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
-    %1023 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
-    %1024 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
-    %1025 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
-    %1026 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
-    %1027 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
-    %1028 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
-    %1029 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %1030 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %1031 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
-    %1032 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %1033 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %1034 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %1035 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
-    %1036 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %1037 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %1038 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %1039 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %1040 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %1041 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %1042 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %1043 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %1044 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %1045 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %1046 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %1047 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %1048 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %1049 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %1050 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %1051 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %1052 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %1053 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %1054 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %1055 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %1056 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %1057 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %1058 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %1059 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
-    %1060 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
-    %1061 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
-    %1062 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %1063 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %1064 = flow.variable.address @"__iree_flow_bert/encoder/layer_8/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %1065 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %1066 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %1067 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %1068 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
-    %1069 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
-    %1070 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
-    %1071 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
-    %1072 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
-    %1073 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
-    %1074 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
-    %1075 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %1076 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %1077 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
-    %1078 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %1079 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %1080 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %1081 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
-    %1082 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %1083 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %1084 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %1085 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %1086 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %1087 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %1088 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %1089 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %1090 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %1091 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %1092 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %1093 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %1094 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %1095 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %1096 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %1097 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %1098 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %1099 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %1100 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %1101 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
-    %1102 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %1103 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
-    %1104 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
-    %1105 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
-    %1106 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
-    %1107 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
-    %1108 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
-    %1109 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/output/dense/bias" : !util.ptr<tensor<128xf32>>
-    %1110 = flow.variable.address @"__iree_flow_bert/encoder/layer_9/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
-    %1111 = flow.variable.address @"__iree_flow_cls/squad/output_bias" : !util.ptr<tensor<2xf32>>
-    %1112 = flow.variable.address @"__iree_flow_cls/squad/output_weights" : !util.ptr<tensor<2x512xf32>>
+    %0 = util.global.address @"__iree_flow_bert/embeddings/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
+    %1 = util.global.address @"__iree_flow_bert/embeddings/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
+    %2 = util.global.address @"__iree_flow_bert/embeddings/embedding_transformation/bias" : !util.ptr<tensor<512xf32>>
+    %3 = util.global.address @"__iree_flow_bert/embeddings/embedding_transformation/kernel" : !util.ptr<tensor<384x512xf32>>
+    %4 = util.global.address @"__iree_flow_bert/embeddings/position_embeddings" : !util.ptr<tensor<512x512xf32>>
+    %5 = util.global.address @"__iree_flow_bert/embeddings/token_type_embeddings" : !util.ptr<tensor<2x512xf32>>
+    %6 = util.global.address @"__iree_flow_bert/embeddings/word_embeddings" : !util.ptr<tensor<30522x128xf32>>
+    %7 = util.global.address @"__iree_flow_bert/encoder/layer_0/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %8 = util.global.address @"__iree_flow_bert/encoder/layer_0/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %9 = util.global.address @"__iree_flow_bert/encoder/layer_0/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %10 = util.global.address @"__iree_flow_bert/encoder/layer_0/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
+    %11 = util.global.address @"__iree_flow_bert/encoder/layer_0/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
+    %12 = util.global.address @"__iree_flow_bert/encoder/layer_0/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
+    %13 = util.global.address @"__iree_flow_bert/encoder/layer_0/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
+    %14 = util.global.address @"__iree_flow_bert/encoder/layer_0/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
+    %15 = util.global.address @"__iree_flow_bert/encoder/layer_0/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
+    %16 = util.global.address @"__iree_flow_bert/encoder/layer_0/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
+    %17 = util.global.address @"__iree_flow_bert/encoder/layer_0/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %18 = util.global.address @"__iree_flow_bert/encoder/layer_0/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %19 = util.global.address @"__iree_flow_bert/encoder/layer_0/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
+    %20 = util.global.address @"__iree_flow_bert/encoder/layer_0/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %21 = util.global.address @"__iree_flow_bert/encoder/layer_0/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %22 = util.global.address @"__iree_flow_bert/encoder/layer_0/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %23 = util.global.address @"__iree_flow_bert/encoder/layer_0/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
+    %24 = util.global.address @"__iree_flow_bert/encoder/layer_0/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %25 = util.global.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %26 = util.global.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %27 = util.global.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %28 = util.global.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %29 = util.global.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %30 = util.global.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %31 = util.global.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %32 = util.global.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %33 = util.global.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %34 = util.global.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %35 = util.global.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %36 = util.global.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %37 = util.global.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %38 = util.global.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %39 = util.global.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %40 = util.global.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %41 = util.global.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %42 = util.global.address @"__iree_flow_bert/encoder/layer_0/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %43 = util.global.address @"__iree_flow_bert/encoder/layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %44 = util.global.address @"__iree_flow_bert/encoder/layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %45 = util.global.address @"__iree_flow_bert/encoder/layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %46 = util.global.address @"__iree_flow_bert/encoder/layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %47 = util.global.address @"__iree_flow_bert/encoder/layer_0/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
+    %48 = util.global.address @"__iree_flow_bert/encoder/layer_0/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
+    %49 = util.global.address @"__iree_flow_bert/encoder/layer_0/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
+    %50 = util.global.address @"__iree_flow_bert/encoder/layer_0/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %51 = util.global.address @"__iree_flow_bert/encoder/layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %52 = util.global.address @"__iree_flow_bert/encoder/layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %53 = util.global.address @"__iree_flow_bert/encoder/layer_1/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %54 = util.global.address @"__iree_flow_bert/encoder/layer_1/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %55 = util.global.address @"__iree_flow_bert/encoder/layer_1/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %56 = util.global.address @"__iree_flow_bert/encoder/layer_1/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
+    %57 = util.global.address @"__iree_flow_bert/encoder/layer_1/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
+    %58 = util.global.address @"__iree_flow_bert/encoder/layer_1/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
+    %59 = util.global.address @"__iree_flow_bert/encoder/layer_1/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
+    %60 = util.global.address @"__iree_flow_bert/encoder/layer_1/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
+    %61 = util.global.address @"__iree_flow_bert/encoder/layer_1/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
+    %62 = util.global.address @"__iree_flow_bert/encoder/layer_1/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
+    %63 = util.global.address @"__iree_flow_bert/encoder/layer_1/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %64 = util.global.address @"__iree_flow_bert/encoder/layer_1/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %65 = util.global.address @"__iree_flow_bert/encoder/layer_1/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
+    %66 = util.global.address @"__iree_flow_bert/encoder/layer_1/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %67 = util.global.address @"__iree_flow_bert/encoder/layer_1/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %68 = util.global.address @"__iree_flow_bert/encoder/layer_1/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %69 = util.global.address @"__iree_flow_bert/encoder/layer_1/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
+    %70 = util.global.address @"__iree_flow_bert/encoder/layer_1/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %71 = util.global.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %72 = util.global.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %73 = util.global.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %74 = util.global.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %75 = util.global.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %76 = util.global.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %77 = util.global.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %78 = util.global.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %79 = util.global.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %80 = util.global.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %81 = util.global.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %82 = util.global.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %83 = util.global.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %84 = util.global.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %85 = util.global.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %86 = util.global.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %87 = util.global.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %88 = util.global.address @"__iree_flow_bert/encoder/layer_1/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %89 = util.global.address @"__iree_flow_bert/encoder/layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %90 = util.global.address @"__iree_flow_bert/encoder/layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %91 = util.global.address @"__iree_flow_bert/encoder/layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %92 = util.global.address @"__iree_flow_bert/encoder/layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %93 = util.global.address @"__iree_flow_bert/encoder/layer_1/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
+    %94 = util.global.address @"__iree_flow_bert/encoder/layer_1/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
+    %95 = util.global.address @"__iree_flow_bert/encoder/layer_1/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
+    %96 = util.global.address @"__iree_flow_bert/encoder/layer_1/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %97 = util.global.address @"__iree_flow_bert/encoder/layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %98 = util.global.address @"__iree_flow_bert/encoder/layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %99 = util.global.address @"__iree_flow_bert/encoder/layer_10/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %100 = util.global.address @"__iree_flow_bert/encoder/layer_10/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %101 = util.global.address @"__iree_flow_bert/encoder/layer_10/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %102 = util.global.address @"__iree_flow_bert/encoder/layer_10/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
+    %103 = util.global.address @"__iree_flow_bert/encoder/layer_10/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
+    %104 = util.global.address @"__iree_flow_bert/encoder/layer_10/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
+    %105 = util.global.address @"__iree_flow_bert/encoder/layer_10/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
+    %106 = util.global.address @"__iree_flow_bert/encoder/layer_10/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
+    %107 = util.global.address @"__iree_flow_bert/encoder/layer_10/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
+    %108 = util.global.address @"__iree_flow_bert/encoder/layer_10/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
+    %109 = util.global.address @"__iree_flow_bert/encoder/layer_10/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %110 = util.global.address @"__iree_flow_bert/encoder/layer_10/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %111 = util.global.address @"__iree_flow_bert/encoder/layer_10/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
+    %112 = util.global.address @"__iree_flow_bert/encoder/layer_10/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %113 = util.global.address @"__iree_flow_bert/encoder/layer_10/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %114 = util.global.address @"__iree_flow_bert/encoder/layer_10/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %115 = util.global.address @"__iree_flow_bert/encoder/layer_10/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
+    %116 = util.global.address @"__iree_flow_bert/encoder/layer_10/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %117 = util.global.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %118 = util.global.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %119 = util.global.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %120 = util.global.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %121 = util.global.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %122 = util.global.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %123 = util.global.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %124 = util.global.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %125 = util.global.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %126 = util.global.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %127 = util.global.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %128 = util.global.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %129 = util.global.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %130 = util.global.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %131 = util.global.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %132 = util.global.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %133 = util.global.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %134 = util.global.address @"__iree_flow_bert/encoder/layer_10/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %135 = util.global.address @"__iree_flow_bert/encoder/layer_10/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %136 = util.global.address @"__iree_flow_bert/encoder/layer_10/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %137 = util.global.address @"__iree_flow_bert/encoder/layer_10/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %138 = util.global.address @"__iree_flow_bert/encoder/layer_10/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %139 = util.global.address @"__iree_flow_bert/encoder/layer_10/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
+    %140 = util.global.address @"__iree_flow_bert/encoder/layer_10/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
+    %141 = util.global.address @"__iree_flow_bert/encoder/layer_10/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
+    %142 = util.global.address @"__iree_flow_bert/encoder/layer_10/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %143 = util.global.address @"__iree_flow_bert/encoder/layer_10/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %144 = util.global.address @"__iree_flow_bert/encoder/layer_10/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %145 = util.global.address @"__iree_flow_bert/encoder/layer_11/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %146 = util.global.address @"__iree_flow_bert/encoder/layer_11/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %147 = util.global.address @"__iree_flow_bert/encoder/layer_11/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %148 = util.global.address @"__iree_flow_bert/encoder/layer_11/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
+    %149 = util.global.address @"__iree_flow_bert/encoder/layer_11/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
+    %150 = util.global.address @"__iree_flow_bert/encoder/layer_11/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
+    %151 = util.global.address @"__iree_flow_bert/encoder/layer_11/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
+    %152 = util.global.address @"__iree_flow_bert/encoder/layer_11/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
+    %153 = util.global.address @"__iree_flow_bert/encoder/layer_11/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
+    %154 = util.global.address @"__iree_flow_bert/encoder/layer_11/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
+    %155 = util.global.address @"__iree_flow_bert/encoder/layer_11/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %156 = util.global.address @"__iree_flow_bert/encoder/layer_11/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %157 = util.global.address @"__iree_flow_bert/encoder/layer_11/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
+    %158 = util.global.address @"__iree_flow_bert/encoder/layer_11/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %159 = util.global.address @"__iree_flow_bert/encoder/layer_11/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %160 = util.global.address @"__iree_flow_bert/encoder/layer_11/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %161 = util.global.address @"__iree_flow_bert/encoder/layer_11/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
+    %162 = util.global.address @"__iree_flow_bert/encoder/layer_11/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %163 = util.global.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %164 = util.global.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %165 = util.global.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %166 = util.global.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %167 = util.global.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %168 = util.global.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %169 = util.global.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %170 = util.global.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %171 = util.global.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %172 = util.global.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %173 = util.global.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %174 = util.global.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %175 = util.global.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %176 = util.global.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %177 = util.global.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %178 = util.global.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %179 = util.global.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %180 = util.global.address @"__iree_flow_bert/encoder/layer_11/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %181 = util.global.address @"__iree_flow_bert/encoder/layer_11/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %182 = util.global.address @"__iree_flow_bert/encoder/layer_11/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %183 = util.global.address @"__iree_flow_bert/encoder/layer_11/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %184 = util.global.address @"__iree_flow_bert/encoder/layer_11/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %185 = util.global.address @"__iree_flow_bert/encoder/layer_11/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
+    %186 = util.global.address @"__iree_flow_bert/encoder/layer_11/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
+    %187 = util.global.address @"__iree_flow_bert/encoder/layer_11/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
+    %188 = util.global.address @"__iree_flow_bert/encoder/layer_11/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %189 = util.global.address @"__iree_flow_bert/encoder/layer_11/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %190 = util.global.address @"__iree_flow_bert/encoder/layer_11/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %191 = util.global.address @"__iree_flow_bert/encoder/layer_12/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %192 = util.global.address @"__iree_flow_bert/encoder/layer_12/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %193 = util.global.address @"__iree_flow_bert/encoder/layer_12/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %194 = util.global.address @"__iree_flow_bert/encoder/layer_12/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
+    %195 = util.global.address @"__iree_flow_bert/encoder/layer_12/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
+    %196 = util.global.address @"__iree_flow_bert/encoder/layer_12/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
+    %197 = util.global.address @"__iree_flow_bert/encoder/layer_12/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
+    %198 = util.global.address @"__iree_flow_bert/encoder/layer_12/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
+    %199 = util.global.address @"__iree_flow_bert/encoder/layer_12/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
+    %200 = util.global.address @"__iree_flow_bert/encoder/layer_12/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
+    %201 = util.global.address @"__iree_flow_bert/encoder/layer_12/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %202 = util.global.address @"__iree_flow_bert/encoder/layer_12/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %203 = util.global.address @"__iree_flow_bert/encoder/layer_12/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
+    %204 = util.global.address @"__iree_flow_bert/encoder/layer_12/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %205 = util.global.address @"__iree_flow_bert/encoder/layer_12/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %206 = util.global.address @"__iree_flow_bert/encoder/layer_12/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %207 = util.global.address @"__iree_flow_bert/encoder/layer_12/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
+    %208 = util.global.address @"__iree_flow_bert/encoder/layer_12/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %209 = util.global.address @"__iree_flow_bert/encoder/layer_12/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %210 = util.global.address @"__iree_flow_bert/encoder/layer_12/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %211 = util.global.address @"__iree_flow_bert/encoder/layer_12/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %212 = util.global.address @"__iree_flow_bert/encoder/layer_12/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %213 = util.global.address @"__iree_flow_bert/encoder/layer_12/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %214 = util.global.address @"__iree_flow_bert/encoder/layer_12/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %215 = util.global.address @"__iree_flow_bert/encoder/layer_12/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %216 = util.global.address @"__iree_flow_bert/encoder/layer_12/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %217 = util.global.address @"__iree_flow_bert/encoder/layer_12/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %218 = util.global.address @"__iree_flow_bert/encoder/layer_12/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %219 = util.global.address @"__iree_flow_bert/encoder/layer_12/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %220 = util.global.address @"__iree_flow_bert/encoder/layer_12/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %221 = util.global.address @"__iree_flow_bert/encoder/layer_12/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %222 = util.global.address @"__iree_flow_bert/encoder/layer_12/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %223 = util.global.address @"__iree_flow_bert/encoder/layer_12/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %224 = util.global.address @"__iree_flow_bert/encoder/layer_12/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %225 = util.global.address @"__iree_flow_bert/encoder/layer_12/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %226 = util.global.address @"__iree_flow_bert/encoder/layer_12/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %227 = util.global.address @"__iree_flow_bert/encoder/layer_12/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %228 = util.global.address @"__iree_flow_bert/encoder/layer_12/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %229 = util.global.address @"__iree_flow_bert/encoder/layer_12/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %230 = util.global.address @"__iree_flow_bert/encoder/layer_12/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %231 = util.global.address @"__iree_flow_bert/encoder/layer_12/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
+    %232 = util.global.address @"__iree_flow_bert/encoder/layer_12/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
+    %233 = util.global.address @"__iree_flow_bert/encoder/layer_12/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
+    %234 = util.global.address @"__iree_flow_bert/encoder/layer_12/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %235 = util.global.address @"__iree_flow_bert/encoder/layer_12/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %236 = util.global.address @"__iree_flow_bert/encoder/layer_12/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %237 = util.global.address @"__iree_flow_bert/encoder/layer_13/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %238 = util.global.address @"__iree_flow_bert/encoder/layer_13/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %239 = util.global.address @"__iree_flow_bert/encoder/layer_13/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %240 = util.global.address @"__iree_flow_bert/encoder/layer_13/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
+    %241 = util.global.address @"__iree_flow_bert/encoder/layer_13/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
+    %242 = util.global.address @"__iree_flow_bert/encoder/layer_13/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
+    %243 = util.global.address @"__iree_flow_bert/encoder/layer_13/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
+    %244 = util.global.address @"__iree_flow_bert/encoder/layer_13/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
+    %245 = util.global.address @"__iree_flow_bert/encoder/layer_13/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
+    %246 = util.global.address @"__iree_flow_bert/encoder/layer_13/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
+    %247 = util.global.address @"__iree_flow_bert/encoder/layer_13/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %248 = util.global.address @"__iree_flow_bert/encoder/layer_13/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %249 = util.global.address @"__iree_flow_bert/encoder/layer_13/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
+    %250 = util.global.address @"__iree_flow_bert/encoder/layer_13/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %251 = util.global.address @"__iree_flow_bert/encoder/layer_13/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %252 = util.global.address @"__iree_flow_bert/encoder/layer_13/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %253 = util.global.address @"__iree_flow_bert/encoder/layer_13/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
+    %254 = util.global.address @"__iree_flow_bert/encoder/layer_13/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %255 = util.global.address @"__iree_flow_bert/encoder/layer_13/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %256 = util.global.address @"__iree_flow_bert/encoder/layer_13/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %257 = util.global.address @"__iree_flow_bert/encoder/layer_13/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %258 = util.global.address @"__iree_flow_bert/encoder/layer_13/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %259 = util.global.address @"__iree_flow_bert/encoder/layer_13/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %260 = util.global.address @"__iree_flow_bert/encoder/layer_13/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %261 = util.global.address @"__iree_flow_bert/encoder/layer_13/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %262 = util.global.address @"__iree_flow_bert/encoder/layer_13/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %263 = util.global.address @"__iree_flow_bert/encoder/layer_13/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %264 = util.global.address @"__iree_flow_bert/encoder/layer_13/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %265 = util.global.address @"__iree_flow_bert/encoder/layer_13/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %266 = util.global.address @"__iree_flow_bert/encoder/layer_13/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %267 = util.global.address @"__iree_flow_bert/encoder/layer_13/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %268 = util.global.address @"__iree_flow_bert/encoder/layer_13/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %269 = util.global.address @"__iree_flow_bert/encoder/layer_13/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %270 = util.global.address @"__iree_flow_bert/encoder/layer_13/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %271 = util.global.address @"__iree_flow_bert/encoder/layer_13/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %272 = util.global.address @"__iree_flow_bert/encoder/layer_13/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %273 = util.global.address @"__iree_flow_bert/encoder/layer_13/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %274 = util.global.address @"__iree_flow_bert/encoder/layer_13/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %275 = util.global.address @"__iree_flow_bert/encoder/layer_13/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %276 = util.global.address @"__iree_flow_bert/encoder/layer_13/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %277 = util.global.address @"__iree_flow_bert/encoder/layer_13/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
+    %278 = util.global.address @"__iree_flow_bert/encoder/layer_13/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
+    %279 = util.global.address @"__iree_flow_bert/encoder/layer_13/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
+    %280 = util.global.address @"__iree_flow_bert/encoder/layer_13/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %281 = util.global.address @"__iree_flow_bert/encoder/layer_13/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %282 = util.global.address @"__iree_flow_bert/encoder/layer_13/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %283 = util.global.address @"__iree_flow_bert/encoder/layer_14/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %284 = util.global.address @"__iree_flow_bert/encoder/layer_14/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %285 = util.global.address @"__iree_flow_bert/encoder/layer_14/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %286 = util.global.address @"__iree_flow_bert/encoder/layer_14/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
+    %287 = util.global.address @"__iree_flow_bert/encoder/layer_14/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
+    %288 = util.global.address @"__iree_flow_bert/encoder/layer_14/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
+    %289 = util.global.address @"__iree_flow_bert/encoder/layer_14/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
+    %290 = util.global.address @"__iree_flow_bert/encoder/layer_14/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
+    %291 = util.global.address @"__iree_flow_bert/encoder/layer_14/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
+    %292 = util.global.address @"__iree_flow_bert/encoder/layer_14/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
+    %293 = util.global.address @"__iree_flow_bert/encoder/layer_14/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %294 = util.global.address @"__iree_flow_bert/encoder/layer_14/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %295 = util.global.address @"__iree_flow_bert/encoder/layer_14/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
+    %296 = util.global.address @"__iree_flow_bert/encoder/layer_14/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %297 = util.global.address @"__iree_flow_bert/encoder/layer_14/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %298 = util.global.address @"__iree_flow_bert/encoder/layer_14/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %299 = util.global.address @"__iree_flow_bert/encoder/layer_14/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
+    %300 = util.global.address @"__iree_flow_bert/encoder/layer_14/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %301 = util.global.address @"__iree_flow_bert/encoder/layer_14/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %302 = util.global.address @"__iree_flow_bert/encoder/layer_14/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %303 = util.global.address @"__iree_flow_bert/encoder/layer_14/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %304 = util.global.address @"__iree_flow_bert/encoder/layer_14/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %305 = util.global.address @"__iree_flow_bert/encoder/layer_14/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %306 = util.global.address @"__iree_flow_bert/encoder/layer_14/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %307 = util.global.address @"__iree_flow_bert/encoder/layer_14/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %308 = util.global.address @"__iree_flow_bert/encoder/layer_14/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %309 = util.global.address @"__iree_flow_bert/encoder/layer_14/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %310 = util.global.address @"__iree_flow_bert/encoder/layer_14/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %311 = util.global.address @"__iree_flow_bert/encoder/layer_14/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %312 = util.global.address @"__iree_flow_bert/encoder/layer_14/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %313 = util.global.address @"__iree_flow_bert/encoder/layer_14/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %314 = util.global.address @"__iree_flow_bert/encoder/layer_14/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %315 = util.global.address @"__iree_flow_bert/encoder/layer_14/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %316 = util.global.address @"__iree_flow_bert/encoder/layer_14/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %317 = util.global.address @"__iree_flow_bert/encoder/layer_14/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %318 = util.global.address @"__iree_flow_bert/encoder/layer_14/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %319 = util.global.address @"__iree_flow_bert/encoder/layer_14/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %320 = util.global.address @"__iree_flow_bert/encoder/layer_14/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %321 = util.global.address @"__iree_flow_bert/encoder/layer_14/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %322 = util.global.address @"__iree_flow_bert/encoder/layer_14/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %323 = util.global.address @"__iree_flow_bert/encoder/layer_14/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
+    %324 = util.global.address @"__iree_flow_bert/encoder/layer_14/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
+    %325 = util.global.address @"__iree_flow_bert/encoder/layer_14/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
+    %326 = util.global.address @"__iree_flow_bert/encoder/layer_14/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %327 = util.global.address @"__iree_flow_bert/encoder/layer_14/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %328 = util.global.address @"__iree_flow_bert/encoder/layer_14/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %329 = util.global.address @"__iree_flow_bert/encoder/layer_15/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %330 = util.global.address @"__iree_flow_bert/encoder/layer_15/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %331 = util.global.address @"__iree_flow_bert/encoder/layer_15/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %332 = util.global.address @"__iree_flow_bert/encoder/layer_15/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
+    %333 = util.global.address @"__iree_flow_bert/encoder/layer_15/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
+    %334 = util.global.address @"__iree_flow_bert/encoder/layer_15/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
+    %335 = util.global.address @"__iree_flow_bert/encoder/layer_15/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
+    %336 = util.global.address @"__iree_flow_bert/encoder/layer_15/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
+    %337 = util.global.address @"__iree_flow_bert/encoder/layer_15/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
+    %338 = util.global.address @"__iree_flow_bert/encoder/layer_15/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
+    %339 = util.global.address @"__iree_flow_bert/encoder/layer_15/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %340 = util.global.address @"__iree_flow_bert/encoder/layer_15/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %341 = util.global.address @"__iree_flow_bert/encoder/layer_15/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
+    %342 = util.global.address @"__iree_flow_bert/encoder/layer_15/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %343 = util.global.address @"__iree_flow_bert/encoder/layer_15/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %344 = util.global.address @"__iree_flow_bert/encoder/layer_15/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %345 = util.global.address @"__iree_flow_bert/encoder/layer_15/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
+    %346 = util.global.address @"__iree_flow_bert/encoder/layer_15/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %347 = util.global.address @"__iree_flow_bert/encoder/layer_15/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %348 = util.global.address @"__iree_flow_bert/encoder/layer_15/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %349 = util.global.address @"__iree_flow_bert/encoder/layer_15/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %350 = util.global.address @"__iree_flow_bert/encoder/layer_15/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %351 = util.global.address @"__iree_flow_bert/encoder/layer_15/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %352 = util.global.address @"__iree_flow_bert/encoder/layer_15/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %353 = util.global.address @"__iree_flow_bert/encoder/layer_15/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %354 = util.global.address @"__iree_flow_bert/encoder/layer_15/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %355 = util.global.address @"__iree_flow_bert/encoder/layer_15/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %356 = util.global.address @"__iree_flow_bert/encoder/layer_15/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %357 = util.global.address @"__iree_flow_bert/encoder/layer_15/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %358 = util.global.address @"__iree_flow_bert/encoder/layer_15/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %359 = util.global.address @"__iree_flow_bert/encoder/layer_15/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %360 = util.global.address @"__iree_flow_bert/encoder/layer_15/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %361 = util.global.address @"__iree_flow_bert/encoder/layer_15/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %362 = util.global.address @"__iree_flow_bert/encoder/layer_15/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %363 = util.global.address @"__iree_flow_bert/encoder/layer_15/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %364 = util.global.address @"__iree_flow_bert/encoder/layer_15/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %365 = util.global.address @"__iree_flow_bert/encoder/layer_15/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %366 = util.global.address @"__iree_flow_bert/encoder/layer_15/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %367 = util.global.address @"__iree_flow_bert/encoder/layer_15/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %368 = util.global.address @"__iree_flow_bert/encoder/layer_15/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %369 = util.global.address @"__iree_flow_bert/encoder/layer_15/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
+    %370 = util.global.address @"__iree_flow_bert/encoder/layer_15/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
+    %371 = util.global.address @"__iree_flow_bert/encoder/layer_15/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
+    %372 = util.global.address @"__iree_flow_bert/encoder/layer_15/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %373 = util.global.address @"__iree_flow_bert/encoder/layer_15/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %374 = util.global.address @"__iree_flow_bert/encoder/layer_15/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %375 = util.global.address @"__iree_flow_bert/encoder/layer_16/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %376 = util.global.address @"__iree_flow_bert/encoder/layer_16/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %377 = util.global.address @"__iree_flow_bert/encoder/layer_16/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %378 = util.global.address @"__iree_flow_bert/encoder/layer_16/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
+    %379 = util.global.address @"__iree_flow_bert/encoder/layer_16/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
+    %380 = util.global.address @"__iree_flow_bert/encoder/layer_16/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
+    %381 = util.global.address @"__iree_flow_bert/encoder/layer_16/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
+    %382 = util.global.address @"__iree_flow_bert/encoder/layer_16/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
+    %383 = util.global.address @"__iree_flow_bert/encoder/layer_16/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
+    %384 = util.global.address @"__iree_flow_bert/encoder/layer_16/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
+    %385 = util.global.address @"__iree_flow_bert/encoder/layer_16/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %386 = util.global.address @"__iree_flow_bert/encoder/layer_16/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %387 = util.global.address @"__iree_flow_bert/encoder/layer_16/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
+    %388 = util.global.address @"__iree_flow_bert/encoder/layer_16/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %389 = util.global.address @"__iree_flow_bert/encoder/layer_16/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %390 = util.global.address @"__iree_flow_bert/encoder/layer_16/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %391 = util.global.address @"__iree_flow_bert/encoder/layer_16/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
+    %392 = util.global.address @"__iree_flow_bert/encoder/layer_16/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %393 = util.global.address @"__iree_flow_bert/encoder/layer_16/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %394 = util.global.address @"__iree_flow_bert/encoder/layer_16/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %395 = util.global.address @"__iree_flow_bert/encoder/layer_16/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %396 = util.global.address @"__iree_flow_bert/encoder/layer_16/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %397 = util.global.address @"__iree_flow_bert/encoder/layer_16/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %398 = util.global.address @"__iree_flow_bert/encoder/layer_16/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %399 = util.global.address @"__iree_flow_bert/encoder/layer_16/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %400 = util.global.address @"__iree_flow_bert/encoder/layer_16/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %401 = util.global.address @"__iree_flow_bert/encoder/layer_16/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %402 = util.global.address @"__iree_flow_bert/encoder/layer_16/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %403 = util.global.address @"__iree_flow_bert/encoder/layer_16/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %404 = util.global.address @"__iree_flow_bert/encoder/layer_16/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %405 = util.global.address @"__iree_flow_bert/encoder/layer_16/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %406 = util.global.address @"__iree_flow_bert/encoder/layer_16/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %407 = util.global.address @"__iree_flow_bert/encoder/layer_16/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %408 = util.global.address @"__iree_flow_bert/encoder/layer_16/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %409 = util.global.address @"__iree_flow_bert/encoder/layer_16/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %410 = util.global.address @"__iree_flow_bert/encoder/layer_16/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %411 = util.global.address @"__iree_flow_bert/encoder/layer_16/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %412 = util.global.address @"__iree_flow_bert/encoder/layer_16/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %413 = util.global.address @"__iree_flow_bert/encoder/layer_16/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %414 = util.global.address @"__iree_flow_bert/encoder/layer_16/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %415 = util.global.address @"__iree_flow_bert/encoder/layer_16/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
+    %416 = util.global.address @"__iree_flow_bert/encoder/layer_16/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
+    %417 = util.global.address @"__iree_flow_bert/encoder/layer_16/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
+    %418 = util.global.address @"__iree_flow_bert/encoder/layer_16/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %419 = util.global.address @"__iree_flow_bert/encoder/layer_16/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %420 = util.global.address @"__iree_flow_bert/encoder/layer_16/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %421 = util.global.address @"__iree_flow_bert/encoder/layer_17/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %422 = util.global.address @"__iree_flow_bert/encoder/layer_17/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %423 = util.global.address @"__iree_flow_bert/encoder/layer_17/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %424 = util.global.address @"__iree_flow_bert/encoder/layer_17/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
+    %425 = util.global.address @"__iree_flow_bert/encoder/layer_17/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
+    %426 = util.global.address @"__iree_flow_bert/encoder/layer_17/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
+    %427 = util.global.address @"__iree_flow_bert/encoder/layer_17/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
+    %428 = util.global.address @"__iree_flow_bert/encoder/layer_17/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
+    %429 = util.global.address @"__iree_flow_bert/encoder/layer_17/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
+    %430 = util.global.address @"__iree_flow_bert/encoder/layer_17/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
+    %431 = util.global.address @"__iree_flow_bert/encoder/layer_17/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %432 = util.global.address @"__iree_flow_bert/encoder/layer_17/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %433 = util.global.address @"__iree_flow_bert/encoder/layer_17/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
+    %434 = util.global.address @"__iree_flow_bert/encoder/layer_17/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %435 = util.global.address @"__iree_flow_bert/encoder/layer_17/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %436 = util.global.address @"__iree_flow_bert/encoder/layer_17/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %437 = util.global.address @"__iree_flow_bert/encoder/layer_17/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
+    %438 = util.global.address @"__iree_flow_bert/encoder/layer_17/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %439 = util.global.address @"__iree_flow_bert/encoder/layer_17/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %440 = util.global.address @"__iree_flow_bert/encoder/layer_17/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %441 = util.global.address @"__iree_flow_bert/encoder/layer_17/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %442 = util.global.address @"__iree_flow_bert/encoder/layer_17/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %443 = util.global.address @"__iree_flow_bert/encoder/layer_17/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %444 = util.global.address @"__iree_flow_bert/encoder/layer_17/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %445 = util.global.address @"__iree_flow_bert/encoder/layer_17/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %446 = util.global.address @"__iree_flow_bert/encoder/layer_17/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %447 = util.global.address @"__iree_flow_bert/encoder/layer_17/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %448 = util.global.address @"__iree_flow_bert/encoder/layer_17/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %449 = util.global.address @"__iree_flow_bert/encoder/layer_17/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %450 = util.global.address @"__iree_flow_bert/encoder/layer_17/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %451 = util.global.address @"__iree_flow_bert/encoder/layer_17/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %452 = util.global.address @"__iree_flow_bert/encoder/layer_17/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %453 = util.global.address @"__iree_flow_bert/encoder/layer_17/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %454 = util.global.address @"__iree_flow_bert/encoder/layer_17/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %455 = util.global.address @"__iree_flow_bert/encoder/layer_17/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %456 = util.global.address @"__iree_flow_bert/encoder/layer_17/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %457 = util.global.address @"__iree_flow_bert/encoder/layer_17/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %458 = util.global.address @"__iree_flow_bert/encoder/layer_17/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %459 = util.global.address @"__iree_flow_bert/encoder/layer_17/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %460 = util.global.address @"__iree_flow_bert/encoder/layer_17/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %461 = util.global.address @"__iree_flow_bert/encoder/layer_17/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
+    %462 = util.global.address @"__iree_flow_bert/encoder/layer_17/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
+    %463 = util.global.address @"__iree_flow_bert/encoder/layer_17/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
+    %464 = util.global.address @"__iree_flow_bert/encoder/layer_17/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %465 = util.global.address @"__iree_flow_bert/encoder/layer_17/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %466 = util.global.address @"__iree_flow_bert/encoder/layer_17/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %467 = util.global.address @"__iree_flow_bert/encoder/layer_18/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %468 = util.global.address @"__iree_flow_bert/encoder/layer_18/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %469 = util.global.address @"__iree_flow_bert/encoder/layer_18/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %470 = util.global.address @"__iree_flow_bert/encoder/layer_18/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
+    %471 = util.global.address @"__iree_flow_bert/encoder/layer_18/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
+    %472 = util.global.address @"__iree_flow_bert/encoder/layer_18/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
+    %473 = util.global.address @"__iree_flow_bert/encoder/layer_18/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
+    %474 = util.global.address @"__iree_flow_bert/encoder/layer_18/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
+    %475 = util.global.address @"__iree_flow_bert/encoder/layer_18/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
+    %476 = util.global.address @"__iree_flow_bert/encoder/layer_18/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
+    %477 = util.global.address @"__iree_flow_bert/encoder/layer_18/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %478 = util.global.address @"__iree_flow_bert/encoder/layer_18/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %479 = util.global.address @"__iree_flow_bert/encoder/layer_18/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
+    %480 = util.global.address @"__iree_flow_bert/encoder/layer_18/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %481 = util.global.address @"__iree_flow_bert/encoder/layer_18/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %482 = util.global.address @"__iree_flow_bert/encoder/layer_18/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %483 = util.global.address @"__iree_flow_bert/encoder/layer_18/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
+    %484 = util.global.address @"__iree_flow_bert/encoder/layer_18/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %485 = util.global.address @"__iree_flow_bert/encoder/layer_18/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %486 = util.global.address @"__iree_flow_bert/encoder/layer_18/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %487 = util.global.address @"__iree_flow_bert/encoder/layer_18/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %488 = util.global.address @"__iree_flow_bert/encoder/layer_18/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %489 = util.global.address @"__iree_flow_bert/encoder/layer_18/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %490 = util.global.address @"__iree_flow_bert/encoder/layer_18/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %491 = util.global.address @"__iree_flow_bert/encoder/layer_18/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %492 = util.global.address @"__iree_flow_bert/encoder/layer_18/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %493 = util.global.address @"__iree_flow_bert/encoder/layer_18/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %494 = util.global.address @"__iree_flow_bert/encoder/layer_18/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %495 = util.global.address @"__iree_flow_bert/encoder/layer_18/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %496 = util.global.address @"__iree_flow_bert/encoder/layer_18/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %497 = util.global.address @"__iree_flow_bert/encoder/layer_18/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %498 = util.global.address @"__iree_flow_bert/encoder/layer_18/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %499 = util.global.address @"__iree_flow_bert/encoder/layer_18/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %500 = util.global.address @"__iree_flow_bert/encoder/layer_18/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %501 = util.global.address @"__iree_flow_bert/encoder/layer_18/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %502 = util.global.address @"__iree_flow_bert/encoder/layer_18/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %503 = util.global.address @"__iree_flow_bert/encoder/layer_18/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %504 = util.global.address @"__iree_flow_bert/encoder/layer_18/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %505 = util.global.address @"__iree_flow_bert/encoder/layer_18/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %506 = util.global.address @"__iree_flow_bert/encoder/layer_18/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %507 = util.global.address @"__iree_flow_bert/encoder/layer_18/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
+    %508 = util.global.address @"__iree_flow_bert/encoder/layer_18/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
+    %509 = util.global.address @"__iree_flow_bert/encoder/layer_18/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
+    %510 = util.global.address @"__iree_flow_bert/encoder/layer_18/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %511 = util.global.address @"__iree_flow_bert/encoder/layer_18/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %512 = util.global.address @"__iree_flow_bert/encoder/layer_18/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %513 = util.global.address @"__iree_flow_bert/encoder/layer_19/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %514 = util.global.address @"__iree_flow_bert/encoder/layer_19/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %515 = util.global.address @"__iree_flow_bert/encoder/layer_19/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %516 = util.global.address @"__iree_flow_bert/encoder/layer_19/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
+    %517 = util.global.address @"__iree_flow_bert/encoder/layer_19/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
+    %518 = util.global.address @"__iree_flow_bert/encoder/layer_19/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
+    %519 = util.global.address @"__iree_flow_bert/encoder/layer_19/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
+    %520 = util.global.address @"__iree_flow_bert/encoder/layer_19/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
+    %521 = util.global.address @"__iree_flow_bert/encoder/layer_19/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
+    %522 = util.global.address @"__iree_flow_bert/encoder/layer_19/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
+    %523 = util.global.address @"__iree_flow_bert/encoder/layer_19/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %524 = util.global.address @"__iree_flow_bert/encoder/layer_19/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %525 = util.global.address @"__iree_flow_bert/encoder/layer_19/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
+    %526 = util.global.address @"__iree_flow_bert/encoder/layer_19/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %527 = util.global.address @"__iree_flow_bert/encoder/layer_19/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %528 = util.global.address @"__iree_flow_bert/encoder/layer_19/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %529 = util.global.address @"__iree_flow_bert/encoder/layer_19/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
+    %530 = util.global.address @"__iree_flow_bert/encoder/layer_19/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %531 = util.global.address @"__iree_flow_bert/encoder/layer_19/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %532 = util.global.address @"__iree_flow_bert/encoder/layer_19/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %533 = util.global.address @"__iree_flow_bert/encoder/layer_19/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %534 = util.global.address @"__iree_flow_bert/encoder/layer_19/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %535 = util.global.address @"__iree_flow_bert/encoder/layer_19/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %536 = util.global.address @"__iree_flow_bert/encoder/layer_19/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %537 = util.global.address @"__iree_flow_bert/encoder/layer_19/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %538 = util.global.address @"__iree_flow_bert/encoder/layer_19/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %539 = util.global.address @"__iree_flow_bert/encoder/layer_19/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %540 = util.global.address @"__iree_flow_bert/encoder/layer_19/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %541 = util.global.address @"__iree_flow_bert/encoder/layer_19/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %542 = util.global.address @"__iree_flow_bert/encoder/layer_19/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %543 = util.global.address @"__iree_flow_bert/encoder/layer_19/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %544 = util.global.address @"__iree_flow_bert/encoder/layer_19/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %545 = util.global.address @"__iree_flow_bert/encoder/layer_19/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %546 = util.global.address @"__iree_flow_bert/encoder/layer_19/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %547 = util.global.address @"__iree_flow_bert/encoder/layer_19/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %548 = util.global.address @"__iree_flow_bert/encoder/layer_19/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %549 = util.global.address @"__iree_flow_bert/encoder/layer_19/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %550 = util.global.address @"__iree_flow_bert/encoder/layer_19/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %551 = util.global.address @"__iree_flow_bert/encoder/layer_19/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %552 = util.global.address @"__iree_flow_bert/encoder/layer_19/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %553 = util.global.address @"__iree_flow_bert/encoder/layer_19/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
+    %554 = util.global.address @"__iree_flow_bert/encoder/layer_19/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
+    %555 = util.global.address @"__iree_flow_bert/encoder/layer_19/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
+    %556 = util.global.address @"__iree_flow_bert/encoder/layer_19/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %557 = util.global.address @"__iree_flow_bert/encoder/layer_19/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %558 = util.global.address @"__iree_flow_bert/encoder/layer_19/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %559 = util.global.address @"__iree_flow_bert/encoder/layer_2/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %560 = util.global.address @"__iree_flow_bert/encoder/layer_2/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %561 = util.global.address @"__iree_flow_bert/encoder/layer_2/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %562 = util.global.address @"__iree_flow_bert/encoder/layer_2/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
+    %563 = util.global.address @"__iree_flow_bert/encoder/layer_2/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
+    %564 = util.global.address @"__iree_flow_bert/encoder/layer_2/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
+    %565 = util.global.address @"__iree_flow_bert/encoder/layer_2/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
+    %566 = util.global.address @"__iree_flow_bert/encoder/layer_2/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
+    %567 = util.global.address @"__iree_flow_bert/encoder/layer_2/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
+    %568 = util.global.address @"__iree_flow_bert/encoder/layer_2/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
+    %569 = util.global.address @"__iree_flow_bert/encoder/layer_2/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %570 = util.global.address @"__iree_flow_bert/encoder/layer_2/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %571 = util.global.address @"__iree_flow_bert/encoder/layer_2/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
+    %572 = util.global.address @"__iree_flow_bert/encoder/layer_2/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %573 = util.global.address @"__iree_flow_bert/encoder/layer_2/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %574 = util.global.address @"__iree_flow_bert/encoder/layer_2/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %575 = util.global.address @"__iree_flow_bert/encoder/layer_2/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
+    %576 = util.global.address @"__iree_flow_bert/encoder/layer_2/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %577 = util.global.address @"__iree_flow_bert/encoder/layer_2/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %578 = util.global.address @"__iree_flow_bert/encoder/layer_2/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %579 = util.global.address @"__iree_flow_bert/encoder/layer_2/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %580 = util.global.address @"__iree_flow_bert/encoder/layer_2/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %581 = util.global.address @"__iree_flow_bert/encoder/layer_2/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %582 = util.global.address @"__iree_flow_bert/encoder/layer_2/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %583 = util.global.address @"__iree_flow_bert/encoder/layer_2/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %584 = util.global.address @"__iree_flow_bert/encoder/layer_2/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %585 = util.global.address @"__iree_flow_bert/encoder/layer_2/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %586 = util.global.address @"__iree_flow_bert/encoder/layer_2/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %587 = util.global.address @"__iree_flow_bert/encoder/layer_2/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %588 = util.global.address @"__iree_flow_bert/encoder/layer_2/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %589 = util.global.address @"__iree_flow_bert/encoder/layer_2/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %590 = util.global.address @"__iree_flow_bert/encoder/layer_2/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %591 = util.global.address @"__iree_flow_bert/encoder/layer_2/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %592 = util.global.address @"__iree_flow_bert/encoder/layer_2/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %593 = util.global.address @"__iree_flow_bert/encoder/layer_2/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %594 = util.global.address @"__iree_flow_bert/encoder/layer_2/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %595 = util.global.address @"__iree_flow_bert/encoder/layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %596 = util.global.address @"__iree_flow_bert/encoder/layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %597 = util.global.address @"__iree_flow_bert/encoder/layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %598 = util.global.address @"__iree_flow_bert/encoder/layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %599 = util.global.address @"__iree_flow_bert/encoder/layer_2/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
+    %600 = util.global.address @"__iree_flow_bert/encoder/layer_2/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
+    %601 = util.global.address @"__iree_flow_bert/encoder/layer_2/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
+    %602 = util.global.address @"__iree_flow_bert/encoder/layer_2/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %603 = util.global.address @"__iree_flow_bert/encoder/layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %604 = util.global.address @"__iree_flow_bert/encoder/layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %605 = util.global.address @"__iree_flow_bert/encoder/layer_20/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %606 = util.global.address @"__iree_flow_bert/encoder/layer_20/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %607 = util.global.address @"__iree_flow_bert/encoder/layer_20/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %608 = util.global.address @"__iree_flow_bert/encoder/layer_20/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
+    %609 = util.global.address @"__iree_flow_bert/encoder/layer_20/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
+    %610 = util.global.address @"__iree_flow_bert/encoder/layer_20/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
+    %611 = util.global.address @"__iree_flow_bert/encoder/layer_20/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
+    %612 = util.global.address @"__iree_flow_bert/encoder/layer_20/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
+    %613 = util.global.address @"__iree_flow_bert/encoder/layer_20/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
+    %614 = util.global.address @"__iree_flow_bert/encoder/layer_20/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
+    %615 = util.global.address @"__iree_flow_bert/encoder/layer_20/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %616 = util.global.address @"__iree_flow_bert/encoder/layer_20/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %617 = util.global.address @"__iree_flow_bert/encoder/layer_20/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
+    %618 = util.global.address @"__iree_flow_bert/encoder/layer_20/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %619 = util.global.address @"__iree_flow_bert/encoder/layer_20/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %620 = util.global.address @"__iree_flow_bert/encoder/layer_20/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %621 = util.global.address @"__iree_flow_bert/encoder/layer_20/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
+    %622 = util.global.address @"__iree_flow_bert/encoder/layer_20/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %623 = util.global.address @"__iree_flow_bert/encoder/layer_20/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %624 = util.global.address @"__iree_flow_bert/encoder/layer_20/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %625 = util.global.address @"__iree_flow_bert/encoder/layer_20/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %626 = util.global.address @"__iree_flow_bert/encoder/layer_20/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %627 = util.global.address @"__iree_flow_bert/encoder/layer_20/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %628 = util.global.address @"__iree_flow_bert/encoder/layer_20/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %629 = util.global.address @"__iree_flow_bert/encoder/layer_20/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %630 = util.global.address @"__iree_flow_bert/encoder/layer_20/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %631 = util.global.address @"__iree_flow_bert/encoder/layer_20/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %632 = util.global.address @"__iree_flow_bert/encoder/layer_20/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %633 = util.global.address @"__iree_flow_bert/encoder/layer_20/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %634 = util.global.address @"__iree_flow_bert/encoder/layer_20/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %635 = util.global.address @"__iree_flow_bert/encoder/layer_20/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %636 = util.global.address @"__iree_flow_bert/encoder/layer_20/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %637 = util.global.address @"__iree_flow_bert/encoder/layer_20/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %638 = util.global.address @"__iree_flow_bert/encoder/layer_20/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %639 = util.global.address @"__iree_flow_bert/encoder/layer_20/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %640 = util.global.address @"__iree_flow_bert/encoder/layer_20/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %641 = util.global.address @"__iree_flow_bert/encoder/layer_20/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %642 = util.global.address @"__iree_flow_bert/encoder/layer_20/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %643 = util.global.address @"__iree_flow_bert/encoder/layer_20/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %644 = util.global.address @"__iree_flow_bert/encoder/layer_20/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %645 = util.global.address @"__iree_flow_bert/encoder/layer_20/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
+    %646 = util.global.address @"__iree_flow_bert/encoder/layer_20/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
+    %647 = util.global.address @"__iree_flow_bert/encoder/layer_20/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
+    %648 = util.global.address @"__iree_flow_bert/encoder/layer_20/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %649 = util.global.address @"__iree_flow_bert/encoder/layer_20/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %650 = util.global.address @"__iree_flow_bert/encoder/layer_20/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %651 = util.global.address @"__iree_flow_bert/encoder/layer_21/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %652 = util.global.address @"__iree_flow_bert/encoder/layer_21/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %653 = util.global.address @"__iree_flow_bert/encoder/layer_21/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %654 = util.global.address @"__iree_flow_bert/encoder/layer_21/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
+    %655 = util.global.address @"__iree_flow_bert/encoder/layer_21/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
+    %656 = util.global.address @"__iree_flow_bert/encoder/layer_21/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
+    %657 = util.global.address @"__iree_flow_bert/encoder/layer_21/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
+    %658 = util.global.address @"__iree_flow_bert/encoder/layer_21/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
+    %659 = util.global.address @"__iree_flow_bert/encoder/layer_21/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
+    %660 = util.global.address @"__iree_flow_bert/encoder/layer_21/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
+    %661 = util.global.address @"__iree_flow_bert/encoder/layer_21/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %662 = util.global.address @"__iree_flow_bert/encoder/layer_21/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %663 = util.global.address @"__iree_flow_bert/encoder/layer_21/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
+    %664 = util.global.address @"__iree_flow_bert/encoder/layer_21/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %665 = util.global.address @"__iree_flow_bert/encoder/layer_21/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %666 = util.global.address @"__iree_flow_bert/encoder/layer_21/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %667 = util.global.address @"__iree_flow_bert/encoder/layer_21/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
+    %668 = util.global.address @"__iree_flow_bert/encoder/layer_21/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %669 = util.global.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %670 = util.global.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %671 = util.global.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %672 = util.global.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %673 = util.global.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %674 = util.global.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %675 = util.global.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %676 = util.global.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %677 = util.global.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %678 = util.global.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %679 = util.global.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %680 = util.global.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %681 = util.global.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %682 = util.global.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %683 = util.global.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %684 = util.global.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %685 = util.global.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %686 = util.global.address @"__iree_flow_bert/encoder/layer_21/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %687 = util.global.address @"__iree_flow_bert/encoder/layer_21/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %688 = util.global.address @"__iree_flow_bert/encoder/layer_21/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %689 = util.global.address @"__iree_flow_bert/encoder/layer_21/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %690 = util.global.address @"__iree_flow_bert/encoder/layer_21/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %691 = util.global.address @"__iree_flow_bert/encoder/layer_21/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
+    %692 = util.global.address @"__iree_flow_bert/encoder/layer_21/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
+    %693 = util.global.address @"__iree_flow_bert/encoder/layer_21/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
+    %694 = util.global.address @"__iree_flow_bert/encoder/layer_21/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %695 = util.global.address @"__iree_flow_bert/encoder/layer_21/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %696 = util.global.address @"__iree_flow_bert/encoder/layer_21/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %697 = util.global.address @"__iree_flow_bert/encoder/layer_22/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %698 = util.global.address @"__iree_flow_bert/encoder/layer_22/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %699 = util.global.address @"__iree_flow_bert/encoder/layer_22/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %700 = util.global.address @"__iree_flow_bert/encoder/layer_22/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
+    %701 = util.global.address @"__iree_flow_bert/encoder/layer_22/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
+    %702 = util.global.address @"__iree_flow_bert/encoder/layer_22/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
+    %703 = util.global.address @"__iree_flow_bert/encoder/layer_22/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
+    %704 = util.global.address @"__iree_flow_bert/encoder/layer_22/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
+    %705 = util.global.address @"__iree_flow_bert/encoder/layer_22/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
+    %706 = util.global.address @"__iree_flow_bert/encoder/layer_22/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
+    %707 = util.global.address @"__iree_flow_bert/encoder/layer_22/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %708 = util.global.address @"__iree_flow_bert/encoder/layer_22/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %709 = util.global.address @"__iree_flow_bert/encoder/layer_22/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
+    %710 = util.global.address @"__iree_flow_bert/encoder/layer_22/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %711 = util.global.address @"__iree_flow_bert/encoder/layer_22/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %712 = util.global.address @"__iree_flow_bert/encoder/layer_22/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %713 = util.global.address @"__iree_flow_bert/encoder/layer_22/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
+    %714 = util.global.address @"__iree_flow_bert/encoder/layer_22/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %715 = util.global.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %716 = util.global.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %717 = util.global.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %718 = util.global.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %719 = util.global.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %720 = util.global.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %721 = util.global.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %722 = util.global.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %723 = util.global.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %724 = util.global.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %725 = util.global.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %726 = util.global.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %727 = util.global.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %728 = util.global.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %729 = util.global.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %730 = util.global.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %731 = util.global.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %732 = util.global.address @"__iree_flow_bert/encoder/layer_22/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %733 = util.global.address @"__iree_flow_bert/encoder/layer_22/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %734 = util.global.address @"__iree_flow_bert/encoder/layer_22/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %735 = util.global.address @"__iree_flow_bert/encoder/layer_22/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %736 = util.global.address @"__iree_flow_bert/encoder/layer_22/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %737 = util.global.address @"__iree_flow_bert/encoder/layer_22/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
+    %738 = util.global.address @"__iree_flow_bert/encoder/layer_22/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
+    %739 = util.global.address @"__iree_flow_bert/encoder/layer_22/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
+    %740 = util.global.address @"__iree_flow_bert/encoder/layer_22/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %741 = util.global.address @"__iree_flow_bert/encoder/layer_22/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %742 = util.global.address @"__iree_flow_bert/encoder/layer_22/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %743 = util.global.address @"__iree_flow_bert/encoder/layer_23/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %744 = util.global.address @"__iree_flow_bert/encoder/layer_23/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %745 = util.global.address @"__iree_flow_bert/encoder/layer_23/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %746 = util.global.address @"__iree_flow_bert/encoder/layer_23/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
+    %747 = util.global.address @"__iree_flow_bert/encoder/layer_23/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
+    %748 = util.global.address @"__iree_flow_bert/encoder/layer_23/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
+    %749 = util.global.address @"__iree_flow_bert/encoder/layer_23/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
+    %750 = util.global.address @"__iree_flow_bert/encoder/layer_23/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
+    %751 = util.global.address @"__iree_flow_bert/encoder/layer_23/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
+    %752 = util.global.address @"__iree_flow_bert/encoder/layer_23/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
+    %753 = util.global.address @"__iree_flow_bert/encoder/layer_23/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %754 = util.global.address @"__iree_flow_bert/encoder/layer_23/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %755 = util.global.address @"__iree_flow_bert/encoder/layer_23/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
+    %756 = util.global.address @"__iree_flow_bert/encoder/layer_23/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %757 = util.global.address @"__iree_flow_bert/encoder/layer_23/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %758 = util.global.address @"__iree_flow_bert/encoder/layer_23/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %759 = util.global.address @"__iree_flow_bert/encoder/layer_23/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
+    %760 = util.global.address @"__iree_flow_bert/encoder/layer_23/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %761 = util.global.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %762 = util.global.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %763 = util.global.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %764 = util.global.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %765 = util.global.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %766 = util.global.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %767 = util.global.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %768 = util.global.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %769 = util.global.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %770 = util.global.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %771 = util.global.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %772 = util.global.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %773 = util.global.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %774 = util.global.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %775 = util.global.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %776 = util.global.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %777 = util.global.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %778 = util.global.address @"__iree_flow_bert/encoder/layer_23/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %779 = util.global.address @"__iree_flow_bert/encoder/layer_23/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %780 = util.global.address @"__iree_flow_bert/encoder/layer_23/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %781 = util.global.address @"__iree_flow_bert/encoder/layer_23/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %782 = util.global.address @"__iree_flow_bert/encoder/layer_23/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %783 = util.global.address @"__iree_flow_bert/encoder/layer_23/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
+    %784 = util.global.address @"__iree_flow_bert/encoder/layer_23/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
+    %785 = util.global.address @"__iree_flow_bert/encoder/layer_23/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
+    %786 = util.global.address @"__iree_flow_bert/encoder/layer_23/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %787 = util.global.address @"__iree_flow_bert/encoder/layer_23/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %788 = util.global.address @"__iree_flow_bert/encoder/layer_23/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %789 = util.global.address @"__iree_flow_bert/encoder/layer_3/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %790 = util.global.address @"__iree_flow_bert/encoder/layer_3/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %791 = util.global.address @"__iree_flow_bert/encoder/layer_3/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %792 = util.global.address @"__iree_flow_bert/encoder/layer_3/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
+    %793 = util.global.address @"__iree_flow_bert/encoder/layer_3/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
+    %794 = util.global.address @"__iree_flow_bert/encoder/layer_3/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
+    %795 = util.global.address @"__iree_flow_bert/encoder/layer_3/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
+    %796 = util.global.address @"__iree_flow_bert/encoder/layer_3/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
+    %797 = util.global.address @"__iree_flow_bert/encoder/layer_3/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
+    %798 = util.global.address @"__iree_flow_bert/encoder/layer_3/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
+    %799 = util.global.address @"__iree_flow_bert/encoder/layer_3/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %800 = util.global.address @"__iree_flow_bert/encoder/layer_3/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %801 = util.global.address @"__iree_flow_bert/encoder/layer_3/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
+    %802 = util.global.address @"__iree_flow_bert/encoder/layer_3/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %803 = util.global.address @"__iree_flow_bert/encoder/layer_3/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %804 = util.global.address @"__iree_flow_bert/encoder/layer_3/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %805 = util.global.address @"__iree_flow_bert/encoder/layer_3/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
+    %806 = util.global.address @"__iree_flow_bert/encoder/layer_3/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %807 = util.global.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %808 = util.global.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %809 = util.global.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %810 = util.global.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %811 = util.global.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %812 = util.global.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %813 = util.global.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %814 = util.global.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %815 = util.global.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %816 = util.global.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %817 = util.global.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %818 = util.global.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %819 = util.global.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %820 = util.global.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %821 = util.global.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %822 = util.global.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %823 = util.global.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %824 = util.global.address @"__iree_flow_bert/encoder/layer_3/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %825 = util.global.address @"__iree_flow_bert/encoder/layer_3/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %826 = util.global.address @"__iree_flow_bert/encoder/layer_3/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %827 = util.global.address @"__iree_flow_bert/encoder/layer_3/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %828 = util.global.address @"__iree_flow_bert/encoder/layer_3/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %829 = util.global.address @"__iree_flow_bert/encoder/layer_3/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
+    %830 = util.global.address @"__iree_flow_bert/encoder/layer_3/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
+    %831 = util.global.address @"__iree_flow_bert/encoder/layer_3/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
+    %832 = util.global.address @"__iree_flow_bert/encoder/layer_3/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %833 = util.global.address @"__iree_flow_bert/encoder/layer_3/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %834 = util.global.address @"__iree_flow_bert/encoder/layer_3/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %835 = util.global.address @"__iree_flow_bert/encoder/layer_4/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %836 = util.global.address @"__iree_flow_bert/encoder/layer_4/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %837 = util.global.address @"__iree_flow_bert/encoder/layer_4/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %838 = util.global.address @"__iree_flow_bert/encoder/layer_4/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
+    %839 = util.global.address @"__iree_flow_bert/encoder/layer_4/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
+    %840 = util.global.address @"__iree_flow_bert/encoder/layer_4/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
+    %841 = util.global.address @"__iree_flow_bert/encoder/layer_4/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
+    %842 = util.global.address @"__iree_flow_bert/encoder/layer_4/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
+    %843 = util.global.address @"__iree_flow_bert/encoder/layer_4/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
+    %844 = util.global.address @"__iree_flow_bert/encoder/layer_4/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
+    %845 = util.global.address @"__iree_flow_bert/encoder/layer_4/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %846 = util.global.address @"__iree_flow_bert/encoder/layer_4/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %847 = util.global.address @"__iree_flow_bert/encoder/layer_4/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
+    %848 = util.global.address @"__iree_flow_bert/encoder/layer_4/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %849 = util.global.address @"__iree_flow_bert/encoder/layer_4/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %850 = util.global.address @"__iree_flow_bert/encoder/layer_4/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %851 = util.global.address @"__iree_flow_bert/encoder/layer_4/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
+    %852 = util.global.address @"__iree_flow_bert/encoder/layer_4/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %853 = util.global.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %854 = util.global.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %855 = util.global.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %856 = util.global.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %857 = util.global.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %858 = util.global.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %859 = util.global.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %860 = util.global.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %861 = util.global.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %862 = util.global.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %863 = util.global.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %864 = util.global.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %865 = util.global.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %866 = util.global.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %867 = util.global.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %868 = util.global.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %869 = util.global.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %870 = util.global.address @"__iree_flow_bert/encoder/layer_4/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %871 = util.global.address @"__iree_flow_bert/encoder/layer_4/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %872 = util.global.address @"__iree_flow_bert/encoder/layer_4/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %873 = util.global.address @"__iree_flow_bert/encoder/layer_4/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %874 = util.global.address @"__iree_flow_bert/encoder/layer_4/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %875 = util.global.address @"__iree_flow_bert/encoder/layer_4/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
+    %876 = util.global.address @"__iree_flow_bert/encoder/layer_4/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
+    %877 = util.global.address @"__iree_flow_bert/encoder/layer_4/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
+    %878 = util.global.address @"__iree_flow_bert/encoder/layer_4/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %879 = util.global.address @"__iree_flow_bert/encoder/layer_4/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %880 = util.global.address @"__iree_flow_bert/encoder/layer_4/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %881 = util.global.address @"__iree_flow_bert/encoder/layer_5/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %882 = util.global.address @"__iree_flow_bert/encoder/layer_5/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %883 = util.global.address @"__iree_flow_bert/encoder/layer_5/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %884 = util.global.address @"__iree_flow_bert/encoder/layer_5/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
+    %885 = util.global.address @"__iree_flow_bert/encoder/layer_5/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
+    %886 = util.global.address @"__iree_flow_bert/encoder/layer_5/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
+    %887 = util.global.address @"__iree_flow_bert/encoder/layer_5/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
+    %888 = util.global.address @"__iree_flow_bert/encoder/layer_5/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
+    %889 = util.global.address @"__iree_flow_bert/encoder/layer_5/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
+    %890 = util.global.address @"__iree_flow_bert/encoder/layer_5/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
+    %891 = util.global.address @"__iree_flow_bert/encoder/layer_5/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %892 = util.global.address @"__iree_flow_bert/encoder/layer_5/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %893 = util.global.address @"__iree_flow_bert/encoder/layer_5/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
+    %894 = util.global.address @"__iree_flow_bert/encoder/layer_5/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %895 = util.global.address @"__iree_flow_bert/encoder/layer_5/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %896 = util.global.address @"__iree_flow_bert/encoder/layer_5/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %897 = util.global.address @"__iree_flow_bert/encoder/layer_5/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
+    %898 = util.global.address @"__iree_flow_bert/encoder/layer_5/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %899 = util.global.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %900 = util.global.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %901 = util.global.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %902 = util.global.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %903 = util.global.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %904 = util.global.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %905 = util.global.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %906 = util.global.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %907 = util.global.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %908 = util.global.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %909 = util.global.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %910 = util.global.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %911 = util.global.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %912 = util.global.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %913 = util.global.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %914 = util.global.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %915 = util.global.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %916 = util.global.address @"__iree_flow_bert/encoder/layer_5/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %917 = util.global.address @"__iree_flow_bert/encoder/layer_5/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %918 = util.global.address @"__iree_flow_bert/encoder/layer_5/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %919 = util.global.address @"__iree_flow_bert/encoder/layer_5/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %920 = util.global.address @"__iree_flow_bert/encoder/layer_5/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %921 = util.global.address @"__iree_flow_bert/encoder/layer_5/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
+    %922 = util.global.address @"__iree_flow_bert/encoder/layer_5/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
+    %923 = util.global.address @"__iree_flow_bert/encoder/layer_5/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
+    %924 = util.global.address @"__iree_flow_bert/encoder/layer_5/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %925 = util.global.address @"__iree_flow_bert/encoder/layer_5/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %926 = util.global.address @"__iree_flow_bert/encoder/layer_5/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %927 = util.global.address @"__iree_flow_bert/encoder/layer_6/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %928 = util.global.address @"__iree_flow_bert/encoder/layer_6/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %929 = util.global.address @"__iree_flow_bert/encoder/layer_6/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %930 = util.global.address @"__iree_flow_bert/encoder/layer_6/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
+    %931 = util.global.address @"__iree_flow_bert/encoder/layer_6/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
+    %932 = util.global.address @"__iree_flow_bert/encoder/layer_6/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
+    %933 = util.global.address @"__iree_flow_bert/encoder/layer_6/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
+    %934 = util.global.address @"__iree_flow_bert/encoder/layer_6/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
+    %935 = util.global.address @"__iree_flow_bert/encoder/layer_6/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
+    %936 = util.global.address @"__iree_flow_bert/encoder/layer_6/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
+    %937 = util.global.address @"__iree_flow_bert/encoder/layer_6/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %938 = util.global.address @"__iree_flow_bert/encoder/layer_6/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %939 = util.global.address @"__iree_flow_bert/encoder/layer_6/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
+    %940 = util.global.address @"__iree_flow_bert/encoder/layer_6/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %941 = util.global.address @"__iree_flow_bert/encoder/layer_6/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %942 = util.global.address @"__iree_flow_bert/encoder/layer_6/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %943 = util.global.address @"__iree_flow_bert/encoder/layer_6/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
+    %944 = util.global.address @"__iree_flow_bert/encoder/layer_6/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %945 = util.global.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %946 = util.global.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %947 = util.global.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %948 = util.global.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %949 = util.global.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %950 = util.global.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %951 = util.global.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %952 = util.global.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %953 = util.global.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %954 = util.global.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %955 = util.global.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %956 = util.global.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %957 = util.global.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %958 = util.global.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %959 = util.global.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %960 = util.global.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %961 = util.global.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %962 = util.global.address @"__iree_flow_bert/encoder/layer_6/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %963 = util.global.address @"__iree_flow_bert/encoder/layer_6/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %964 = util.global.address @"__iree_flow_bert/encoder/layer_6/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %965 = util.global.address @"__iree_flow_bert/encoder/layer_6/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %966 = util.global.address @"__iree_flow_bert/encoder/layer_6/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %967 = util.global.address @"__iree_flow_bert/encoder/layer_6/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
+    %968 = util.global.address @"__iree_flow_bert/encoder/layer_6/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
+    %969 = util.global.address @"__iree_flow_bert/encoder/layer_6/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
+    %970 = util.global.address @"__iree_flow_bert/encoder/layer_6/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %971 = util.global.address @"__iree_flow_bert/encoder/layer_6/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %972 = util.global.address @"__iree_flow_bert/encoder/layer_6/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %973 = util.global.address @"__iree_flow_bert/encoder/layer_7/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %974 = util.global.address @"__iree_flow_bert/encoder/layer_7/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %975 = util.global.address @"__iree_flow_bert/encoder/layer_7/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %976 = util.global.address @"__iree_flow_bert/encoder/layer_7/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
+    %977 = util.global.address @"__iree_flow_bert/encoder/layer_7/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
+    %978 = util.global.address @"__iree_flow_bert/encoder/layer_7/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
+    %979 = util.global.address @"__iree_flow_bert/encoder/layer_7/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
+    %980 = util.global.address @"__iree_flow_bert/encoder/layer_7/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
+    %981 = util.global.address @"__iree_flow_bert/encoder/layer_7/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
+    %982 = util.global.address @"__iree_flow_bert/encoder/layer_7/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
+    %983 = util.global.address @"__iree_flow_bert/encoder/layer_7/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %984 = util.global.address @"__iree_flow_bert/encoder/layer_7/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %985 = util.global.address @"__iree_flow_bert/encoder/layer_7/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
+    %986 = util.global.address @"__iree_flow_bert/encoder/layer_7/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %987 = util.global.address @"__iree_flow_bert/encoder/layer_7/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %988 = util.global.address @"__iree_flow_bert/encoder/layer_7/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %989 = util.global.address @"__iree_flow_bert/encoder/layer_7/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
+    %990 = util.global.address @"__iree_flow_bert/encoder/layer_7/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %991 = util.global.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %992 = util.global.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %993 = util.global.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %994 = util.global.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %995 = util.global.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %996 = util.global.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %997 = util.global.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %998 = util.global.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %999 = util.global.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %1000 = util.global.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %1001 = util.global.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %1002 = util.global.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %1003 = util.global.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %1004 = util.global.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %1005 = util.global.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %1006 = util.global.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %1007 = util.global.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %1008 = util.global.address @"__iree_flow_bert/encoder/layer_7/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %1009 = util.global.address @"__iree_flow_bert/encoder/layer_7/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %1010 = util.global.address @"__iree_flow_bert/encoder/layer_7/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %1011 = util.global.address @"__iree_flow_bert/encoder/layer_7/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %1012 = util.global.address @"__iree_flow_bert/encoder/layer_7/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %1013 = util.global.address @"__iree_flow_bert/encoder/layer_7/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
+    %1014 = util.global.address @"__iree_flow_bert/encoder/layer_7/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
+    %1015 = util.global.address @"__iree_flow_bert/encoder/layer_7/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
+    %1016 = util.global.address @"__iree_flow_bert/encoder/layer_7/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %1017 = util.global.address @"__iree_flow_bert/encoder/layer_7/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %1018 = util.global.address @"__iree_flow_bert/encoder/layer_7/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %1019 = util.global.address @"__iree_flow_bert/encoder/layer_8/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %1020 = util.global.address @"__iree_flow_bert/encoder/layer_8/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %1021 = util.global.address @"__iree_flow_bert/encoder/layer_8/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %1022 = util.global.address @"__iree_flow_bert/encoder/layer_8/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
+    %1023 = util.global.address @"__iree_flow_bert/encoder/layer_8/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
+    %1024 = util.global.address @"__iree_flow_bert/encoder/layer_8/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
+    %1025 = util.global.address @"__iree_flow_bert/encoder/layer_8/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
+    %1026 = util.global.address @"__iree_flow_bert/encoder/layer_8/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
+    %1027 = util.global.address @"__iree_flow_bert/encoder/layer_8/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
+    %1028 = util.global.address @"__iree_flow_bert/encoder/layer_8/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
+    %1029 = util.global.address @"__iree_flow_bert/encoder/layer_8/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %1030 = util.global.address @"__iree_flow_bert/encoder/layer_8/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %1031 = util.global.address @"__iree_flow_bert/encoder/layer_8/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
+    %1032 = util.global.address @"__iree_flow_bert/encoder/layer_8/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %1033 = util.global.address @"__iree_flow_bert/encoder/layer_8/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %1034 = util.global.address @"__iree_flow_bert/encoder/layer_8/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %1035 = util.global.address @"__iree_flow_bert/encoder/layer_8/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
+    %1036 = util.global.address @"__iree_flow_bert/encoder/layer_8/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %1037 = util.global.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %1038 = util.global.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %1039 = util.global.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %1040 = util.global.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %1041 = util.global.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %1042 = util.global.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %1043 = util.global.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %1044 = util.global.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %1045 = util.global.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %1046 = util.global.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %1047 = util.global.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %1048 = util.global.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %1049 = util.global.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %1050 = util.global.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %1051 = util.global.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %1052 = util.global.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %1053 = util.global.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %1054 = util.global.address @"__iree_flow_bert/encoder/layer_8/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %1055 = util.global.address @"__iree_flow_bert/encoder/layer_8/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %1056 = util.global.address @"__iree_flow_bert/encoder/layer_8/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %1057 = util.global.address @"__iree_flow_bert/encoder/layer_8/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %1058 = util.global.address @"__iree_flow_bert/encoder/layer_8/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %1059 = util.global.address @"__iree_flow_bert/encoder/layer_8/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
+    %1060 = util.global.address @"__iree_flow_bert/encoder/layer_8/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
+    %1061 = util.global.address @"__iree_flow_bert/encoder/layer_8/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
+    %1062 = util.global.address @"__iree_flow_bert/encoder/layer_8/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %1063 = util.global.address @"__iree_flow_bert/encoder/layer_8/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %1064 = util.global.address @"__iree_flow_bert/encoder/layer_8/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %1065 = util.global.address @"__iree_flow_bert/encoder/layer_9/attention/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %1066 = util.global.address @"__iree_flow_bert/encoder/layer_9/attention/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %1067 = util.global.address @"__iree_flow_bert/encoder/layer_9/attention/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %1068 = util.global.address @"__iree_flow_bert/encoder/layer_9/attention/output/dense/kernel" : !util.ptr<tensor<128x128xf32>>
+    %1069 = util.global.address @"__iree_flow_bert/encoder/layer_9/attention/self/key/bias" : !util.ptr<tensor<128xf32>>
+    %1070 = util.global.address @"__iree_flow_bert/encoder/layer_9/attention/self/key/kernel" : !util.ptr<tensor<128x128xf32>>
+    %1071 = util.global.address @"__iree_flow_bert/encoder/layer_9/attention/self/query/bias" : !util.ptr<tensor<128xf32>>
+    %1072 = util.global.address @"__iree_flow_bert/encoder/layer_9/attention/self/query/kernel" : !util.ptr<tensor<128x128xf32>>
+    %1073 = util.global.address @"__iree_flow_bert/encoder/layer_9/attention/self/value/bias" : !util.ptr<tensor<128xf32>>
+    %1074 = util.global.address @"__iree_flow_bert/encoder/layer_9/attention/self/value/kernel" : !util.ptr<tensor<512x128xf32>>
+    %1075 = util.global.address @"__iree_flow_bert/encoder/layer_9/bottleneck/attention/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %1076 = util.global.address @"__iree_flow_bert/encoder/layer_9/bottleneck/attention/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %1077 = util.global.address @"__iree_flow_bert/encoder/layer_9/bottleneck/attention/dense/bias" : !util.ptr<tensor<128xf32>>
+    %1078 = util.global.address @"__iree_flow_bert/encoder/layer_9/bottleneck/attention/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %1079 = util.global.address @"__iree_flow_bert/encoder/layer_9/bottleneck/input/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %1080 = util.global.address @"__iree_flow_bert/encoder/layer_9/bottleneck/input/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %1081 = util.global.address @"__iree_flow_bert/encoder/layer_9/bottleneck/input/dense/bias" : !util.ptr<tensor<128xf32>>
+    %1082 = util.global.address @"__iree_flow_bert/encoder/layer_9/bottleneck/input/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %1083 = util.global.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_0/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %1084 = util.global.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_0/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %1085 = util.global.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_0/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %1086 = util.global.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_0/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %1087 = util.global.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_0/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %1088 = util.global.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_0/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %1089 = util.global.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_1/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %1090 = util.global.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_1/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %1091 = util.global.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_1/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %1092 = util.global.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_1/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %1093 = util.global.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_1/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %1094 = util.global.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_1/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %1095 = util.global.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_2/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %1096 = util.global.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_2/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %1097 = util.global.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_2/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %1098 = util.global.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_2/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %1099 = util.global.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_2/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %1100 = util.global.address @"__iree_flow_bert/encoder/layer_9/ffn_layer_2/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %1101 = util.global.address @"__iree_flow_bert/encoder/layer_9/intermediate/dense/bias" : !util.ptr<tensor<512xf32>>
+    %1102 = util.global.address @"__iree_flow_bert/encoder/layer_9/intermediate/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %1103 = util.global.address @"__iree_flow_bert/encoder/layer_9/output/FakeLayerNorm/beta" : !util.ptr<tensor<128xf32>>
+    %1104 = util.global.address @"__iree_flow_bert/encoder/layer_9/output/FakeLayerNorm/gamma" : !util.ptr<tensor<128xf32>>
+    %1105 = util.global.address @"__iree_flow_bert/encoder/layer_9/output/bottleneck/FakeLayerNorm/beta" : !util.ptr<tensor<512xf32>>
+    %1106 = util.global.address @"__iree_flow_bert/encoder/layer_9/output/bottleneck/FakeLayerNorm/gamma" : !util.ptr<tensor<512xf32>>
+    %1107 = util.global.address @"__iree_flow_bert/encoder/layer_9/output/bottleneck/dense/bias" : !util.ptr<tensor<512xf32>>
+    %1108 = util.global.address @"__iree_flow_bert/encoder/layer_9/output/bottleneck/dense/kernel" : !util.ptr<tensor<128x512xf32>>
+    %1109 = util.global.address @"__iree_flow_bert/encoder/layer_9/output/dense/bias" : !util.ptr<tensor<128xf32>>
+    %1110 = util.global.address @"__iree_flow_bert/encoder/layer_9/output/dense/kernel" : !util.ptr<tensor<512x128xf32>>
+    %1111 = util.global.address @"__iree_flow_cls/squad/output_bias" : !util.ptr<tensor<2xf32>>
+    %1112 = util.global.address @"__iree_flow_cls/squad/output_weights" : !util.ptr<tensor<2x512xf32>>
     %1113 = mhlo.constant dense<-1.000000e+04> : tensor<1x1x384x384xf32>
     %1114 = mhlo.constant dense<0.176776692> : tensor<1x4x384x384xf32>
     %1115 = mhlo.constant dense<1.000000e+04> : tensor<1x1x384x384xf32>
@@ -2238,1121 +2238,1121 @@
     %1117 = mhlo.constant dense<0xFF800000> : tensor<f32>
     %1118 = mhlo.constant dense<0.000000e+00> : tensor<f32>
     %1119 = mhlo.constant dense<0.000000e+00> : tensor<1x384x512xf32>
-    %1120 = flow.variable.load.indirect %0 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1121 = flow.variable.load.indirect %1 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1122 = flow.variable.load.indirect %2 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1123 = flow.variable.load.indirect %3 : !util.ptr<tensor<384x512xf32>> -> tensor<384x512xf32>
-    %1124 = flow.variable.load.indirect %4 : !util.ptr<tensor<512x512xf32>> -> tensor<512x512xf32>
+    %1120 = util.global.load.indirect %0 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %1121 = util.global.load.indirect %1 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %1122 = util.global.load.indirect %2 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %1123 = util.global.load.indirect %3 : !util.ptr<tensor<384x512xf32>> -> tensor<384x512xf32>
+    %1124 = util.global.load.indirect %4 : !util.ptr<tensor<512x512xf32>> -> tensor<512x512xf32>
     %1125 = "mhlo.slice"(%1124) {limit_indices = dense<[384, 512]> : tensor<2xi64>, start_indices = dense<0> : tensor<2xi64>, strides = dense<1> : tensor<2xi64>} : (tensor<512x512xf32>) -> tensor<384x512xf32>
     %1126 = "mhlo.reshape"(%1125) : (tensor<384x512xf32>) -> tensor<1x384x512xf32>
-    %1127 = flow.variable.load.indirect %5 : !util.ptr<tensor<2x512xf32>> -> tensor<2x512xf32>
-    %1128 = flow.variable.load.indirect %6 : !util.ptr<tensor<30522x128xf32>> -> tensor<30522x128xf32>
-    %1129 = flow.variable.load.indirect %7 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1130 = flow.variable.load.indirect %8 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1131 = flow.variable.load.indirect %9 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1132 = flow.variable.load.indirect %10 : !util.ptr<tensor<128x128xf32>> -> tensor<128x128xf32>
-    %1133 = flow.variable.load.indirect %11 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1134 = flow.variable.load.indirect %12 : !util.ptr<tensor<128x128xf32>> -> tensor<128x128xf32>
-    %1135 = flow.variable.load.indirect %13 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1136 = flow.variable.load.indirect %14 : !util.ptr<tensor<128x128xf32>> -> tensor<128x128xf32>
-    %1137 = flow.variable.load.indirect %15 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1138 = flow.variable.load.indirect %16 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1139 = flow.variable.load.indirect %17 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1140 = flow.variable.load.indirect %18 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1141 = flow.variable.load.indirect %19 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1142 = flow.variable.load.indirect %20 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1143 = flow.variable.load.indirect %21 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1144 = flow.variable.load.indirect %22 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1145 = flow.variable.load.indirect %23 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1146 = flow.variable.load.indirect %24 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1147 = flow.variable.load.indirect %25 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1148 = flow.variable.load.indirect %26 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
-    %1149 = flow.variable.load.indirect %27 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1150 = flow.variable.load.indirect %28 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1151 = flow.variable.load.indirect %29 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1152 = flow.variable.load.indirect %30 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1153 = flow.variable.load.indirect %31 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1154 = flow.variable.load.indirect %32 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
-    %1155 = flow.variable.load.indirect %33 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1156 = flow.variable.load.indirect %34 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1157 = flow.variable.load.indirect %35 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1158 = flow.variable.load.indirect %36 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1159 = flow.variable.load.indirect %37 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1160 = flow.variable.load.indirect %38 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
-    %1161 = flow.variable.load.indirect %39 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1162 = flow.variable.load.indirect %40 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1163 = flow.variable.load.indirect %41 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1164 = flow.variable.load.indirect %42 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1165 = flow.variable.load.indirect %43 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1166 = flow.variable.load.indirect %44 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
-    %1167 = flow.variable.load.indirect %45 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1168 = flow.variable.load.indirect %46 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1169 = flow.variable.load.indirect %47 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1170 = flow.variable.load.indirect %48 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1171 = flow.variable.load.indirect %49 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1172 = flow.variable.load.indirect %50 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
-    %1173 = flow.variable.load.indirect %51 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1174 = flow.variable.load.indirect %52 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1175 = flow.variable.load.indirect %53 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1176 = flow.variable.load.indirect %54 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1177 = flow.variable.load.indirect %55 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1178 = flow.variable.load.indirect %56 : !util.ptr<tensor<128x128xf32>> -> tensor<128x128xf32>
-    %1179 = flow.variable.load.indirect %57 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1180 = flow.variable.load.indirect %58 : !util.ptr<tensor<128x128xf32>> -> tensor<128x128xf32>
-    %1181 = flow.variable.load.indirect %59 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1182 = flow.variable.load.indirect %60 : !util.ptr<tensor<128x128xf32>> -> tensor<128x128xf32>
-    %1183 = flow.variable.load.indirect %61 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1184 = flow.variable.load.indirect %62 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1185 = flow.variable.load.indirect %63 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1186 = flow.variable.load.indirect %64 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1187 = flow.variable.load.indirect %65 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1188 = flow.variable.load.indirect %66 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1189 = flow.variable.load.indirect %67 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1190 = flow.variable.load.indirect %68 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1191 = flow.variable.load.indirect %69 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1192 = flow.variable.load.indirect %70 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1193 = flow.variable.load.indirect %71 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1194 = flow.variable.load.indirect %72 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
-    %1195 = flow.variable.load.indirect %73 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1196 = flow.variable.load.indirect %74 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1197 = flow.variable.load.indirect %75 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1198 = flow.variable.load.indirect %76 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1199 = flow.variable.load.indirect %77 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1200 = flow.variable.load.indirect %78 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
-    %1201 = flow.variable.load.indirect %79 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1202 = flow.variable.load.indirect %80 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1203 = flow.variable.load.indirect %81 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1204 = flow.variable.load.indirect %82 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1205 = flow.variable.load.indirect %83 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1206 = flow.variable.load.indirect %84 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
-    %1207 = flow.variable.load.indirect %85 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1208 = flow.variable.load.indirect %86 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1209 = flow.variable.load.indirect %87 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1210 = flow.variable.load.indirect %88 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1211 = flow.variable.load.indirect %89 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1212 = flow.variable.load.indirect %90 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
-    %1213 = flow.variable.load.indirect %91 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1214 = flow.variable.load.indirect %92 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1215 = flow.variable.load.indirect %93 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1216 = flow.variable.load.indirect %94 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1217 = flow.variable.load.indirect %95 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1218 = flow.variable.load.indirect %96 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
-    %1219 = flow.variable.load.indirect %97 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1220 = flow.variable.load.indirect %98 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1221 = flow.variable.load.indirect %99 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1222 = flow.variable.load.indirect %100 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1223 = flow.variable.load.indirect %101 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1224 = flow.variable.load.indirect %102 : !util.ptr<tensor<128x128xf32>> -> tensor<128x128xf32>
-    %1225 = flow.variable.load.indirect %103 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1226 = flow.variable.load.indirect %104 : !util.ptr<tensor<128x128xf32>> -> tensor<128x128xf32>
-    %1227 = flow.variable.load.indirect %105 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1228 = flow.variable.load.indirect %106 : !util.ptr<tensor<128x128xf32>> -> tensor<128x128xf32>
-    %1229 = flow.variable.load.indirect %107 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1230 = flow.variable.load.indirect %108 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1231 = flow.variable.load.indirect %109 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1232 = flow.variable.load.indirect %110 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1233 = flow.variable.load.indirect %111 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1234 = flow.variable.load.indirect %112 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1235 = flow.variable.load.indirect %113 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1236 = flow.variable.load.indirect %114 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1237 = flow.variable.load.indirect %115 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1238 = flow.variable.load.indirect %116 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1239 = flow.variable.load.indirect %117 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1240 = flow.variable.load.indirect %118 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
-    %1241 = flow.variable.load.indirect %119 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1242 = flow.variable.load.indirect %120 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1243 = flow.variable.load.indirect %121 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1244 = flow.variable.load.indirect %122 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1245 = flow.variable.load.indirect %123 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1246 = flow.variable.load.indirect %124 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
-    %1247 = flow.variable.load.indirect %125 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1248 = flow.variable.load.indirect %126 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1249 = flow.variable.load.indirect %127 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1250 = flow.variable.load.indirect %128 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1251 = flow.variable.load.indirect %129 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1252 = flow.variable.load.indirect %130 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
-    %1253 = flow.variable.load.indirect %131 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1254 = flow.variable.load.indirect %132 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1255 = flow.variable.load.indirect %133 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1256 = flow.variable.load.indirect %134 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1257 = flow.variable.load.indirect %135 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1258 = flow.variable.load.indirect %136 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
-    %1259 = flow.variable.load.indirect %137 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1260 = flow.variable.load.indirect %138 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1261 = flow.variable.load.indirect %139 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1262 = flow.variable.load.indirect %140 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1263 = flow.variable.load.indirect %141 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1264 = flow.variable.load.indirect %142 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
-    %1265 = flow.variable.load.indirect %143 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1266 = flow.variable.load.indirect %144 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1267 = flow.variable.load.indirect %145 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1268 = flow.variable.load.indirect %146 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1269 = flow.variable.load.indirect %147 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1270 = flow.variable.load.indirect %148 : !util.ptr<tensor<128x128xf32>> -> tensor<128x128xf32>
-    %1271 = flow.variable.load.indirect %149 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1272 = flow.variable.load.indirect %150 : !util.ptr<tensor<128x128xf32>> -> tensor<128x128xf32>
-    %1273 = flow.variable.load.indirect %151 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1274 = flow.variable.load.indirect %152 : !util.ptr<tensor<128x128xf32>> -> tensor<128x128xf32>
-    %1275 = flow.variable.load.indirect %153 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1276 = flow.variable.load.indirect %154 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1277 = flow.variable.load.indirect %155 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1278 = flow.variable.load.indirect %156 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1279 = flow.variable.load.indirect %157 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1280 = flow.variable.load.indirect %158 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1281 = flow.variable.load.indirect %159 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1282 = flow.variable.load.indirect %160 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1283 = flow.variable.load.indirect %161 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1284 = flow.variable.load.indirect %162 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1285 = flow.variable.load.indirect %163 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1286 = flow.variable.load.indirect %164 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
-    %1287 = flow.variable.load.indirect %165 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1288 = flow.variable.load.indirect %166 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1289 = flow.variable.load.indirect %167 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1290 = flow.variable.load.indirect %168 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1291 = flow.variable.load.indirect %169 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1292 = flow.variable.load.indirect %170 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
-    %1293 = flow.variable.load.indirect %171 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1294 = flow.variable.load.indirect %172 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1295 = flow.variable.load.indirect %173 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1296 = flow.variable.load.indirect %174 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1297 = flow.variable.load.indirect %175 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1298 = flow.variable.load.indirect %176 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
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-    %1301 = flow.variable.load.indirect %179 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1302 = flow.variable.load.indirect %180 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1303 = flow.variable.load.indirect %181 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1304 = flow.variable.load.indirect %182 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
-    %1305 = flow.variable.load.indirect %183 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1306 = flow.variable.load.indirect %184 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1307 = flow.variable.load.indirect %185 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1308 = flow.variable.load.indirect %186 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1309 = flow.variable.load.indirect %187 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1310 = flow.variable.load.indirect %188 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
-    %1311 = flow.variable.load.indirect %189 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1312 = flow.variable.load.indirect %190 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1313 = flow.variable.load.indirect %191 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1314 = flow.variable.load.indirect %192 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1315 = flow.variable.load.indirect %193 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1316 = flow.variable.load.indirect %194 : !util.ptr<tensor<128x128xf32>> -> tensor<128x128xf32>
-    %1317 = flow.variable.load.indirect %195 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1318 = flow.variable.load.indirect %196 : !util.ptr<tensor<128x128xf32>> -> tensor<128x128xf32>
-    %1319 = flow.variable.load.indirect %197 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1320 = flow.variable.load.indirect %198 : !util.ptr<tensor<128x128xf32>> -> tensor<128x128xf32>
-    %1321 = flow.variable.load.indirect %199 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1322 = flow.variable.load.indirect %200 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1323 = flow.variable.load.indirect %201 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1324 = flow.variable.load.indirect %202 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1325 = flow.variable.load.indirect %203 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1326 = flow.variable.load.indirect %204 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1327 = flow.variable.load.indirect %205 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1328 = flow.variable.load.indirect %206 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1329 = flow.variable.load.indirect %207 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1330 = flow.variable.load.indirect %208 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1331 = flow.variable.load.indirect %209 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1332 = flow.variable.load.indirect %210 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
-    %1333 = flow.variable.load.indirect %211 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
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-    %1547 = flow.variable.load.indirect %425 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1548 = flow.variable.load.indirect %426 : !util.ptr<tensor<128x128xf32>> -> tensor<128x128xf32>
-    %1549 = flow.variable.load.indirect %427 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1550 = flow.variable.load.indirect %428 : !util.ptr<tensor<128x128xf32>> -> tensor<128x128xf32>
-    %1551 = flow.variable.load.indirect %429 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1552 = flow.variable.load.indirect %430 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1553 = flow.variable.load.indirect %431 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1554 = flow.variable.load.indirect %432 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1555 = flow.variable.load.indirect %433 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1556 = flow.variable.load.indirect %434 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1557 = flow.variable.load.indirect %435 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1558 = flow.variable.load.indirect %436 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1559 = flow.variable.load.indirect %437 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1560 = flow.variable.load.indirect %438 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1561 = flow.variable.load.indirect %439 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1562 = flow.variable.load.indirect %440 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
-    %1563 = flow.variable.load.indirect %441 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1564 = flow.variable.load.indirect %442 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1565 = flow.variable.load.indirect %443 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1566 = flow.variable.load.indirect %444 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1567 = flow.variable.load.indirect %445 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1568 = flow.variable.load.indirect %446 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
-    %1569 = flow.variable.load.indirect %447 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1570 = flow.variable.load.indirect %448 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1571 = flow.variable.load.indirect %449 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1572 = flow.variable.load.indirect %450 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1573 = flow.variable.load.indirect %451 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1574 = flow.variable.load.indirect %452 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
-    %1575 = flow.variable.load.indirect %453 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1576 = flow.variable.load.indirect %454 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1577 = flow.variable.load.indirect %455 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1578 = flow.variable.load.indirect %456 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1579 = flow.variable.load.indirect %457 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1580 = flow.variable.load.indirect %458 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
-    %1581 = flow.variable.load.indirect %459 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1582 = flow.variable.load.indirect %460 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1583 = flow.variable.load.indirect %461 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1584 = flow.variable.load.indirect %462 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1585 = flow.variable.load.indirect %463 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1586 = flow.variable.load.indirect %464 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
-    %1587 = flow.variable.load.indirect %465 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1588 = flow.variable.load.indirect %466 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1589 = flow.variable.load.indirect %467 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1590 = flow.variable.load.indirect %468 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1591 = flow.variable.load.indirect %469 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1592 = flow.variable.load.indirect %470 : !util.ptr<tensor<128x128xf32>> -> tensor<128x128xf32>
-    %1593 = flow.variable.load.indirect %471 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1594 = flow.variable.load.indirect %472 : !util.ptr<tensor<128x128xf32>> -> tensor<128x128xf32>
-    %1595 = flow.variable.load.indirect %473 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1596 = flow.variable.load.indirect %474 : !util.ptr<tensor<128x128xf32>> -> tensor<128x128xf32>
-    %1597 = flow.variable.load.indirect %475 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1598 = flow.variable.load.indirect %476 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1599 = flow.variable.load.indirect %477 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
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-    %1601 = flow.variable.load.indirect %479 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
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-    %1603 = flow.variable.load.indirect %481 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1604 = flow.variable.load.indirect %482 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1605 = flow.variable.load.indirect %483 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1606 = flow.variable.load.indirect %484 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1607 = flow.variable.load.indirect %485 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1608 = flow.variable.load.indirect %486 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
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-    %1610 = flow.variable.load.indirect %488 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1611 = flow.variable.load.indirect %489 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1612 = flow.variable.load.indirect %490 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1613 = flow.variable.load.indirect %491 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1614 = flow.variable.load.indirect %492 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
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-    %1616 = flow.variable.load.indirect %494 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1617 = flow.variable.load.indirect %495 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1618 = flow.variable.load.indirect %496 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1619 = flow.variable.load.indirect %497 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1620 = flow.variable.load.indirect %498 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
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-    %1622 = flow.variable.load.indirect %500 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1623 = flow.variable.load.indirect %501 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1624 = flow.variable.load.indirect %502 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
-    %1625 = flow.variable.load.indirect %503 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %1626 = flow.variable.load.indirect %504 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
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-    %1628 = flow.variable.load.indirect %506 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
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-    %1631 = flow.variable.load.indirect %509 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
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-    %1636 = flow.variable.load.indirect %514 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1637 = flow.variable.load.indirect %515 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
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-    %1640 = flow.variable.load.indirect %518 : !util.ptr<tensor<128x128xf32>> -> tensor<128x128xf32>
-    %1641 = flow.variable.load.indirect %519 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1642 = flow.variable.load.indirect %520 : !util.ptr<tensor<128x128xf32>> -> tensor<128x128xf32>
-    %1643 = flow.variable.load.indirect %521 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1644 = flow.variable.load.indirect %522 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
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-    %1646 = flow.variable.load.indirect %524 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
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-    %1650 = flow.variable.load.indirect %528 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1651 = flow.variable.load.indirect %529 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
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-    %1662 = flow.variable.load.indirect %540 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
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-    %1668 = flow.variable.load.indirect %546 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
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-    %1674 = flow.variable.load.indirect %552 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
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-    %1761 = flow.variable.load.indirect %639 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %1762 = flow.variable.load.indirect %640 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
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-    %1764 = flow.variable.load.indirect %642 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
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-    %1775 = flow.variable.load.indirect %653 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
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+    %2124 = util.global.load.indirect %1002 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
+    %2125 = util.global.load.indirect %1003 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %2126 = util.global.load.indirect %1004 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
+    %2127 = util.global.load.indirect %1005 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2128 = util.global.load.indirect %1006 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2129 = util.global.load.indirect %1007 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2130 = util.global.load.indirect %1008 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
+    %2131 = util.global.load.indirect %1009 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %2132 = util.global.load.indirect %1010 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
+    %2133 = util.global.load.indirect %1011 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2134 = util.global.load.indirect %1012 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2135 = util.global.load.indirect %1013 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %2136 = util.global.load.indirect %1014 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %2137 = util.global.load.indirect %1015 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %2138 = util.global.load.indirect %1016 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
+    %2139 = util.global.load.indirect %1017 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2140 = util.global.load.indirect %1018 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
+    %2141 = util.global.load.indirect %1019 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2142 = util.global.load.indirect %1020 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2143 = util.global.load.indirect %1021 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2144 = util.global.load.indirect %1022 : !util.ptr<tensor<128x128xf32>> -> tensor<128x128xf32>
+    %2145 = util.global.load.indirect %1023 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2146 = util.global.load.indirect %1024 : !util.ptr<tensor<128x128xf32>> -> tensor<128x128xf32>
+    %2147 = util.global.load.indirect %1025 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2148 = util.global.load.indirect %1026 : !util.ptr<tensor<128x128xf32>> -> tensor<128x128xf32>
+    %2149 = util.global.load.indirect %1027 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2150 = util.global.load.indirect %1028 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
+    %2151 = util.global.load.indirect %1029 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2152 = util.global.load.indirect %1030 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2153 = util.global.load.indirect %1031 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2154 = util.global.load.indirect %1032 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
+    %2155 = util.global.load.indirect %1033 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2156 = util.global.load.indirect %1034 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2157 = util.global.load.indirect %1035 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2158 = util.global.load.indirect %1036 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
+    %2159 = util.global.load.indirect %1037 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %2160 = util.global.load.indirect %1038 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
+    %2161 = util.global.load.indirect %1039 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2162 = util.global.load.indirect %1040 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2163 = util.global.load.indirect %1041 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2164 = util.global.load.indirect %1042 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
+    %2165 = util.global.load.indirect %1043 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %2166 = util.global.load.indirect %1044 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
+    %2167 = util.global.load.indirect %1045 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2168 = util.global.load.indirect %1046 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2169 = util.global.load.indirect %1047 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2170 = util.global.load.indirect %1048 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
+    %2171 = util.global.load.indirect %1049 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %2172 = util.global.load.indirect %1050 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
+    %2173 = util.global.load.indirect %1051 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2174 = util.global.load.indirect %1052 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2175 = util.global.load.indirect %1053 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2176 = util.global.load.indirect %1054 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
+    %2177 = util.global.load.indirect %1055 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %2178 = util.global.load.indirect %1056 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
+    %2179 = util.global.load.indirect %1057 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2180 = util.global.load.indirect %1058 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2181 = util.global.load.indirect %1059 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %2182 = util.global.load.indirect %1060 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %2183 = util.global.load.indirect %1061 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %2184 = util.global.load.indirect %1062 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
+    %2185 = util.global.load.indirect %1063 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2186 = util.global.load.indirect %1064 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
+    %2187 = util.global.load.indirect %1065 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2188 = util.global.load.indirect %1066 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2189 = util.global.load.indirect %1067 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2190 = util.global.load.indirect %1068 : !util.ptr<tensor<128x128xf32>> -> tensor<128x128xf32>
+    %2191 = util.global.load.indirect %1069 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2192 = util.global.load.indirect %1070 : !util.ptr<tensor<128x128xf32>> -> tensor<128x128xf32>
+    %2193 = util.global.load.indirect %1071 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2194 = util.global.load.indirect %1072 : !util.ptr<tensor<128x128xf32>> -> tensor<128x128xf32>
+    %2195 = util.global.load.indirect %1073 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2196 = util.global.load.indirect %1074 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
+    %2197 = util.global.load.indirect %1075 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2198 = util.global.load.indirect %1076 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2199 = util.global.load.indirect %1077 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2200 = util.global.load.indirect %1078 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
+    %2201 = util.global.load.indirect %1079 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2202 = util.global.load.indirect %1080 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2203 = util.global.load.indirect %1081 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2204 = util.global.load.indirect %1082 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
+    %2205 = util.global.load.indirect %1083 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %2206 = util.global.load.indirect %1084 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
+    %2207 = util.global.load.indirect %1085 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2208 = util.global.load.indirect %1086 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2209 = util.global.load.indirect %1087 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2210 = util.global.load.indirect %1088 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
+    %2211 = util.global.load.indirect %1089 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %2212 = util.global.load.indirect %1090 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
+    %2213 = util.global.load.indirect %1091 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2214 = util.global.load.indirect %1092 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2215 = util.global.load.indirect %1093 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2216 = util.global.load.indirect %1094 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
+    %2217 = util.global.load.indirect %1095 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %2218 = util.global.load.indirect %1096 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
+    %2219 = util.global.load.indirect %1097 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2220 = util.global.load.indirect %1098 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2221 = util.global.load.indirect %1099 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2222 = util.global.load.indirect %1100 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
+    %2223 = util.global.load.indirect %1101 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %2224 = util.global.load.indirect %1102 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
+    %2225 = util.global.load.indirect %1103 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2226 = util.global.load.indirect %1104 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2227 = util.global.load.indirect %1105 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %2228 = util.global.load.indirect %1106 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %2229 = util.global.load.indirect %1107 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %2230 = util.global.load.indirect %1108 : !util.ptr<tensor<128x512xf32>> -> tensor<128x512xf32>
+    %2231 = util.global.load.indirect %1109 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %2232 = util.global.load.indirect %1110 : !util.ptr<tensor<512x128xf32>> -> tensor<512x128xf32>
+    %2233 = util.global.load.indirect %1111 : !util.ptr<tensor<2xf32>> -> tensor<2xf32>
+    %2234 = util.global.load.indirect %1112 : !util.ptr<tensor<2x512xf32>> -> tensor<2x512xf32>
     %2235 = "mhlo.reshape"(%arg1) : (tensor<1x384xi32>) -> tensor<1x384x1xi32>
     %2236 = "mhlo.torch_index_select"(%1128, %2235) {batch_dims = 0 : i64, dim = 0 : i64} : (tensor<30522x128xf32>, tensor<1x384x1xi32>) -> tensor<1x384x1x128xf32>
     %2237 = "mhlo.reshape"(%2236) : (tensor<1x384x1x128xf32>) -> tensor<1x384x128xf32>
diff --git a/iree/test/e2e/models/mnist_fake_weights.mlir b/iree/test/e2e/models/mnist_fake_weights.mlir
index cff4402..c2dd705 100644
--- a/iree/test/e2e/models/mnist_fake_weights.mlir
+++ b/iree/test/e2e/models/mnist_fake_weights.mlir
@@ -5,23 +5,23 @@
 // RUN: [[ $IREE_VULKAN_DISABLE == 1 ]] || (iree-run-mlir --iree-input-type=mhlo -iree-hal-target-backends=vulkan-spirv %s -function-input="1x28x28x1xf32" | IreeFileCheck %s)
 
 module {
-  flow.variable @"__iree_flow___sm_node17__model.layer-1.kernel" dense<1.000000e+00> : tensor<784x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node18__model.layer-1.bias" dense<5.000000e-01> : tensor<128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node24__model.layer-2.kernel" dense<0.333333343> : tensor<128x10xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node25__model.layer-2.bias" dense<2.500000e-01> : tensor<10xf32> attributes {noinline, sym_visibility = "private"}
+  util.global private @"__iree_flow___sm_node17__model.layer-1.kernel" {noinline} = dense<1.000000e+00> : tensor<784x128xf32>
+  util.global private @"__iree_flow___sm_node18__model.layer-1.bias" {noinline} = dense<5.000000e-01> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node24__model.layer-2.kernel" {noinline} = dense<0.333333343> : tensor<128x10xf32>
+  util.global private @"__iree_flow___sm_node25__model.layer-2.bias" {noinline} = dense<2.500000e-01> : tensor<10xf32>
   // CHECK-LABEL: EXEC @predict
   func @predict(%arg0: tensor<1x28x28x1xf32>) -> tensor<1x10xf32> attributes {iree.module.export, iree.reflection = {abi = "sip", abiv = 1 : i32, sip = "I8!S5!k0_0R3!_0"}} {
-    %0 = flow.variable.address @"__iree_flow___sm_node17__model.layer-1.kernel" : !util.ptr<tensor<784x128xf32>>
-    %1 = flow.variable.address @"__iree_flow___sm_node18__model.layer-1.bias" : !util.ptr<tensor<128xf32>>
-    %2 = flow.variable.address @"__iree_flow___sm_node24__model.layer-2.kernel" : !util.ptr<tensor<128x10xf32>>
-    %3 = flow.variable.address @"__iree_flow___sm_node25__model.layer-2.bias" : !util.ptr<tensor<10xf32>>
+    %0 = util.global.address @"__iree_flow___sm_node17__model.layer-1.kernel" : !util.ptr<tensor<784x128xf32>>
+    %1 = util.global.address @"__iree_flow___sm_node18__model.layer-1.bias" : !util.ptr<tensor<128xf32>>
+    %2 = util.global.address @"__iree_flow___sm_node24__model.layer-2.kernel" : !util.ptr<tensor<128x10xf32>>
+    %3 = util.global.address @"__iree_flow___sm_node25__model.layer-2.bias" : !util.ptr<tensor<10xf32>>
     %4 = mhlo.constant dense<0.000000e+00> : tensor<1x128xf32>
     %5 = mhlo.constant dense<0xFF800000> : tensor<f32>
     %6 = mhlo.constant dense<0.000000e+00> : tensor<f32>
-    %7 = flow.variable.load.indirect %3 : !util.ptr<tensor<10xf32>> -> tensor<10xf32>
-    %8 = flow.variable.load.indirect %2 : !util.ptr<tensor<128x10xf32>> -> tensor<128x10xf32>
-    %9 = flow.variable.load.indirect %1 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %10 = flow.variable.load.indirect %0 : !util.ptr<tensor<784x128xf32>> -> tensor<784x128xf32>
+    %7 = util.global.load.indirect %3 : !util.ptr<tensor<10xf32>> -> tensor<10xf32>
+    %8 = util.global.load.indirect %2 : !util.ptr<tensor<128x10xf32>> -> tensor<128x10xf32>
+    %9 = util.global.load.indirect %1 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
+    %10 = util.global.load.indirect %0 : !util.ptr<tensor<784x128xf32>> -> tensor<784x128xf32>
     %11 = "mhlo.reshape"(%arg0) : (tensor<1x28x28x1xf32>) -> tensor<1x784xf32>
     %12 = "mhlo.dot"(%11, %10) : (tensor<1x784xf32>, tensor<784x128xf32>) -> tensor<1x128xf32>
     %13 = "mhlo.broadcast_in_dim"(%9) {broadcast_dimensions = dense<1> : tensor<1xi64>} : (tensor<128xf32>) -> tensor<1x128xf32>
diff --git a/iree/test/e2e/models/mobilenetv3_fake_weights.mlir b/iree/test/e2e/models/mobilenetv3_fake_weights.mlir
index 19cb7f7..5bcdccc 100644
--- a/iree/test/e2e/models/mobilenetv3_fake_weights.mlir
+++ b/iree/test/e2e/models/mobilenetv3_fake_weights.mlir
@@ -1,426 +1,426 @@
 module  {
-  flow.variable @"__iree_flow___sm_node260__m.layer-2.kernel" dense<1.000000e+00> : tensor<3x3x3x16xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node266__m.layer-3.gamma" dense<5.000000e-01> : tensor<16xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node267__m.layer-3.beta" dense<0.333333343> : tensor<16xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node268__m.layer-3.moving_mean" dense<2.500000e-01> : tensor<16xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node269__m.layer-3.moving_variance" dense<2.000000e-01> : tensor<16xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node288__m.layer-9.depthwise_kernel" dense<0.166666672> : tensor<3x3x16x1xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node294__m.layer-10.gamma" dense<0.142857149> : tensor<16xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node295__m.layer-10.beta" dense<1.250000e-01> : tensor<16xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node296__m.layer-10.moving_mean" dense<0.111111112> : tensor<16xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node297__m.layer-10.moving_variance" dense<1.000000e-01> : tensor<16xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node314__m.layer-14.kernel" dense<0.0909090936> : tensor<1x1x16x8xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node315__m.layer-14.bias" dense<0.0833333358> : tensor<8xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node324__m.layer-16.kernel" dense<0.0769230798> : tensor<1x1x8x16xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node325__m.layer-16.bias" dense<0.0714285746> : tensor<16xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node340__m.layer-21.kernel" dense<0.0666666701> : tensor<1x1x16x16xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node346__m.layer-22.gamma" dense<6.250000e-02> : tensor<16xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node347__m.layer-22.beta" dense<0.0588235296> : tensor<16xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node348__m.layer-22.moving_mean" dense<0.055555556> : tensor<16xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node349__m.layer-22.moving_variance" dense<0.0526315793> : tensor<16xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node354__m.layer-23.kernel" dense<5.000000e-02> : tensor<1x1x16x72xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node360__m.layer-24.gamma" dense<0.0476190485> : tensor<72xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node361__m.layer-24.beta" dense<0.0454545468> : tensor<72xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node362__m.layer-24.moving_mean" dense<0.0434782617> : tensor<72xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node363__m.layer-24.moving_variance" dense<0.0416666679> : tensor<72xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node376__m.layer-27.depthwise_kernel" dense<4.000000e-02> : tensor<3x3x72x1xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node382__m.layer-28.gamma" dense<0.0384615399> : tensor<72xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node383__m.layer-28.beta" dense<0.0370370373> : tensor<72xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node384__m.layer-28.moving_mean" dense<0.0357142873> : tensor<72xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node385__m.layer-28.moving_variance" dense<0.0344827585> : tensor<72xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node394__m.layer-30.kernel" dense<0.0333333351> : tensor<1x1x72x24xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node400__m.layer-31.gamma" dense<0.0322580636> : tensor<24xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node401__m.layer-31.beta" dense<3.125000e-02> : tensor<24xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node402__m.layer-31.moving_mean" dense<0.0303030312> : tensor<24xf32> attributes {noinline, sym_visibility = "private"}
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-  flow.variable @"__iree_flow___sm_node1090__m.layer-191.moving_mean" dense<0.00581395347> : tensor<576xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1091__m.layer-191.moving_variance" dense<0.00578034669> : tensor<576xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1114__m.layer-198.kernel" dense<0.00574712642> : tensor<1x1x576x144xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1115__m.layer-198.bias" dense<0.00571428565> : tensor<144xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1124__m.layer-200.kernel" dense<0.00568181835> : tensor<1x1x144x576xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1125__m.layer-200.bias" dense<0.00564971752> : tensor<576xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1140__m.layer-205.kernel" dense<0.00561797759> : tensor<1x1x576x96xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1146__m.layer-206.gamma" dense<0.00558659201> : tensor<96xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1147__m.layer-206.beta" dense<0.00555555569> : tensor<96xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1148__m.layer-206.moving_mean" dense<0.00552486209> : tensor<96xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1149__m.layer-206.moving_variance" dense<0.00549450563> : tensor<96xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1158__m.layer-208.kernel" dense<0.00546448072> : tensor<1x1x96x576xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1164__m.layer-209.gamma" dense<0.00543478271> : tensor<576xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1165__m.layer-209.beta" dense<0.00540540554> : tensor<576xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1166__m.layer-209.moving_mean" dense<0.00537634408> : tensor<576xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1167__m.layer-209.moving_variance" dense<0.00534759369> : tensor<576xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1182__m.layer-214.depthwise_kernel" dense<0.00531914877> : tensor<5x5x576x1xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1188__m.layer-215.gamma" dense<0.00529100513> : tensor<576xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1189__m.layer-215.beta" dense<0.00526315812> : tensor<576xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1190__m.layer-215.moving_mean" dense<0.00523560215> : tensor<576xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1191__m.layer-215.moving_variance" dense<0.00520833349> : tensor<576xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1214__m.layer-222.kernel" dense<0.00518134702> : tensor<1x1x576x144xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1215__m.layer-222.bias" dense<0.00515463902> : tensor<144xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1224__m.layer-224.kernel" dense<0.00512820529> : tensor<1x1x144x576xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1225__m.layer-224.bias" dense<0.00510204071> : tensor<576xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1240__m.layer-229.kernel" dense<0.00507614203> : tensor<1x1x576x96xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1246__m.layer-230.gamma" dense<0.00505050505> : tensor<96xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1247__m.layer-230.beta" dense<0.00502512557> : tensor<96xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1248__m.layer-230.moving_mean" dense<5.000000e-03> : tensor<96xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1249__m.layer-230.moving_variance" dense<0.00497512426> : tensor<96xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1258__m.layer-232.kernel" dense<0.00495049497> : tensor<1x1x96x576xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1264__m.layer-233.gamma" dense<0.00492610829> : tensor<576xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1265__m.layer-233.beta" dense<0.00490196096> : tensor<576xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1266__m.layer-233.moving_mean" dense<0.00487804879> : tensor<576xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1267__m.layer-233.moving_variance" dense<0.00485436898> : tensor<576xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1290__m.layer-240.kernel" dense<0.00483091781> : tensor<1x1x576x1024xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1291__m.layer-240.bias" dense<0.00480769249> : tensor<1024xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1310__m.layer-246.kernel" dense<0.00478468882> : tensor<1x1x1024x1000xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1311__m.layer-246.bias" dense<0.00476190494> : tensor<1000xf32> attributes {noinline, sym_visibility = "private"}
+  util.global private @"__iree_flow___sm_node260__m.layer-2.kernel" {noinline} = dense<1.000000e+00> : tensor<3x3x3x16xf32>
+  util.global private @"__iree_flow___sm_node266__m.layer-3.gamma" {noinline} = dense<5.000000e-01> : tensor<16xf32>
+  util.global private @"__iree_flow___sm_node267__m.layer-3.beta" {noinline} = dense<0.333333343> : tensor<16xf32>
+  util.global private @"__iree_flow___sm_node268__m.layer-3.moving_mean" {noinline} = dense<2.500000e-01> : tensor<16xf32>
+  util.global private @"__iree_flow___sm_node269__m.layer-3.moving_variance" {noinline} = dense<2.000000e-01> : tensor<16xf32>
+  util.global private @"__iree_flow___sm_node288__m.layer-9.depthwise_kernel" {noinline} = dense<0.166666672> : tensor<3x3x16x1xf32>
+  util.global private @"__iree_flow___sm_node294__m.layer-10.gamma" {noinline} = dense<0.142857149> : tensor<16xf32>
+  util.global private @"__iree_flow___sm_node295__m.layer-10.beta" {noinline} = dense<1.250000e-01> : tensor<16xf32>
+  util.global private @"__iree_flow___sm_node296__m.layer-10.moving_mean" {noinline} = dense<0.111111112> : tensor<16xf32>
+  util.global private @"__iree_flow___sm_node297__m.layer-10.moving_variance" {noinline} = dense<1.000000e-01> : tensor<16xf32>
+  util.global private @"__iree_flow___sm_node314__m.layer-14.kernel" {noinline} = dense<0.0909090936> : tensor<1x1x16x8xf32>
+  util.global private @"__iree_flow___sm_node315__m.layer-14.bias" {noinline} = dense<0.0833333358> : tensor<8xf32>
+  util.global private @"__iree_flow___sm_node324__m.layer-16.kernel" {noinline} = dense<0.0769230798> : tensor<1x1x8x16xf32>
+  util.global private @"__iree_flow___sm_node325__m.layer-16.bias" {noinline} = dense<0.0714285746> : tensor<16xf32>
+  util.global private @"__iree_flow___sm_node340__m.layer-21.kernel" {noinline} = dense<0.0666666701> : tensor<1x1x16x16xf32>
+  util.global private @"__iree_flow___sm_node346__m.layer-22.gamma" {noinline} = dense<6.250000e-02> : tensor<16xf32>
+  util.global private @"__iree_flow___sm_node347__m.layer-22.beta" {noinline} = dense<0.0588235296> : tensor<16xf32>
+  util.global private @"__iree_flow___sm_node348__m.layer-22.moving_mean" {noinline} = dense<0.055555556> : tensor<16xf32>
+  util.global private @"__iree_flow___sm_node349__m.layer-22.moving_variance" {noinline} = dense<0.0526315793> : tensor<16xf32>
+  util.global private @"__iree_flow___sm_node354__m.layer-23.kernel" {noinline} = dense<5.000000e-02> : tensor<1x1x16x72xf32>
+  util.global private @"__iree_flow___sm_node360__m.layer-24.gamma" {noinline} = dense<0.0476190485> : tensor<72xf32>
+  util.global private @"__iree_flow___sm_node361__m.layer-24.beta" {noinline} = dense<0.0454545468> : tensor<72xf32>
+  util.global private @"__iree_flow___sm_node362__m.layer-24.moving_mean" {noinline} = dense<0.0434782617> : tensor<72xf32>
+  util.global private @"__iree_flow___sm_node363__m.layer-24.moving_variance" {noinline} = dense<0.0416666679> : tensor<72xf32>
+  util.global private @"__iree_flow___sm_node376__m.layer-27.depthwise_kernel" {noinline} = dense<4.000000e-02> : tensor<3x3x72x1xf32>
+  util.global private @"__iree_flow___sm_node382__m.layer-28.gamma" {noinline} = dense<0.0384615399> : tensor<72xf32>
+  util.global private @"__iree_flow___sm_node383__m.layer-28.beta" {noinline} = dense<0.0370370373> : tensor<72xf32>
+  util.global private @"__iree_flow___sm_node384__m.layer-28.moving_mean" {noinline} = dense<0.0357142873> : tensor<72xf32>
+  util.global private @"__iree_flow___sm_node385__m.layer-28.moving_variance" {noinline} = dense<0.0344827585> : tensor<72xf32>
+  util.global private @"__iree_flow___sm_node394__m.layer-30.kernel" {noinline} = dense<0.0333333351> : tensor<1x1x72x24xf32>
+  util.global private @"__iree_flow___sm_node400__m.layer-31.gamma" {noinline} = dense<0.0322580636> : tensor<24xf32>
+  util.global private @"__iree_flow___sm_node401__m.layer-31.beta" {noinline} = dense<3.125000e-02> : tensor<24xf32>
+  util.global private @"__iree_flow___sm_node402__m.layer-31.moving_mean" {noinline} = dense<0.0303030312> : tensor<24xf32>
+  util.global private @"__iree_flow___sm_node403__m.layer-31.moving_variance" {noinline} = dense<0.0294117648> : tensor<24xf32>
+  util.global private @"__iree_flow___sm_node408__m.layer-32.kernel" {noinline} = dense<0.0285714287> : tensor<1x1x24x88xf32>
+  util.global private @"__iree_flow___sm_node414__m.layer-33.gamma" {noinline} = dense<0.027777778> : tensor<88xf32>
+  util.global private @"__iree_flow___sm_node415__m.layer-33.beta" {noinline} = dense<0.0270270277> : tensor<88xf32>
+  util.global private @"__iree_flow___sm_node416__m.layer-33.moving_mean" {noinline} = dense<0.0263157897> : tensor<88xf32>
+  util.global private @"__iree_flow___sm_node417__m.layer-33.moving_variance" {noinline} = dense<0.025641026> : tensor<88xf32>
+  util.global private @"__iree_flow___sm_node426__m.layer-35.depthwise_kernel" {noinline} = dense<2.500000e-02> : tensor<3x3x88x1xf32>
+  util.global private @"__iree_flow___sm_node432__m.layer-36.gamma" {noinline} = dense<0.024390243> : tensor<88xf32>
+  util.global private @"__iree_flow___sm_node433__m.layer-36.beta" {noinline} = dense<0.0238095243> : tensor<88xf32>
+  util.global private @"__iree_flow___sm_node434__m.layer-36.moving_mean" {noinline} = dense<0.0232558139> : tensor<88xf32>
+  util.global private @"__iree_flow___sm_node435__m.layer-36.moving_variance" {noinline} = dense<0.0227272734> : tensor<88xf32>
+  util.global private @"__iree_flow___sm_node444__m.layer-38.kernel" {noinline} = dense<0.0222222228> : tensor<1x1x88x24xf32>
+  util.global private @"__iree_flow___sm_node450__m.layer-39.gamma" {noinline} = dense<0.0217391308> : tensor<24xf32>
+  util.global private @"__iree_flow___sm_node451__m.layer-39.beta" {noinline} = dense<0.0212765951> : tensor<24xf32>
+  util.global private @"__iree_flow___sm_node452__m.layer-39.moving_mean" {noinline} = dense<0.020833334> : tensor<24xf32>
+  util.global private @"__iree_flow___sm_node453__m.layer-39.moving_variance" {noinline} = dense<0.0204081628> : tensor<24xf32>
+  util.global private @"__iree_flow___sm_node462__m.layer-41.kernel" {noinline} = dense<2.000000e-02> : tensor<1x1x24x96xf32>
+  util.global private @"__iree_flow___sm_node468__m.layer-42.gamma" {noinline} = dense<0.0196078438> : tensor<96xf32>
+  util.global private @"__iree_flow___sm_node469__m.layer-42.beta" {noinline} = dense<0.0192307699> : tensor<96xf32>
+  util.global private @"__iree_flow___sm_node470__m.layer-42.moving_mean" {noinline} = dense<0.0188679248> : tensor<96xf32>
+  util.global private @"__iree_flow___sm_node471__m.layer-42.moving_variance" {noinline} = dense<0.0185185187> : tensor<96xf32>
+  util.global private @"__iree_flow___sm_node490__m.layer-48.depthwise_kernel" {noinline} = dense<0.0181818176> : tensor<5x5x96x1xf32>
+  util.global private @"__iree_flow___sm_node496__m.layer-49.gamma" {noinline} = dense<0.0178571437> : tensor<96xf32>
+  util.global private @"__iree_flow___sm_node497__m.layer-49.beta" {noinline} = dense<0.0175438598> : tensor<96xf32>
+  util.global private @"__iree_flow___sm_node498__m.layer-49.moving_mean" {noinline} = dense<0.0172413792> : tensor<96xf32>
+  util.global private @"__iree_flow___sm_node499__m.layer-49.moving_variance" {noinline} = dense<0.0169491526> : tensor<96xf32>
+  util.global private @"__iree_flow___sm_node522__m.layer-56.kernel" {noinline} = dense<0.0166666675> : tensor<1x1x96x24xf32>
+  util.global private @"__iree_flow___sm_node523__m.layer-56.bias" {noinline} = dense<0.0163934417> : tensor<24xf32>
+  util.global private @"__iree_flow___sm_node532__m.layer-58.kernel" {noinline} = dense<0.0161290318> : tensor<1x1x24x96xf32>
+  util.global private @"__iree_flow___sm_node533__m.layer-58.bias" {noinline} = dense<0.0158730168> : tensor<96xf32>
+  util.global private @"__iree_flow___sm_node548__m.layer-63.kernel" {noinline} = dense<1.562500e-02> : tensor<1x1x96x40xf32>
+  util.global private @"__iree_flow___sm_node554__m.layer-64.gamma" {noinline} = dense<0.0153846154> : tensor<40xf32>
+  util.global private @"__iree_flow___sm_node555__m.layer-64.beta" {noinline} = dense<0.0151515156> : tensor<40xf32>
+  util.global private @"__iree_flow___sm_node556__m.layer-64.moving_mean" {noinline} = dense<0.0149253728> : tensor<40xf32>
+  util.global private @"__iree_flow___sm_node557__m.layer-64.moving_variance" {noinline} = dense<0.0147058824> : tensor<40xf32>
+  util.global private @"__iree_flow___sm_node562__m.layer-65.kernel" {noinline} = dense<0.0144927539> : tensor<1x1x40x240xf32>
+  util.global private @"__iree_flow___sm_node568__m.layer-66.gamma" {noinline} = dense<0.0142857144> : tensor<240xf32>
+  util.global private @"__iree_flow___sm_node569__m.layer-66.beta" {noinline} = dense<0.0140845068> : tensor<240xf32>
+  util.global private @"__iree_flow___sm_node570__m.layer-66.moving_mean" {noinline} = dense<0.013888889> : tensor<240xf32>
+  util.global private @"__iree_flow___sm_node571__m.layer-66.moving_variance" {noinline} = dense<0.01369863> : tensor<240xf32>
+  util.global private @"__iree_flow___sm_node586__m.layer-71.depthwise_kernel" {noinline} = dense<0.0135135138> : tensor<5x5x240x1xf32>
+  util.global private @"__iree_flow___sm_node592__m.layer-72.gamma" {noinline} = dense<0.0133333337> : tensor<240xf32>
+  util.global private @"__iree_flow___sm_node593__m.layer-72.beta" {noinline} = dense<0.0131578948> : tensor<240xf32>
+  util.global private @"__iree_flow___sm_node594__m.layer-72.moving_mean" {noinline} = dense<0.012987013> : tensor<240xf32>
+  util.global private @"__iree_flow___sm_node595__m.layer-72.moving_variance" {noinline} = dense<0.012820513> : tensor<240xf32>
+  util.global private @"__iree_flow___sm_node618__m.layer-79.kernel" {noinline} = dense<0.0126582282> : tensor<1x1x240x64xf32>
+  util.global private @"__iree_flow___sm_node619__m.layer-79.bias" {noinline} = dense<1.250000e-02> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node628__m.layer-81.kernel" {noinline} = dense<0.0123456791> : tensor<1x1x64x240xf32>
+  util.global private @"__iree_flow___sm_node629__m.layer-81.bias" {noinline} = dense<0.0121951215> : tensor<240xf32>
+  util.global private @"__iree_flow___sm_node644__m.layer-86.kernel" {noinline} = dense<0.0120481923> : tensor<1x1x240x40xf32>
+  util.global private @"__iree_flow___sm_node650__m.layer-87.gamma" {noinline} = dense<0.0119047621> : tensor<40xf32>
+  util.global private @"__iree_flow___sm_node651__m.layer-87.beta" {noinline} = dense<0.0117647061> : tensor<40xf32>
+  util.global private @"__iree_flow___sm_node652__m.layer-87.moving_mean" {noinline} = dense<0.0116279069> : tensor<40xf32>
+  util.global private @"__iree_flow___sm_node653__m.layer-87.moving_variance" {noinline} = dense<0.0114942528> : tensor<40xf32>
+  util.global private @"__iree_flow___sm_node662__m.layer-89.kernel" {noinline} = dense<0.0113636367> : tensor<1x1x40x240xf32>
+  util.global private @"__iree_flow___sm_node668__m.layer-90.gamma" {noinline} = dense<0.0112359552> : tensor<240xf32>
+  util.global private @"__iree_flow___sm_node669__m.layer-90.beta" {noinline} = dense<0.0111111114> : tensor<240xf32>
+  util.global private @"__iree_flow___sm_node670__m.layer-90.moving_mean" {noinline} = dense<0.0109890113> : tensor<240xf32>
+  util.global private @"__iree_flow___sm_node671__m.layer-90.moving_variance" {noinline} = dense<0.0108695654> : tensor<240xf32>
+  util.global private @"__iree_flow___sm_node686__m.layer-95.depthwise_kernel" {noinline} = dense<0.0107526882> : tensor<5x5x240x1xf32>
+  util.global private @"__iree_flow___sm_node692__m.layer-96.gamma" {noinline} = dense<0.0106382975> : tensor<240xf32>
+  util.global private @"__iree_flow___sm_node693__m.layer-96.beta" {noinline} = dense<0.0105263162> : tensor<240xf32>
+  util.global private @"__iree_flow___sm_node694__m.layer-96.moving_mean" {noinline} = dense<0.010416667> : tensor<240xf32>
+  util.global private @"__iree_flow___sm_node695__m.layer-96.moving_variance" {noinline} = dense<0.010309278> : tensor<240xf32>
+  util.global private @"__iree_flow___sm_node718__m.layer-103.kernel" {noinline} = dense<0.0102040814> : tensor<1x1x240x64xf32>
+  util.global private @"__iree_flow___sm_node719__m.layer-103.bias" {noinline} = dense<0.0101010101> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node728__m.layer-105.kernel" {noinline} = dense<0.00999999977> : tensor<1x1x64x240xf32>
+  util.global private @"__iree_flow___sm_node729__m.layer-105.bias" {noinline} = dense<9.900990e-03> : tensor<240xf32>
+  util.global private @"__iree_flow___sm_node744__m.layer-110.kernel" {noinline} = dense<0.00980392192> : tensor<1x1x240x40xf32>
+  util.global private @"__iree_flow___sm_node750__m.layer-111.gamma" {noinline} = dense<0.00970873795> : tensor<40xf32>
+  util.global private @"__iree_flow___sm_node751__m.layer-111.beta" {noinline} = dense<0.00961538497> : tensor<40xf32>
+  util.global private @"__iree_flow___sm_node752__m.layer-111.moving_mean" {noinline} = dense<9.523810e-03> : tensor<40xf32>
+  util.global private @"__iree_flow___sm_node753__m.layer-111.moving_variance" {noinline} = dense<0.0094339624> : tensor<40xf32>
+  util.global private @"__iree_flow___sm_node762__m.layer-113.kernel" {noinline} = dense<0.00934579409> : tensor<1x1x40x120xf32>
+  util.global private @"__iree_flow___sm_node768__m.layer-114.gamma" {noinline} = dense<0.00925925932> : tensor<120xf32>
+  util.global private @"__iree_flow___sm_node769__m.layer-114.beta" {noinline} = dense<0.00917431153> : tensor<120xf32>
+  util.global private @"__iree_flow___sm_node770__m.layer-114.moving_mean" {noinline} = dense<0.0090909088> : tensor<120xf32>
+  util.global private @"__iree_flow___sm_node771__m.layer-114.moving_variance" {noinline} = dense<0.00900900922> : tensor<120xf32>
+  util.global private @"__iree_flow___sm_node786__m.layer-119.depthwise_kernel" {noinline} = dense<0.00892857183> : tensor<5x5x120x1xf32>
+  util.global private @"__iree_flow___sm_node792__m.layer-120.gamma" {noinline} = dense<0.00884955748> : tensor<120xf32>
+  util.global private @"__iree_flow___sm_node793__m.layer-120.beta" {noinline} = dense<0.00877192988> : tensor<120xf32>
+  util.global private @"__iree_flow___sm_node794__m.layer-120.moving_mean" {noinline} = dense<0.00869565178> : tensor<120xf32>
+  util.global private @"__iree_flow___sm_node795__m.layer-120.moving_variance" {noinline} = dense<8.620690e-03> : tensor<120xf32>
+  util.global private @"__iree_flow___sm_node818__m.layer-127.kernel" {noinline} = dense<0.00854700897> : tensor<1x1x120x32xf32>
+  util.global private @"__iree_flow___sm_node819__m.layer-127.bias" {noinline} = dense<0.00847457629> : tensor<32xf32>
+  util.global private @"__iree_flow___sm_node828__m.layer-129.kernel" {noinline} = dense<0.00840336177> : tensor<1x1x32x120xf32>
+  util.global private @"__iree_flow___sm_node829__m.layer-129.bias" {noinline} = dense<0.00833333377> : tensor<120xf32>
+  util.global private @"__iree_flow___sm_node844__m.layer-134.kernel" {noinline} = dense<0.00826446246> : tensor<1x1x120x48xf32>
+  util.global private @"__iree_flow___sm_node850__m.layer-135.gamma" {noinline} = dense<0.00819672085> : tensor<48xf32>
+  util.global private @"__iree_flow___sm_node851__m.layer-135.beta" {noinline} = dense<0.008130081> : tensor<48xf32>
+  util.global private @"__iree_flow___sm_node852__m.layer-135.moving_mean" {noinline} = dense<0.00806451589> : tensor<48xf32>
+  util.global private @"__iree_flow___sm_node853__m.layer-135.moving_variance" {noinline} = dense<8.000000e-03> : tensor<48xf32>
+  util.global private @"__iree_flow___sm_node858__m.layer-136.kernel" {noinline} = dense<0.00793650839> : tensor<1x1x48x144xf32>
+  util.global private @"__iree_flow___sm_node864__m.layer-137.gamma" {noinline} = dense<0.00787401571> : tensor<144xf32>
+  util.global private @"__iree_flow___sm_node865__m.layer-137.beta" {noinline} = dense<7.812500e-03> : tensor<144xf32>
+  util.global private @"__iree_flow___sm_node866__m.layer-137.moving_mean" {noinline} = dense<0.00775193795> : tensor<144xf32>
+  util.global private @"__iree_flow___sm_node867__m.layer-137.moving_variance" {noinline} = dense<0.0076923077> : tensor<144xf32>
+  util.global private @"__iree_flow___sm_node882__m.layer-142.depthwise_kernel" {noinline} = dense<0.00763358781> : tensor<5x5x144x1xf32>
+  util.global private @"__iree_flow___sm_node888__m.layer-143.gamma" {noinline} = dense<0.0075757578> : tensor<144xf32>
+  util.global private @"__iree_flow___sm_node889__m.layer-143.beta" {noinline} = dense<0.00751879718> : tensor<144xf32>
+  util.global private @"__iree_flow___sm_node890__m.layer-143.moving_mean" {noinline} = dense<0.00746268639> : tensor<144xf32>
+  util.global private @"__iree_flow___sm_node891__m.layer-143.moving_variance" {noinline} = dense<0.00740740728> : tensor<144xf32>
+  util.global private @"__iree_flow___sm_node914__m.layer-150.kernel" {noinline} = dense<0.0073529412> : tensor<1x1x144x40xf32>
+  util.global private @"__iree_flow___sm_node915__m.layer-150.bias" {noinline} = dense<7.299270e-03> : tensor<40xf32>
+  util.global private @"__iree_flow___sm_node924__m.layer-152.kernel" {noinline} = dense<0.00724637694> : tensor<1x1x40x144xf32>
+  util.global private @"__iree_flow___sm_node925__m.layer-152.bias" {noinline} = dense<0.00719424477> : tensor<144xf32>
+  util.global private @"__iree_flow___sm_node940__m.layer-157.kernel" {noinline} = dense<0.00714285718> : tensor<1x1x144x48xf32>
+  util.global private @"__iree_flow___sm_node946__m.layer-158.gamma" {noinline} = dense<0.00709219835> : tensor<48xf32>
+  util.global private @"__iree_flow___sm_node947__m.layer-158.beta" {noinline} = dense<0.00704225338> : tensor<48xf32>
+  util.global private @"__iree_flow___sm_node948__m.layer-158.moving_mean" {noinline} = dense<0.00699300691> : tensor<48xf32>
+  util.global private @"__iree_flow___sm_node949__m.layer-158.moving_variance" {noinline} = dense<0.0069444445> : tensor<48xf32>
+  util.global private @"__iree_flow___sm_node958__m.layer-160.kernel" {noinline} = dense<0.0068965517> : tensor<1x1x48x288xf32>
+  util.global private @"__iree_flow___sm_node964__m.layer-161.gamma" {noinline} = dense<0.00684931502> : tensor<288xf32>
+  util.global private @"__iree_flow___sm_node965__m.layer-161.beta" {noinline} = dense<0.00680272094> : tensor<288xf32>
+  util.global private @"__iree_flow___sm_node966__m.layer-161.moving_mean" {noinline} = dense<0.00675675692> : tensor<288xf32>
+  util.global private @"__iree_flow___sm_node967__m.layer-161.moving_variance" {noinline} = dense<0.00671140943> : tensor<288xf32>
+  util.global private @"__iree_flow___sm_node986__m.layer-167.depthwise_kernel" {noinline} = dense<0.00666666683> : tensor<5x5x288x1xf32>
+  util.global private @"__iree_flow___sm_node992__m.layer-168.gamma" {noinline} = dense<0.00662251655> : tensor<288xf32>
+  util.global private @"__iree_flow___sm_node993__m.layer-168.beta" {noinline} = dense<0.00657894742> : tensor<288xf32>
+  util.global private @"__iree_flow___sm_node994__m.layer-168.moving_mean" {noinline} = dense<0.00653594779> : tensor<288xf32>
+  util.global private @"__iree_flow___sm_node995__m.layer-168.moving_variance" {noinline} = dense<0.00649350649> : tensor<288xf32>
+  util.global private @"__iree_flow___sm_node1018__m.layer-175.kernel" {noinline} = dense<0.0064516128> : tensor<1x1x288x72xf32>
+  util.global private @"__iree_flow___sm_node1019__m.layer-175.bias" {noinline} = dense<0.00641025649> : tensor<72xf32>
+  util.global private @"__iree_flow___sm_node1028__m.layer-177.kernel" {noinline} = dense<0.00636942684> : tensor<1x1x72x288xf32>
+  util.global private @"__iree_flow___sm_node1029__m.layer-177.bias" {noinline} = dense<0.00632911408> : tensor<288xf32>
+  util.global private @"__iree_flow___sm_node1044__m.layer-182.kernel" {noinline} = dense<0.00628930796> : tensor<1x1x288x96xf32>
+  util.global private @"__iree_flow___sm_node1050__m.layer-183.gamma" {noinline} = dense<6.250000e-03> : tensor<96xf32>
+  util.global private @"__iree_flow___sm_node1051__m.layer-183.beta" {noinline} = dense<0.00621118024> : tensor<96xf32>
+  util.global private @"__iree_flow___sm_node1052__m.layer-183.moving_mean" {noinline} = dense<0.00617283955> : tensor<96xf32>
+  util.global private @"__iree_flow___sm_node1053__m.layer-183.moving_variance" {noinline} = dense<0.00613496918> : tensor<96xf32>
+  util.global private @"__iree_flow___sm_node1058__m.layer-184.kernel" {noinline} = dense<0.00609756075> : tensor<1x1x96x576xf32>
+  util.global private @"__iree_flow___sm_node1064__m.layer-185.gamma" {noinline} = dense<0.00606060587> : tensor<576xf32>
+  util.global private @"__iree_flow___sm_node1065__m.layer-185.beta" {noinline} = dense<0.00602409616> : tensor<576xf32>
+  util.global private @"__iree_flow___sm_node1066__m.layer-185.moving_mean" {noinline} = dense<0.00598802418> : tensor<576xf32>
+  util.global private @"__iree_flow___sm_node1067__m.layer-185.moving_variance" {noinline} = dense<0.00595238106> : tensor<576xf32>
+  util.global private @"__iree_flow___sm_node1082__m.layer-190.depthwise_kernel" {noinline} = dense<5.917160e-03> : tensor<5x5x576x1xf32>
+  util.global private @"__iree_flow___sm_node1088__m.layer-191.gamma" {noinline} = dense<0.00588235306> : tensor<576xf32>
+  util.global private @"__iree_flow___sm_node1089__m.layer-191.beta" {noinline} = dense<0.00584795326> : tensor<576xf32>
+  util.global private @"__iree_flow___sm_node1090__m.layer-191.moving_mean" {noinline} = dense<0.00581395347> : tensor<576xf32>
+  util.global private @"__iree_flow___sm_node1091__m.layer-191.moving_variance" {noinline} = dense<0.00578034669> : tensor<576xf32>
+  util.global private @"__iree_flow___sm_node1114__m.layer-198.kernel" {noinline} = dense<0.00574712642> : tensor<1x1x576x144xf32>
+  util.global private @"__iree_flow___sm_node1115__m.layer-198.bias" {noinline} = dense<0.00571428565> : tensor<144xf32>
+  util.global private @"__iree_flow___sm_node1124__m.layer-200.kernel" {noinline} = dense<0.00568181835> : tensor<1x1x144x576xf32>
+  util.global private @"__iree_flow___sm_node1125__m.layer-200.bias" {noinline} = dense<0.00564971752> : tensor<576xf32>
+  util.global private @"__iree_flow___sm_node1140__m.layer-205.kernel" {noinline} = dense<0.00561797759> : tensor<1x1x576x96xf32>
+  util.global private @"__iree_flow___sm_node1146__m.layer-206.gamma" {noinline} = dense<0.00558659201> : tensor<96xf32>
+  util.global private @"__iree_flow___sm_node1147__m.layer-206.beta" {noinline} = dense<0.00555555569> : tensor<96xf32>
+  util.global private @"__iree_flow___sm_node1148__m.layer-206.moving_mean" {noinline} = dense<0.00552486209> : tensor<96xf32>
+  util.global private @"__iree_flow___sm_node1149__m.layer-206.moving_variance" {noinline} = dense<0.00549450563> : tensor<96xf32>
+  util.global private @"__iree_flow___sm_node1158__m.layer-208.kernel" {noinline} = dense<0.00546448072> : tensor<1x1x96x576xf32>
+  util.global private @"__iree_flow___sm_node1164__m.layer-209.gamma" {noinline} = dense<0.00543478271> : tensor<576xf32>
+  util.global private @"__iree_flow___sm_node1165__m.layer-209.beta" {noinline} = dense<0.00540540554> : tensor<576xf32>
+  util.global private @"__iree_flow___sm_node1166__m.layer-209.moving_mean" {noinline} = dense<0.00537634408> : tensor<576xf32>
+  util.global private @"__iree_flow___sm_node1167__m.layer-209.moving_variance" {noinline} = dense<0.00534759369> : tensor<576xf32>
+  util.global private @"__iree_flow___sm_node1182__m.layer-214.depthwise_kernel" {noinline} = dense<0.00531914877> : tensor<5x5x576x1xf32>
+  util.global private @"__iree_flow___sm_node1188__m.layer-215.gamma" {noinline} = dense<0.00529100513> : tensor<576xf32>
+  util.global private @"__iree_flow___sm_node1189__m.layer-215.beta" {noinline} = dense<0.00526315812> : tensor<576xf32>
+  util.global private @"__iree_flow___sm_node1190__m.layer-215.moving_mean" {noinline} = dense<0.00523560215> : tensor<576xf32>
+  util.global private @"__iree_flow___sm_node1191__m.layer-215.moving_variance" {noinline} = dense<0.00520833349> : tensor<576xf32>
+  util.global private @"__iree_flow___sm_node1214__m.layer-222.kernel" {noinline} = dense<0.00518134702> : tensor<1x1x576x144xf32>
+  util.global private @"__iree_flow___sm_node1215__m.layer-222.bias" {noinline} = dense<0.00515463902> : tensor<144xf32>
+  util.global private @"__iree_flow___sm_node1224__m.layer-224.kernel" {noinline} = dense<0.00512820529> : tensor<1x1x144x576xf32>
+  util.global private @"__iree_flow___sm_node1225__m.layer-224.bias" {noinline} = dense<0.00510204071> : tensor<576xf32>
+  util.global private @"__iree_flow___sm_node1240__m.layer-229.kernel" {noinline} = dense<0.00507614203> : tensor<1x1x576x96xf32>
+  util.global private @"__iree_flow___sm_node1246__m.layer-230.gamma" {noinline} = dense<0.00505050505> : tensor<96xf32>
+  util.global private @"__iree_flow___sm_node1247__m.layer-230.beta" {noinline} = dense<0.00502512557> : tensor<96xf32>
+  util.global private @"__iree_flow___sm_node1248__m.layer-230.moving_mean" {noinline} = dense<5.000000e-03> : tensor<96xf32>
+  util.global private @"__iree_flow___sm_node1249__m.layer-230.moving_variance" {noinline} = dense<0.00497512426> : tensor<96xf32>
+  util.global private @"__iree_flow___sm_node1258__m.layer-232.kernel" {noinline} = dense<0.00495049497> : tensor<1x1x96x576xf32>
+  util.global private @"__iree_flow___sm_node1264__m.layer-233.gamma" {noinline} = dense<0.00492610829> : tensor<576xf32>
+  util.global private @"__iree_flow___sm_node1265__m.layer-233.beta" {noinline} = dense<0.00490196096> : tensor<576xf32>
+  util.global private @"__iree_flow___sm_node1266__m.layer-233.moving_mean" {noinline} = dense<0.00487804879> : tensor<576xf32>
+  util.global private @"__iree_flow___sm_node1267__m.layer-233.moving_variance" {noinline} = dense<0.00485436898> : tensor<576xf32>
+  util.global private @"__iree_flow___sm_node1290__m.layer-240.kernel" {noinline} = dense<0.00483091781> : tensor<1x1x576x1024xf32>
+  util.global private @"__iree_flow___sm_node1291__m.layer-240.bias" {noinline} = dense<0.00480769249> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node1310__m.layer-246.kernel" {noinline} = dense<0.00478468882> : tensor<1x1x1024x1000xf32>
+  util.global private @"__iree_flow___sm_node1311__m.layer-246.bias" {noinline} = dense<0.00476190494> : tensor<1000xf32>
   func @call() {
     %arg0 = util.unfoldable_constant dense<1.5> : tensor<1x224x224x3xf32>
-    %0 = flow.variable.address @"__iree_flow___sm_node260__m.layer-2.kernel" : !util.ptr<tensor<3x3x3x16xf32>>
-    %1 = flow.variable.address @"__iree_flow___sm_node266__m.layer-3.gamma" : !util.ptr<tensor<16xf32>>
-    %2 = flow.variable.address @"__iree_flow___sm_node267__m.layer-3.beta" : !util.ptr<tensor<16xf32>>
-    %3 = flow.variable.address @"__iree_flow___sm_node268__m.layer-3.moving_mean" : !util.ptr<tensor<16xf32>>
-    %4 = flow.variable.address @"__iree_flow___sm_node269__m.layer-3.moving_variance" : !util.ptr<tensor<16xf32>>
-    %5 = flow.variable.address @"__iree_flow___sm_node288__m.layer-9.depthwise_kernel" : !util.ptr<tensor<3x3x16x1xf32>>
-    %6 = flow.variable.address @"__iree_flow___sm_node294__m.layer-10.gamma" : !util.ptr<tensor<16xf32>>
-    %7 = flow.variable.address @"__iree_flow___sm_node295__m.layer-10.beta" : !util.ptr<tensor<16xf32>>
-    %8 = flow.variable.address @"__iree_flow___sm_node296__m.layer-10.moving_mean" : !util.ptr<tensor<16xf32>>
-    %9 = flow.variable.address @"__iree_flow___sm_node297__m.layer-10.moving_variance" : !util.ptr<tensor<16xf32>>
-    %10 = flow.variable.address @"__iree_flow___sm_node314__m.layer-14.kernel" : !util.ptr<tensor<1x1x16x8xf32>>
-    %11 = flow.variable.address @"__iree_flow___sm_node315__m.layer-14.bias" : !util.ptr<tensor<8xf32>>
-    %12 = flow.variable.address @"__iree_flow___sm_node324__m.layer-16.kernel" : !util.ptr<tensor<1x1x8x16xf32>>
-    %13 = flow.variable.address @"__iree_flow___sm_node325__m.layer-16.bias" : !util.ptr<tensor<16xf32>>
-    %14 = flow.variable.address @"__iree_flow___sm_node340__m.layer-21.kernel" : !util.ptr<tensor<1x1x16x16xf32>>
-    %15 = flow.variable.address @"__iree_flow___sm_node346__m.layer-22.gamma" : !util.ptr<tensor<16xf32>>
-    %16 = flow.variable.address @"__iree_flow___sm_node347__m.layer-22.beta" : !util.ptr<tensor<16xf32>>
-    %17 = flow.variable.address @"__iree_flow___sm_node348__m.layer-22.moving_mean" : !util.ptr<tensor<16xf32>>
-    %18 = flow.variable.address @"__iree_flow___sm_node349__m.layer-22.moving_variance" : !util.ptr<tensor<16xf32>>
-    %19 = flow.variable.address @"__iree_flow___sm_node354__m.layer-23.kernel" : !util.ptr<tensor<1x1x16x72xf32>>
-    %20 = flow.variable.address @"__iree_flow___sm_node360__m.layer-24.gamma" : !util.ptr<tensor<72xf32>>
-    %21 = flow.variable.address @"__iree_flow___sm_node361__m.layer-24.beta" : !util.ptr<tensor<72xf32>>
-    %22 = flow.variable.address @"__iree_flow___sm_node362__m.layer-24.moving_mean" : !util.ptr<tensor<72xf32>>
-    %23 = flow.variable.address @"__iree_flow___sm_node363__m.layer-24.moving_variance" : !util.ptr<tensor<72xf32>>
-    %24 = flow.variable.address @"__iree_flow___sm_node376__m.layer-27.depthwise_kernel" : !util.ptr<tensor<3x3x72x1xf32>>
-    %25 = flow.variable.address @"__iree_flow___sm_node382__m.layer-28.gamma" : !util.ptr<tensor<72xf32>>
-    %26 = flow.variable.address @"__iree_flow___sm_node383__m.layer-28.beta" : !util.ptr<tensor<72xf32>>
-    %27 = flow.variable.address @"__iree_flow___sm_node384__m.layer-28.moving_mean" : !util.ptr<tensor<72xf32>>
-    %28 = flow.variable.address @"__iree_flow___sm_node385__m.layer-28.moving_variance" : !util.ptr<tensor<72xf32>>
-    %29 = flow.variable.address @"__iree_flow___sm_node394__m.layer-30.kernel" : !util.ptr<tensor<1x1x72x24xf32>>
-    %30 = flow.variable.address @"__iree_flow___sm_node400__m.layer-31.gamma" : !util.ptr<tensor<24xf32>>
-    %31 = flow.variable.address @"__iree_flow___sm_node401__m.layer-31.beta" : !util.ptr<tensor<24xf32>>
-    %32 = flow.variable.address @"__iree_flow___sm_node402__m.layer-31.moving_mean" : !util.ptr<tensor<24xf32>>
-    %33 = flow.variable.address @"__iree_flow___sm_node403__m.layer-31.moving_variance" : !util.ptr<tensor<24xf32>>
-    %34 = flow.variable.address @"__iree_flow___sm_node408__m.layer-32.kernel" : !util.ptr<tensor<1x1x24x88xf32>>
-    %35 = flow.variable.address @"__iree_flow___sm_node414__m.layer-33.gamma" : !util.ptr<tensor<88xf32>>
-    %36 = flow.variable.address @"__iree_flow___sm_node415__m.layer-33.beta" : !util.ptr<tensor<88xf32>>
-    %37 = flow.variable.address @"__iree_flow___sm_node416__m.layer-33.moving_mean" : !util.ptr<tensor<88xf32>>
-    %38 = flow.variable.address @"__iree_flow___sm_node417__m.layer-33.moving_variance" : !util.ptr<tensor<88xf32>>
-    %39 = flow.variable.address @"__iree_flow___sm_node426__m.layer-35.depthwise_kernel" : !util.ptr<tensor<3x3x88x1xf32>>
-    %40 = flow.variable.address @"__iree_flow___sm_node432__m.layer-36.gamma" : !util.ptr<tensor<88xf32>>
-    %41 = flow.variable.address @"__iree_flow___sm_node433__m.layer-36.beta" : !util.ptr<tensor<88xf32>>
-    %42 = flow.variable.address @"__iree_flow___sm_node434__m.layer-36.moving_mean" : !util.ptr<tensor<88xf32>>
-    %43 = flow.variable.address @"__iree_flow___sm_node435__m.layer-36.moving_variance" : !util.ptr<tensor<88xf32>>
-    %44 = flow.variable.address @"__iree_flow___sm_node444__m.layer-38.kernel" : !util.ptr<tensor<1x1x88x24xf32>>
-    %45 = flow.variable.address @"__iree_flow___sm_node450__m.layer-39.gamma" : !util.ptr<tensor<24xf32>>
-    %46 = flow.variable.address @"__iree_flow___sm_node451__m.layer-39.beta" : !util.ptr<tensor<24xf32>>
-    %47 = flow.variable.address @"__iree_flow___sm_node452__m.layer-39.moving_mean" : !util.ptr<tensor<24xf32>>
-    %48 = flow.variable.address @"__iree_flow___sm_node453__m.layer-39.moving_variance" : !util.ptr<tensor<24xf32>>
-    %49 = flow.variable.address @"__iree_flow___sm_node462__m.layer-41.kernel" : !util.ptr<tensor<1x1x24x96xf32>>
-    %50 = flow.variable.address @"__iree_flow___sm_node468__m.layer-42.gamma" : !util.ptr<tensor<96xf32>>
-    %51 = flow.variable.address @"__iree_flow___sm_node469__m.layer-42.beta" : !util.ptr<tensor<96xf32>>
-    %52 = flow.variable.address @"__iree_flow___sm_node470__m.layer-42.moving_mean" : !util.ptr<tensor<96xf32>>
-    %53 = flow.variable.address @"__iree_flow___sm_node471__m.layer-42.moving_variance" : !util.ptr<tensor<96xf32>>
-    %54 = flow.variable.address @"__iree_flow___sm_node490__m.layer-48.depthwise_kernel" : !util.ptr<tensor<5x5x96x1xf32>>
-    %55 = flow.variable.address @"__iree_flow___sm_node496__m.layer-49.gamma" : !util.ptr<tensor<96xf32>>
-    %56 = flow.variable.address @"__iree_flow___sm_node497__m.layer-49.beta" : !util.ptr<tensor<96xf32>>
-    %57 = flow.variable.address @"__iree_flow___sm_node498__m.layer-49.moving_mean" : !util.ptr<tensor<96xf32>>
-    %58 = flow.variable.address @"__iree_flow___sm_node499__m.layer-49.moving_variance" : !util.ptr<tensor<96xf32>>
-    %59 = flow.variable.address @"__iree_flow___sm_node522__m.layer-56.kernel" : !util.ptr<tensor<1x1x96x24xf32>>
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-    %124 = flow.variable.address @"__iree_flow___sm_node853__m.layer-135.moving_variance" : !util.ptr<tensor<48xf32>>
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-    %128 = flow.variable.address @"__iree_flow___sm_node866__m.layer-137.moving_mean" : !util.ptr<tensor<144xf32>>
-    %129 = flow.variable.address @"__iree_flow___sm_node867__m.layer-137.moving_variance" : !util.ptr<tensor<144xf32>>
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-    %149 = flow.variable.address @"__iree_flow___sm_node986__m.layer-167.depthwise_kernel" : !util.ptr<tensor<5x5x288x1xf32>>
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-    %153 = flow.variable.address @"__iree_flow___sm_node995__m.layer-168.moving_variance" : !util.ptr<tensor<288xf32>>
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-    %161 = flow.variable.address @"__iree_flow___sm_node1052__m.layer-183.moving_mean" : !util.ptr<tensor<96xf32>>
-    %162 = flow.variable.address @"__iree_flow___sm_node1053__m.layer-183.moving_variance" : !util.ptr<tensor<96xf32>>
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-    %167 = flow.variable.address @"__iree_flow___sm_node1067__m.layer-185.moving_variance" : !util.ptr<tensor<576xf32>>
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-    %170 = flow.variable.address @"__iree_flow___sm_node1089__m.layer-191.beta" : !util.ptr<tensor<576xf32>>
-    %171 = flow.variable.address @"__iree_flow___sm_node1090__m.layer-191.moving_mean" : !util.ptr<tensor<576xf32>>
-    %172 = flow.variable.address @"__iree_flow___sm_node1091__m.layer-191.moving_variance" : !util.ptr<tensor<576xf32>>
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-    %179 = flow.variable.address @"__iree_flow___sm_node1147__m.layer-206.beta" : !util.ptr<tensor<96xf32>>
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-    %181 = flow.variable.address @"__iree_flow___sm_node1149__m.layer-206.moving_variance" : !util.ptr<tensor<96xf32>>
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-    %183 = flow.variable.address @"__iree_flow___sm_node1164__m.layer-209.gamma" : !util.ptr<tensor<576xf32>>
-    %184 = flow.variable.address @"__iree_flow___sm_node1165__m.layer-209.beta" : !util.ptr<tensor<576xf32>>
-    %185 = flow.variable.address @"__iree_flow___sm_node1166__m.layer-209.moving_mean" : !util.ptr<tensor<576xf32>>
-    %186 = flow.variable.address @"__iree_flow___sm_node1167__m.layer-209.moving_variance" : !util.ptr<tensor<576xf32>>
-    %187 = flow.variable.address @"__iree_flow___sm_node1182__m.layer-214.depthwise_kernel" : !util.ptr<tensor<5x5x576x1xf32>>
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-    %189 = flow.variable.address @"__iree_flow___sm_node1189__m.layer-215.beta" : !util.ptr<tensor<576xf32>>
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-    %191 = flow.variable.address @"__iree_flow___sm_node1191__m.layer-215.moving_variance" : !util.ptr<tensor<576xf32>>
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-    %193 = flow.variable.address @"__iree_flow___sm_node1215__m.layer-222.bias" : !util.ptr<tensor<144xf32>>
-    %194 = flow.variable.address @"__iree_flow___sm_node1224__m.layer-224.kernel" : !util.ptr<tensor<1x1x144x576xf32>>
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-    %196 = flow.variable.address @"__iree_flow___sm_node1240__m.layer-229.kernel" : !util.ptr<tensor<1x1x576x96xf32>>
-    %197 = flow.variable.address @"__iree_flow___sm_node1246__m.layer-230.gamma" : !util.ptr<tensor<96xf32>>
-    %198 = flow.variable.address @"__iree_flow___sm_node1247__m.layer-230.beta" : !util.ptr<tensor<96xf32>>
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-    %200 = flow.variable.address @"__iree_flow___sm_node1249__m.layer-230.moving_variance" : !util.ptr<tensor<96xf32>>
-    %201 = flow.variable.address @"__iree_flow___sm_node1258__m.layer-232.kernel" : !util.ptr<tensor<1x1x96x576xf32>>
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-    %203 = flow.variable.address @"__iree_flow___sm_node1265__m.layer-233.beta" : !util.ptr<tensor<576xf32>>
-    %204 = flow.variable.address @"__iree_flow___sm_node1266__m.layer-233.moving_mean" : !util.ptr<tensor<576xf32>>
-    %205 = flow.variable.address @"__iree_flow___sm_node1267__m.layer-233.moving_variance" : !util.ptr<tensor<576xf32>>
-    %206 = flow.variable.address @"__iree_flow___sm_node1290__m.layer-240.kernel" : !util.ptr<tensor<1x1x576x1024xf32>>
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-    %209 = flow.variable.address @"__iree_flow___sm_node1311__m.layer-246.bias" : !util.ptr<tensor<1000xf32>>
+    %0 = util.global.address @"__iree_flow___sm_node260__m.layer-2.kernel" : !util.ptr<tensor<3x3x3x16xf32>>
+    %1 = util.global.address @"__iree_flow___sm_node266__m.layer-3.gamma" : !util.ptr<tensor<16xf32>>
+    %2 = util.global.address @"__iree_flow___sm_node267__m.layer-3.beta" : !util.ptr<tensor<16xf32>>
+    %3 = util.global.address @"__iree_flow___sm_node268__m.layer-3.moving_mean" : !util.ptr<tensor<16xf32>>
+    %4 = util.global.address @"__iree_flow___sm_node269__m.layer-3.moving_variance" : !util.ptr<tensor<16xf32>>
+    %5 = util.global.address @"__iree_flow___sm_node288__m.layer-9.depthwise_kernel" : !util.ptr<tensor<3x3x16x1xf32>>
+    %6 = util.global.address @"__iree_flow___sm_node294__m.layer-10.gamma" : !util.ptr<tensor<16xf32>>
+    %7 = util.global.address @"__iree_flow___sm_node295__m.layer-10.beta" : !util.ptr<tensor<16xf32>>
+    %8 = util.global.address @"__iree_flow___sm_node296__m.layer-10.moving_mean" : !util.ptr<tensor<16xf32>>
+    %9 = util.global.address @"__iree_flow___sm_node297__m.layer-10.moving_variance" : !util.ptr<tensor<16xf32>>
+    %10 = util.global.address @"__iree_flow___sm_node314__m.layer-14.kernel" : !util.ptr<tensor<1x1x16x8xf32>>
+    %11 = util.global.address @"__iree_flow___sm_node315__m.layer-14.bias" : !util.ptr<tensor<8xf32>>
+    %12 = util.global.address @"__iree_flow___sm_node324__m.layer-16.kernel" : !util.ptr<tensor<1x1x8x16xf32>>
+    %13 = util.global.address @"__iree_flow___sm_node325__m.layer-16.bias" : !util.ptr<tensor<16xf32>>
+    %14 = util.global.address @"__iree_flow___sm_node340__m.layer-21.kernel" : !util.ptr<tensor<1x1x16x16xf32>>
+    %15 = util.global.address @"__iree_flow___sm_node346__m.layer-22.gamma" : !util.ptr<tensor<16xf32>>
+    %16 = util.global.address @"__iree_flow___sm_node347__m.layer-22.beta" : !util.ptr<tensor<16xf32>>
+    %17 = util.global.address @"__iree_flow___sm_node348__m.layer-22.moving_mean" : !util.ptr<tensor<16xf32>>
+    %18 = util.global.address @"__iree_flow___sm_node349__m.layer-22.moving_variance" : !util.ptr<tensor<16xf32>>
+    %19 = util.global.address @"__iree_flow___sm_node354__m.layer-23.kernel" : !util.ptr<tensor<1x1x16x72xf32>>
+    %20 = util.global.address @"__iree_flow___sm_node360__m.layer-24.gamma" : !util.ptr<tensor<72xf32>>
+    %21 = util.global.address @"__iree_flow___sm_node361__m.layer-24.beta" : !util.ptr<tensor<72xf32>>
+    %22 = util.global.address @"__iree_flow___sm_node362__m.layer-24.moving_mean" : !util.ptr<tensor<72xf32>>
+    %23 = util.global.address @"__iree_flow___sm_node363__m.layer-24.moving_variance" : !util.ptr<tensor<72xf32>>
+    %24 = util.global.address @"__iree_flow___sm_node376__m.layer-27.depthwise_kernel" : !util.ptr<tensor<3x3x72x1xf32>>
+    %25 = util.global.address @"__iree_flow___sm_node382__m.layer-28.gamma" : !util.ptr<tensor<72xf32>>
+    %26 = util.global.address @"__iree_flow___sm_node383__m.layer-28.beta" : !util.ptr<tensor<72xf32>>
+    %27 = util.global.address @"__iree_flow___sm_node384__m.layer-28.moving_mean" : !util.ptr<tensor<72xf32>>
+    %28 = util.global.address @"__iree_flow___sm_node385__m.layer-28.moving_variance" : !util.ptr<tensor<72xf32>>
+    %29 = util.global.address @"__iree_flow___sm_node394__m.layer-30.kernel" : !util.ptr<tensor<1x1x72x24xf32>>
+    %30 = util.global.address @"__iree_flow___sm_node400__m.layer-31.gamma" : !util.ptr<tensor<24xf32>>
+    %31 = util.global.address @"__iree_flow___sm_node401__m.layer-31.beta" : !util.ptr<tensor<24xf32>>
+    %32 = util.global.address @"__iree_flow___sm_node402__m.layer-31.moving_mean" : !util.ptr<tensor<24xf32>>
+    %33 = util.global.address @"__iree_flow___sm_node403__m.layer-31.moving_variance" : !util.ptr<tensor<24xf32>>
+    %34 = util.global.address @"__iree_flow___sm_node408__m.layer-32.kernel" : !util.ptr<tensor<1x1x24x88xf32>>
+    %35 = util.global.address @"__iree_flow___sm_node414__m.layer-33.gamma" : !util.ptr<tensor<88xf32>>
+    %36 = util.global.address @"__iree_flow___sm_node415__m.layer-33.beta" : !util.ptr<tensor<88xf32>>
+    %37 = util.global.address @"__iree_flow___sm_node416__m.layer-33.moving_mean" : !util.ptr<tensor<88xf32>>
+    %38 = util.global.address @"__iree_flow___sm_node417__m.layer-33.moving_variance" : !util.ptr<tensor<88xf32>>
+    %39 = util.global.address @"__iree_flow___sm_node426__m.layer-35.depthwise_kernel" : !util.ptr<tensor<3x3x88x1xf32>>
+    %40 = util.global.address @"__iree_flow___sm_node432__m.layer-36.gamma" : !util.ptr<tensor<88xf32>>
+    %41 = util.global.address @"__iree_flow___sm_node433__m.layer-36.beta" : !util.ptr<tensor<88xf32>>
+    %42 = util.global.address @"__iree_flow___sm_node434__m.layer-36.moving_mean" : !util.ptr<tensor<88xf32>>
+    %43 = util.global.address @"__iree_flow___sm_node435__m.layer-36.moving_variance" : !util.ptr<tensor<88xf32>>
+    %44 = util.global.address @"__iree_flow___sm_node444__m.layer-38.kernel" : !util.ptr<tensor<1x1x88x24xf32>>
+    %45 = util.global.address @"__iree_flow___sm_node450__m.layer-39.gamma" : !util.ptr<tensor<24xf32>>
+    %46 = util.global.address @"__iree_flow___sm_node451__m.layer-39.beta" : !util.ptr<tensor<24xf32>>
+    %47 = util.global.address @"__iree_flow___sm_node452__m.layer-39.moving_mean" : !util.ptr<tensor<24xf32>>
+    %48 = util.global.address @"__iree_flow___sm_node453__m.layer-39.moving_variance" : !util.ptr<tensor<24xf32>>
+    %49 = util.global.address @"__iree_flow___sm_node462__m.layer-41.kernel" : !util.ptr<tensor<1x1x24x96xf32>>
+    %50 = util.global.address @"__iree_flow___sm_node468__m.layer-42.gamma" : !util.ptr<tensor<96xf32>>
+    %51 = util.global.address @"__iree_flow___sm_node469__m.layer-42.beta" : !util.ptr<tensor<96xf32>>
+    %52 = util.global.address @"__iree_flow___sm_node470__m.layer-42.moving_mean" : !util.ptr<tensor<96xf32>>
+    %53 = util.global.address @"__iree_flow___sm_node471__m.layer-42.moving_variance" : !util.ptr<tensor<96xf32>>
+    %54 = util.global.address @"__iree_flow___sm_node490__m.layer-48.depthwise_kernel" : !util.ptr<tensor<5x5x96x1xf32>>
+    %55 = util.global.address @"__iree_flow___sm_node496__m.layer-49.gamma" : !util.ptr<tensor<96xf32>>
+    %56 = util.global.address @"__iree_flow___sm_node497__m.layer-49.beta" : !util.ptr<tensor<96xf32>>
+    %57 = util.global.address @"__iree_flow___sm_node498__m.layer-49.moving_mean" : !util.ptr<tensor<96xf32>>
+    %58 = util.global.address @"__iree_flow___sm_node499__m.layer-49.moving_variance" : !util.ptr<tensor<96xf32>>
+    %59 = util.global.address @"__iree_flow___sm_node522__m.layer-56.kernel" : !util.ptr<tensor<1x1x96x24xf32>>
+    %60 = util.global.address @"__iree_flow___sm_node523__m.layer-56.bias" : !util.ptr<tensor<24xf32>>
+    %61 = util.global.address @"__iree_flow___sm_node532__m.layer-58.kernel" : !util.ptr<tensor<1x1x24x96xf32>>
+    %62 = util.global.address @"__iree_flow___sm_node533__m.layer-58.bias" : !util.ptr<tensor<96xf32>>
+    %63 = util.global.address @"__iree_flow___sm_node548__m.layer-63.kernel" : !util.ptr<tensor<1x1x96x40xf32>>
+    %64 = util.global.address @"__iree_flow___sm_node554__m.layer-64.gamma" : !util.ptr<tensor<40xf32>>
+    %65 = util.global.address @"__iree_flow___sm_node555__m.layer-64.beta" : !util.ptr<tensor<40xf32>>
+    %66 = util.global.address @"__iree_flow___sm_node556__m.layer-64.moving_mean" : !util.ptr<tensor<40xf32>>
+    %67 = util.global.address @"__iree_flow___sm_node557__m.layer-64.moving_variance" : !util.ptr<tensor<40xf32>>
+    %68 = util.global.address @"__iree_flow___sm_node562__m.layer-65.kernel" : !util.ptr<tensor<1x1x40x240xf32>>
+    %69 = util.global.address @"__iree_flow___sm_node568__m.layer-66.gamma" : !util.ptr<tensor<240xf32>>
+    %70 = util.global.address @"__iree_flow___sm_node569__m.layer-66.beta" : !util.ptr<tensor<240xf32>>
+    %71 = util.global.address @"__iree_flow___sm_node570__m.layer-66.moving_mean" : !util.ptr<tensor<240xf32>>
+    %72 = util.global.address @"__iree_flow___sm_node571__m.layer-66.moving_variance" : !util.ptr<tensor<240xf32>>
+    %73 = util.global.address @"__iree_flow___sm_node586__m.layer-71.depthwise_kernel" : !util.ptr<tensor<5x5x240x1xf32>>
+    %74 = util.global.address @"__iree_flow___sm_node592__m.layer-72.gamma" : !util.ptr<tensor<240xf32>>
+    %75 = util.global.address @"__iree_flow___sm_node593__m.layer-72.beta" : !util.ptr<tensor<240xf32>>
+    %76 = util.global.address @"__iree_flow___sm_node594__m.layer-72.moving_mean" : !util.ptr<tensor<240xf32>>
+    %77 = util.global.address @"__iree_flow___sm_node595__m.layer-72.moving_variance" : !util.ptr<tensor<240xf32>>
+    %78 = util.global.address @"__iree_flow___sm_node618__m.layer-79.kernel" : !util.ptr<tensor<1x1x240x64xf32>>
+    %79 = util.global.address @"__iree_flow___sm_node619__m.layer-79.bias" : !util.ptr<tensor<64xf32>>
+    %80 = util.global.address @"__iree_flow___sm_node628__m.layer-81.kernel" : !util.ptr<tensor<1x1x64x240xf32>>
+    %81 = util.global.address @"__iree_flow___sm_node629__m.layer-81.bias" : !util.ptr<tensor<240xf32>>
+    %82 = util.global.address @"__iree_flow___sm_node644__m.layer-86.kernel" : !util.ptr<tensor<1x1x240x40xf32>>
+    %83 = util.global.address @"__iree_flow___sm_node650__m.layer-87.gamma" : !util.ptr<tensor<40xf32>>
+    %84 = util.global.address @"__iree_flow___sm_node651__m.layer-87.beta" : !util.ptr<tensor<40xf32>>
+    %85 = util.global.address @"__iree_flow___sm_node652__m.layer-87.moving_mean" : !util.ptr<tensor<40xf32>>
+    %86 = util.global.address @"__iree_flow___sm_node653__m.layer-87.moving_variance" : !util.ptr<tensor<40xf32>>
+    %87 = util.global.address @"__iree_flow___sm_node662__m.layer-89.kernel" : !util.ptr<tensor<1x1x40x240xf32>>
+    %88 = util.global.address @"__iree_flow___sm_node668__m.layer-90.gamma" : !util.ptr<tensor<240xf32>>
+    %89 = util.global.address @"__iree_flow___sm_node669__m.layer-90.beta" : !util.ptr<tensor<240xf32>>
+    %90 = util.global.address @"__iree_flow___sm_node670__m.layer-90.moving_mean" : !util.ptr<tensor<240xf32>>
+    %91 = util.global.address @"__iree_flow___sm_node671__m.layer-90.moving_variance" : !util.ptr<tensor<240xf32>>
+    %92 = util.global.address @"__iree_flow___sm_node686__m.layer-95.depthwise_kernel" : !util.ptr<tensor<5x5x240x1xf32>>
+    %93 = util.global.address @"__iree_flow___sm_node692__m.layer-96.gamma" : !util.ptr<tensor<240xf32>>
+    %94 = util.global.address @"__iree_flow___sm_node693__m.layer-96.beta" : !util.ptr<tensor<240xf32>>
+    %95 = util.global.address @"__iree_flow___sm_node694__m.layer-96.moving_mean" : !util.ptr<tensor<240xf32>>
+    %96 = util.global.address @"__iree_flow___sm_node695__m.layer-96.moving_variance" : !util.ptr<tensor<240xf32>>
+    %97 = util.global.address @"__iree_flow___sm_node718__m.layer-103.kernel" : !util.ptr<tensor<1x1x240x64xf32>>
+    %98 = util.global.address @"__iree_flow___sm_node719__m.layer-103.bias" : !util.ptr<tensor<64xf32>>
+    %99 = util.global.address @"__iree_flow___sm_node728__m.layer-105.kernel" : !util.ptr<tensor<1x1x64x240xf32>>
+    %100 = util.global.address @"__iree_flow___sm_node729__m.layer-105.bias" : !util.ptr<tensor<240xf32>>
+    %101 = util.global.address @"__iree_flow___sm_node744__m.layer-110.kernel" : !util.ptr<tensor<1x1x240x40xf32>>
+    %102 = util.global.address @"__iree_flow___sm_node750__m.layer-111.gamma" : !util.ptr<tensor<40xf32>>
+    %103 = util.global.address @"__iree_flow___sm_node751__m.layer-111.beta" : !util.ptr<tensor<40xf32>>
+    %104 = util.global.address @"__iree_flow___sm_node752__m.layer-111.moving_mean" : !util.ptr<tensor<40xf32>>
+    %105 = util.global.address @"__iree_flow___sm_node753__m.layer-111.moving_variance" : !util.ptr<tensor<40xf32>>
+    %106 = util.global.address @"__iree_flow___sm_node762__m.layer-113.kernel" : !util.ptr<tensor<1x1x40x120xf32>>
+    %107 = util.global.address @"__iree_flow___sm_node768__m.layer-114.gamma" : !util.ptr<tensor<120xf32>>
+    %108 = util.global.address @"__iree_flow___sm_node769__m.layer-114.beta" : !util.ptr<tensor<120xf32>>
+    %109 = util.global.address @"__iree_flow___sm_node770__m.layer-114.moving_mean" : !util.ptr<tensor<120xf32>>
+    %110 = util.global.address @"__iree_flow___sm_node771__m.layer-114.moving_variance" : !util.ptr<tensor<120xf32>>
+    %111 = util.global.address @"__iree_flow___sm_node786__m.layer-119.depthwise_kernel" : !util.ptr<tensor<5x5x120x1xf32>>
+    %112 = util.global.address @"__iree_flow___sm_node792__m.layer-120.gamma" : !util.ptr<tensor<120xf32>>
+    %113 = util.global.address @"__iree_flow___sm_node793__m.layer-120.beta" : !util.ptr<tensor<120xf32>>
+    %114 = util.global.address @"__iree_flow___sm_node794__m.layer-120.moving_mean" : !util.ptr<tensor<120xf32>>
+    %115 = util.global.address @"__iree_flow___sm_node795__m.layer-120.moving_variance" : !util.ptr<tensor<120xf32>>
+    %116 = util.global.address @"__iree_flow___sm_node818__m.layer-127.kernel" : !util.ptr<tensor<1x1x120x32xf32>>
+    %117 = util.global.address @"__iree_flow___sm_node819__m.layer-127.bias" : !util.ptr<tensor<32xf32>>
+    %118 = util.global.address @"__iree_flow___sm_node828__m.layer-129.kernel" : !util.ptr<tensor<1x1x32x120xf32>>
+    %119 = util.global.address @"__iree_flow___sm_node829__m.layer-129.bias" : !util.ptr<tensor<120xf32>>
+    %120 = util.global.address @"__iree_flow___sm_node844__m.layer-134.kernel" : !util.ptr<tensor<1x1x120x48xf32>>
+    %121 = util.global.address @"__iree_flow___sm_node850__m.layer-135.gamma" : !util.ptr<tensor<48xf32>>
+    %122 = util.global.address @"__iree_flow___sm_node851__m.layer-135.beta" : !util.ptr<tensor<48xf32>>
+    %123 = util.global.address @"__iree_flow___sm_node852__m.layer-135.moving_mean" : !util.ptr<tensor<48xf32>>
+    %124 = util.global.address @"__iree_flow___sm_node853__m.layer-135.moving_variance" : !util.ptr<tensor<48xf32>>
+    %125 = util.global.address @"__iree_flow___sm_node858__m.layer-136.kernel" : !util.ptr<tensor<1x1x48x144xf32>>
+    %126 = util.global.address @"__iree_flow___sm_node864__m.layer-137.gamma" : !util.ptr<tensor<144xf32>>
+    %127 = util.global.address @"__iree_flow___sm_node865__m.layer-137.beta" : !util.ptr<tensor<144xf32>>
+    %128 = util.global.address @"__iree_flow___sm_node866__m.layer-137.moving_mean" : !util.ptr<tensor<144xf32>>
+    %129 = util.global.address @"__iree_flow___sm_node867__m.layer-137.moving_variance" : !util.ptr<tensor<144xf32>>
+    %130 = util.global.address @"__iree_flow___sm_node882__m.layer-142.depthwise_kernel" : !util.ptr<tensor<5x5x144x1xf32>>
+    %131 = util.global.address @"__iree_flow___sm_node888__m.layer-143.gamma" : !util.ptr<tensor<144xf32>>
+    %132 = util.global.address @"__iree_flow___sm_node889__m.layer-143.beta" : !util.ptr<tensor<144xf32>>
+    %133 = util.global.address @"__iree_flow___sm_node890__m.layer-143.moving_mean" : !util.ptr<tensor<144xf32>>
+    %134 = util.global.address @"__iree_flow___sm_node891__m.layer-143.moving_variance" : !util.ptr<tensor<144xf32>>
+    %135 = util.global.address @"__iree_flow___sm_node914__m.layer-150.kernel" : !util.ptr<tensor<1x1x144x40xf32>>
+    %136 = util.global.address @"__iree_flow___sm_node915__m.layer-150.bias" : !util.ptr<tensor<40xf32>>
+    %137 = util.global.address @"__iree_flow___sm_node924__m.layer-152.kernel" : !util.ptr<tensor<1x1x40x144xf32>>
+    %138 = util.global.address @"__iree_flow___sm_node925__m.layer-152.bias" : !util.ptr<tensor<144xf32>>
+    %139 = util.global.address @"__iree_flow___sm_node940__m.layer-157.kernel" : !util.ptr<tensor<1x1x144x48xf32>>
+    %140 = util.global.address @"__iree_flow___sm_node946__m.layer-158.gamma" : !util.ptr<tensor<48xf32>>
+    %141 = util.global.address @"__iree_flow___sm_node947__m.layer-158.beta" : !util.ptr<tensor<48xf32>>
+    %142 = util.global.address @"__iree_flow___sm_node948__m.layer-158.moving_mean" : !util.ptr<tensor<48xf32>>
+    %143 = util.global.address @"__iree_flow___sm_node949__m.layer-158.moving_variance" : !util.ptr<tensor<48xf32>>
+    %144 = util.global.address @"__iree_flow___sm_node958__m.layer-160.kernel" : !util.ptr<tensor<1x1x48x288xf32>>
+    %145 = util.global.address @"__iree_flow___sm_node964__m.layer-161.gamma" : !util.ptr<tensor<288xf32>>
+    %146 = util.global.address @"__iree_flow___sm_node965__m.layer-161.beta" : !util.ptr<tensor<288xf32>>
+    %147 = util.global.address @"__iree_flow___sm_node966__m.layer-161.moving_mean" : !util.ptr<tensor<288xf32>>
+    %148 = util.global.address @"__iree_flow___sm_node967__m.layer-161.moving_variance" : !util.ptr<tensor<288xf32>>
+    %149 = util.global.address @"__iree_flow___sm_node986__m.layer-167.depthwise_kernel" : !util.ptr<tensor<5x5x288x1xf32>>
+    %150 = util.global.address @"__iree_flow___sm_node992__m.layer-168.gamma" : !util.ptr<tensor<288xf32>>
+    %151 = util.global.address @"__iree_flow___sm_node993__m.layer-168.beta" : !util.ptr<tensor<288xf32>>
+    %152 = util.global.address @"__iree_flow___sm_node994__m.layer-168.moving_mean" : !util.ptr<tensor<288xf32>>
+    %153 = util.global.address @"__iree_flow___sm_node995__m.layer-168.moving_variance" : !util.ptr<tensor<288xf32>>
+    %154 = util.global.address @"__iree_flow___sm_node1018__m.layer-175.kernel" : !util.ptr<tensor<1x1x288x72xf32>>
+    %155 = util.global.address @"__iree_flow___sm_node1019__m.layer-175.bias" : !util.ptr<tensor<72xf32>>
+    %156 = util.global.address @"__iree_flow___sm_node1028__m.layer-177.kernel" : !util.ptr<tensor<1x1x72x288xf32>>
+    %157 = util.global.address @"__iree_flow___sm_node1029__m.layer-177.bias" : !util.ptr<tensor<288xf32>>
+    %158 = util.global.address @"__iree_flow___sm_node1044__m.layer-182.kernel" : !util.ptr<tensor<1x1x288x96xf32>>
+    %159 = util.global.address @"__iree_flow___sm_node1050__m.layer-183.gamma" : !util.ptr<tensor<96xf32>>
+    %160 = util.global.address @"__iree_flow___sm_node1051__m.layer-183.beta" : !util.ptr<tensor<96xf32>>
+    %161 = util.global.address @"__iree_flow___sm_node1052__m.layer-183.moving_mean" : !util.ptr<tensor<96xf32>>
+    %162 = util.global.address @"__iree_flow___sm_node1053__m.layer-183.moving_variance" : !util.ptr<tensor<96xf32>>
+    %163 = util.global.address @"__iree_flow___sm_node1058__m.layer-184.kernel" : !util.ptr<tensor<1x1x96x576xf32>>
+    %164 = util.global.address @"__iree_flow___sm_node1064__m.layer-185.gamma" : !util.ptr<tensor<576xf32>>
+    %165 = util.global.address @"__iree_flow___sm_node1065__m.layer-185.beta" : !util.ptr<tensor<576xf32>>
+    %166 = util.global.address @"__iree_flow___sm_node1066__m.layer-185.moving_mean" : !util.ptr<tensor<576xf32>>
+    %167 = util.global.address @"__iree_flow___sm_node1067__m.layer-185.moving_variance" : !util.ptr<tensor<576xf32>>
+    %168 = util.global.address @"__iree_flow___sm_node1082__m.layer-190.depthwise_kernel" : !util.ptr<tensor<5x5x576x1xf32>>
+    %169 = util.global.address @"__iree_flow___sm_node1088__m.layer-191.gamma" : !util.ptr<tensor<576xf32>>
+    %170 = util.global.address @"__iree_flow___sm_node1089__m.layer-191.beta" : !util.ptr<tensor<576xf32>>
+    %171 = util.global.address @"__iree_flow___sm_node1090__m.layer-191.moving_mean" : !util.ptr<tensor<576xf32>>
+    %172 = util.global.address @"__iree_flow___sm_node1091__m.layer-191.moving_variance" : !util.ptr<tensor<576xf32>>
+    %173 = util.global.address @"__iree_flow___sm_node1114__m.layer-198.kernel" : !util.ptr<tensor<1x1x576x144xf32>>
+    %174 = util.global.address @"__iree_flow___sm_node1115__m.layer-198.bias" : !util.ptr<tensor<144xf32>>
+    %175 = util.global.address @"__iree_flow___sm_node1124__m.layer-200.kernel" : !util.ptr<tensor<1x1x144x576xf32>>
+    %176 = util.global.address @"__iree_flow___sm_node1125__m.layer-200.bias" : !util.ptr<tensor<576xf32>>
+    %177 = util.global.address @"__iree_flow___sm_node1140__m.layer-205.kernel" : !util.ptr<tensor<1x1x576x96xf32>>
+    %178 = util.global.address @"__iree_flow___sm_node1146__m.layer-206.gamma" : !util.ptr<tensor<96xf32>>
+    %179 = util.global.address @"__iree_flow___sm_node1147__m.layer-206.beta" : !util.ptr<tensor<96xf32>>
+    %180 = util.global.address @"__iree_flow___sm_node1148__m.layer-206.moving_mean" : !util.ptr<tensor<96xf32>>
+    %181 = util.global.address @"__iree_flow___sm_node1149__m.layer-206.moving_variance" : !util.ptr<tensor<96xf32>>
+    %182 = util.global.address @"__iree_flow___sm_node1158__m.layer-208.kernel" : !util.ptr<tensor<1x1x96x576xf32>>
+    %183 = util.global.address @"__iree_flow___sm_node1164__m.layer-209.gamma" : !util.ptr<tensor<576xf32>>
+    %184 = util.global.address @"__iree_flow___sm_node1165__m.layer-209.beta" : !util.ptr<tensor<576xf32>>
+    %185 = util.global.address @"__iree_flow___sm_node1166__m.layer-209.moving_mean" : !util.ptr<tensor<576xf32>>
+    %186 = util.global.address @"__iree_flow___sm_node1167__m.layer-209.moving_variance" : !util.ptr<tensor<576xf32>>
+    %187 = util.global.address @"__iree_flow___sm_node1182__m.layer-214.depthwise_kernel" : !util.ptr<tensor<5x5x576x1xf32>>
+    %188 = util.global.address @"__iree_flow___sm_node1188__m.layer-215.gamma" : !util.ptr<tensor<576xf32>>
+    %189 = util.global.address @"__iree_flow___sm_node1189__m.layer-215.beta" : !util.ptr<tensor<576xf32>>
+    %190 = util.global.address @"__iree_flow___sm_node1190__m.layer-215.moving_mean" : !util.ptr<tensor<576xf32>>
+    %191 = util.global.address @"__iree_flow___sm_node1191__m.layer-215.moving_variance" : !util.ptr<tensor<576xf32>>
+    %192 = util.global.address @"__iree_flow___sm_node1214__m.layer-222.kernel" : !util.ptr<tensor<1x1x576x144xf32>>
+    %193 = util.global.address @"__iree_flow___sm_node1215__m.layer-222.bias" : !util.ptr<tensor<144xf32>>
+    %194 = util.global.address @"__iree_flow___sm_node1224__m.layer-224.kernel" : !util.ptr<tensor<1x1x144x576xf32>>
+    %195 = util.global.address @"__iree_flow___sm_node1225__m.layer-224.bias" : !util.ptr<tensor<576xf32>>
+    %196 = util.global.address @"__iree_flow___sm_node1240__m.layer-229.kernel" : !util.ptr<tensor<1x1x576x96xf32>>
+    %197 = util.global.address @"__iree_flow___sm_node1246__m.layer-230.gamma" : !util.ptr<tensor<96xf32>>
+    %198 = util.global.address @"__iree_flow___sm_node1247__m.layer-230.beta" : !util.ptr<tensor<96xf32>>
+    %199 = util.global.address @"__iree_flow___sm_node1248__m.layer-230.moving_mean" : !util.ptr<tensor<96xf32>>
+    %200 = util.global.address @"__iree_flow___sm_node1249__m.layer-230.moving_variance" : !util.ptr<tensor<96xf32>>
+    %201 = util.global.address @"__iree_flow___sm_node1258__m.layer-232.kernel" : !util.ptr<tensor<1x1x96x576xf32>>
+    %202 = util.global.address @"__iree_flow___sm_node1264__m.layer-233.gamma" : !util.ptr<tensor<576xf32>>
+    %203 = util.global.address @"__iree_flow___sm_node1265__m.layer-233.beta" : !util.ptr<tensor<576xf32>>
+    %204 = util.global.address @"__iree_flow___sm_node1266__m.layer-233.moving_mean" : !util.ptr<tensor<576xf32>>
+    %205 = util.global.address @"__iree_flow___sm_node1267__m.layer-233.moving_variance" : !util.ptr<tensor<576xf32>>
+    %206 = util.global.address @"__iree_flow___sm_node1290__m.layer-240.kernel" : !util.ptr<tensor<1x1x576x1024xf32>>
+    %207 = util.global.address @"__iree_flow___sm_node1291__m.layer-240.bias" : !util.ptr<tensor<1024xf32>>
+    %208 = util.global.address @"__iree_flow___sm_node1310__m.layer-246.kernel" : !util.ptr<tensor<1x1x1024x1000xf32>>
+    %209 = util.global.address @"__iree_flow___sm_node1311__m.layer-246.bias" : !util.ptr<tensor<1000xf32>>
     %210 = mhlo.constant dense<0.00784313772> : tensor<1x224x224x3xf32>
     %211 = mhlo.constant dense<-1.000000e+00> : tensor<1x224x224x3xf32>
     %212 = mhlo.constant dense<3.000000e+00> : tensor<1x112x112x16xf32>
@@ -478,216 +478,216 @@
     %264 = mhlo.constant dense<6.000000e+00> : tensor<f32>
     %265 = mhlo.constant dense<0xFF800000> : tensor<f32>
     %266 = mhlo.constant dense<0.000000e+00> : tensor<f32>
-    %267 = flow.variable.load.indirect %205 : !util.ptr<tensor<576xf32>> -> tensor<576xf32>
-    %268 = flow.variable.load.indirect %204 : !util.ptr<tensor<576xf32>> -> tensor<576xf32>
-    %269 = flow.variable.load.indirect %203 : !util.ptr<tensor<576xf32>> -> tensor<576xf32>
-    %270 = flow.variable.load.indirect %202 : !util.ptr<tensor<576xf32>> -> tensor<576xf32>
-    %271 = flow.variable.load.indirect %201 : !util.ptr<tensor<1x1x96x576xf32>> -> tensor<1x1x96x576xf32>
-    %272 = flow.variable.load.indirect %207 : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
-    %273 = flow.variable.load.indirect %206 : !util.ptr<tensor<1x1x576x1024xf32>> -> tensor<1x1x576x1024xf32>
-    %274 = flow.variable.load.indirect %4 : !util.ptr<tensor<16xf32>> -> tensor<16xf32>
-    %275 = flow.variable.load.indirect %3 : !util.ptr<tensor<16xf32>> -> tensor<16xf32>
-    %276 = flow.variable.load.indirect %2 : !util.ptr<tensor<16xf32>> -> tensor<16xf32>
-    %277 = flow.variable.load.indirect %1 : !util.ptr<tensor<16xf32>> -> tensor<16xf32>
-    %278 = flow.variable.load.indirect %0 : !util.ptr<tensor<3x3x3x16xf32>> -> tensor<3x3x3x16xf32>
-    %279 = flow.variable.load.indirect %191 : !util.ptr<tensor<576xf32>> -> tensor<576xf32>
-    %280 = flow.variable.load.indirect %190 : !util.ptr<tensor<576xf32>> -> tensor<576xf32>
-    %281 = flow.variable.load.indirect %189 : !util.ptr<tensor<576xf32>> -> tensor<576xf32>
-    %282 = flow.variable.load.indirect %188 : !util.ptr<tensor<576xf32>> -> tensor<576xf32>
-    %283 = flow.variable.load.indirect %187 : !util.ptr<tensor<5x5x576x1xf32>> -> tensor<5x5x576x1xf32>
-    %284 = flow.variable.load.indirect %186 : !util.ptr<tensor<576xf32>> -> tensor<576xf32>
-    %285 = flow.variable.load.indirect %185 : !util.ptr<tensor<576xf32>> -> tensor<576xf32>
-    %286 = flow.variable.load.indirect %184 : !util.ptr<tensor<576xf32>> -> tensor<576xf32>
-    %287 = flow.variable.load.indirect %183 : !util.ptr<tensor<576xf32>> -> tensor<576xf32>
-    %288 = flow.variable.load.indirect %182 : !util.ptr<tensor<1x1x96x576xf32>> -> tensor<1x1x96x576xf32>
-    %289 = flow.variable.load.indirect %200 : !util.ptr<tensor<96xf32>> -> tensor<96xf32>
-    %290 = flow.variable.load.indirect %199 : !util.ptr<tensor<96xf32>> -> tensor<96xf32>
-    %291 = flow.variable.load.indirect %198 : !util.ptr<tensor<96xf32>> -> tensor<96xf32>
-    %292 = flow.variable.load.indirect %197 : !util.ptr<tensor<96xf32>> -> tensor<96xf32>
-    %293 = flow.variable.load.indirect %196 : !util.ptr<tensor<1x1x576x96xf32>> -> tensor<1x1x576x96xf32>
-    %294 = flow.variable.load.indirect %195 : !util.ptr<tensor<576xf32>> -> tensor<576xf32>
-    %295 = flow.variable.load.indirect %194 : !util.ptr<tensor<1x1x144x576xf32>> -> tensor<1x1x144x576xf32>
-    %296 = flow.variable.load.indirect %193 : !util.ptr<tensor<144xf32>> -> tensor<144xf32>
-    %297 = flow.variable.load.indirect %192 : !util.ptr<tensor<1x1x576x144xf32>> -> tensor<1x1x576x144xf32>
-    %298 = flow.variable.load.indirect %28 : !util.ptr<tensor<72xf32>> -> tensor<72xf32>
-    %299 = flow.variable.load.indirect %27 : !util.ptr<tensor<72xf32>> -> tensor<72xf32>
-    %300 = flow.variable.load.indirect %26 : !util.ptr<tensor<72xf32>> -> tensor<72xf32>
-    %301 = flow.variable.load.indirect %25 : !util.ptr<tensor<72xf32>> -> tensor<72xf32>
-    %302 = flow.variable.load.indirect %24 : !util.ptr<tensor<3x3x72x1xf32>> -> tensor<3x3x72x1xf32>
-    %303 = flow.variable.load.indirect %23 : !util.ptr<tensor<72xf32>> -> tensor<72xf32>
-    %304 = flow.variable.load.indirect %22 : !util.ptr<tensor<72xf32>> -> tensor<72xf32>
-    %305 = flow.variable.load.indirect %21 : !util.ptr<tensor<72xf32>> -> tensor<72xf32>
-    %306 = flow.variable.load.indirect %20 : !util.ptr<tensor<72xf32>> -> tensor<72xf32>
-    %307 = flow.variable.load.indirect %19 : !util.ptr<tensor<1x1x16x72xf32>> -> tensor<1x1x16x72xf32>
-    %308 = flow.variable.load.indirect %33 : !util.ptr<tensor<24xf32>> -> tensor<24xf32>
-    %309 = flow.variable.load.indirect %32 : !util.ptr<tensor<24xf32>> -> tensor<24xf32>
-    %310 = flow.variable.load.indirect %31 : !util.ptr<tensor<24xf32>> -> tensor<24xf32>
-    %311 = flow.variable.load.indirect %30 : !util.ptr<tensor<24xf32>> -> tensor<24xf32>
-    %312 = flow.variable.load.indirect %29 : !util.ptr<tensor<1x1x72x24xf32>> -> tensor<1x1x72x24xf32>
-    %313 = flow.variable.load.indirect %43 : !util.ptr<tensor<88xf32>> -> tensor<88xf32>
-    %314 = flow.variable.load.indirect %42 : !util.ptr<tensor<88xf32>> -> tensor<88xf32>
-    %315 = flow.variable.load.indirect %41 : !util.ptr<tensor<88xf32>> -> tensor<88xf32>
-    %316 = flow.variable.load.indirect %40 : !util.ptr<tensor<88xf32>> -> tensor<88xf32>
-    %317 = flow.variable.load.indirect %39 : !util.ptr<tensor<3x3x88x1xf32>> -> tensor<3x3x88x1xf32>
-    %318 = flow.variable.load.indirect %38 : !util.ptr<tensor<88xf32>> -> tensor<88xf32>
-    %319 = flow.variable.load.indirect %37 : !util.ptr<tensor<88xf32>> -> tensor<88xf32>
-    %320 = flow.variable.load.indirect %36 : !util.ptr<tensor<88xf32>> -> tensor<88xf32>
-    %321 = flow.variable.load.indirect %35 : !util.ptr<tensor<88xf32>> -> tensor<88xf32>
-    %322 = flow.variable.load.indirect %34 : !util.ptr<tensor<1x1x24x88xf32>> -> tensor<1x1x24x88xf32>
-    %323 = flow.variable.load.indirect %48 : !util.ptr<tensor<24xf32>> -> tensor<24xf32>
-    %324 = flow.variable.load.indirect %47 : !util.ptr<tensor<24xf32>> -> tensor<24xf32>
-    %325 = flow.variable.load.indirect %46 : !util.ptr<tensor<24xf32>> -> tensor<24xf32>
-    %326 = flow.variable.load.indirect %45 : !util.ptr<tensor<24xf32>> -> tensor<24xf32>
-    %327 = flow.variable.load.indirect %44 : !util.ptr<tensor<1x1x88x24xf32>> -> tensor<1x1x88x24xf32>
-    %328 = flow.variable.load.indirect %58 : !util.ptr<tensor<96xf32>> -> tensor<96xf32>
-    %329 = flow.variable.load.indirect %57 : !util.ptr<tensor<96xf32>> -> tensor<96xf32>
-    %330 = flow.variable.load.indirect %56 : !util.ptr<tensor<96xf32>> -> tensor<96xf32>
-    %331 = flow.variable.load.indirect %55 : !util.ptr<tensor<96xf32>> -> tensor<96xf32>
-    %332 = flow.variable.load.indirect %54 : !util.ptr<tensor<5x5x96x1xf32>> -> tensor<5x5x96x1xf32>
-    %333 = flow.variable.load.indirect %53 : !util.ptr<tensor<96xf32>> -> tensor<96xf32>
-    %334 = flow.variable.load.indirect %52 : !util.ptr<tensor<96xf32>> -> tensor<96xf32>
-    %335 = flow.variable.load.indirect %51 : !util.ptr<tensor<96xf32>> -> tensor<96xf32>
-    %336 = flow.variable.load.indirect %50 : !util.ptr<tensor<96xf32>> -> tensor<96xf32>
-    %337 = flow.variable.load.indirect %49 : !util.ptr<tensor<1x1x24x96xf32>> -> tensor<1x1x24x96xf32>
-    %338 = flow.variable.load.indirect %67 : !util.ptr<tensor<40xf32>> -> tensor<40xf32>
-    %339 = flow.variable.load.indirect %66 : !util.ptr<tensor<40xf32>> -> tensor<40xf32>
-    %340 = flow.variable.load.indirect %65 : !util.ptr<tensor<40xf32>> -> tensor<40xf32>
-    %341 = flow.variable.load.indirect %64 : !util.ptr<tensor<40xf32>> -> tensor<40xf32>
-    %342 = flow.variable.load.indirect %63 : !util.ptr<tensor<1x1x96x40xf32>> -> tensor<1x1x96x40xf32>
-    %343 = flow.variable.load.indirect %62 : !util.ptr<tensor<96xf32>> -> tensor<96xf32>
-    %344 = flow.variable.load.indirect %61 : !util.ptr<tensor<1x1x24x96xf32>> -> tensor<1x1x24x96xf32>
-    %345 = flow.variable.load.indirect %60 : !util.ptr<tensor<24xf32>> -> tensor<24xf32>
-    %346 = flow.variable.load.indirect %59 : !util.ptr<tensor<1x1x96x24xf32>> -> tensor<1x1x96x24xf32>
-    %347 = flow.variable.load.indirect %77 : !util.ptr<tensor<240xf32>> -> tensor<240xf32>
-    %348 = flow.variable.load.indirect %76 : !util.ptr<tensor<240xf32>> -> tensor<240xf32>
-    %349 = flow.variable.load.indirect %75 : !util.ptr<tensor<240xf32>> -> tensor<240xf32>
-    %350 = flow.variable.load.indirect %74 : !util.ptr<tensor<240xf32>> -> tensor<240xf32>
-    %351 = flow.variable.load.indirect %73 : !util.ptr<tensor<5x5x240x1xf32>> -> tensor<5x5x240x1xf32>
-    %352 = flow.variable.load.indirect %72 : !util.ptr<tensor<240xf32>> -> tensor<240xf32>
-    %353 = flow.variable.load.indirect %71 : !util.ptr<tensor<240xf32>> -> tensor<240xf32>
-    %354 = flow.variable.load.indirect %70 : !util.ptr<tensor<240xf32>> -> tensor<240xf32>
-    %355 = flow.variable.load.indirect %69 : !util.ptr<tensor<240xf32>> -> tensor<240xf32>
-    %356 = flow.variable.load.indirect %68 : !util.ptr<tensor<1x1x40x240xf32>> -> tensor<1x1x40x240xf32>
-    %357 = flow.variable.load.indirect %86 : !util.ptr<tensor<40xf32>> -> tensor<40xf32>
-    %358 = flow.variable.load.indirect %85 : !util.ptr<tensor<40xf32>> -> tensor<40xf32>
-    %359 = flow.variable.load.indirect %84 : !util.ptr<tensor<40xf32>> -> tensor<40xf32>
-    %360 = flow.variable.load.indirect %83 : !util.ptr<tensor<40xf32>> -> tensor<40xf32>
-    %361 = flow.variable.load.indirect %82 : !util.ptr<tensor<1x1x240x40xf32>> -> tensor<1x1x240x40xf32>
-    %362 = flow.variable.load.indirect %81 : !util.ptr<tensor<240xf32>> -> tensor<240xf32>
-    %363 = flow.variable.load.indirect %80 : !util.ptr<tensor<1x1x64x240xf32>> -> tensor<1x1x64x240xf32>
-    %364 = flow.variable.load.indirect %79 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %365 = flow.variable.load.indirect %78 : !util.ptr<tensor<1x1x240x64xf32>> -> tensor<1x1x240x64xf32>
-    %366 = flow.variable.load.indirect %96 : !util.ptr<tensor<240xf32>> -> tensor<240xf32>
-    %367 = flow.variable.load.indirect %95 : !util.ptr<tensor<240xf32>> -> tensor<240xf32>
-    %368 = flow.variable.load.indirect %94 : !util.ptr<tensor<240xf32>> -> tensor<240xf32>
-    %369 = flow.variable.load.indirect %93 : !util.ptr<tensor<240xf32>> -> tensor<240xf32>
-    %370 = flow.variable.load.indirect %92 : !util.ptr<tensor<5x5x240x1xf32>> -> tensor<5x5x240x1xf32>
-    %371 = flow.variable.load.indirect %91 : !util.ptr<tensor<240xf32>> -> tensor<240xf32>
-    %372 = flow.variable.load.indirect %90 : !util.ptr<tensor<240xf32>> -> tensor<240xf32>
-    %373 = flow.variable.load.indirect %89 : !util.ptr<tensor<240xf32>> -> tensor<240xf32>
-    %374 = flow.variable.load.indirect %88 : !util.ptr<tensor<240xf32>> -> tensor<240xf32>
-    %375 = flow.variable.load.indirect %87 : !util.ptr<tensor<1x1x40x240xf32>> -> tensor<1x1x40x240xf32>
-    %376 = flow.variable.load.indirect %105 : !util.ptr<tensor<40xf32>> -> tensor<40xf32>
-    %377 = flow.variable.load.indirect %104 : !util.ptr<tensor<40xf32>> -> tensor<40xf32>
-    %378 = flow.variable.load.indirect %103 : !util.ptr<tensor<40xf32>> -> tensor<40xf32>
-    %379 = flow.variable.load.indirect %102 : !util.ptr<tensor<40xf32>> -> tensor<40xf32>
-    %380 = flow.variable.load.indirect %101 : !util.ptr<tensor<1x1x240x40xf32>> -> tensor<1x1x240x40xf32>
-    %381 = flow.variable.load.indirect %100 : !util.ptr<tensor<240xf32>> -> tensor<240xf32>
-    %382 = flow.variable.load.indirect %99 : !util.ptr<tensor<1x1x64x240xf32>> -> tensor<1x1x64x240xf32>
-    %383 = flow.variable.load.indirect %98 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %384 = flow.variable.load.indirect %97 : !util.ptr<tensor<1x1x240x64xf32>> -> tensor<1x1x240x64xf32>
-    %385 = flow.variable.load.indirect %115 : !util.ptr<tensor<120xf32>> -> tensor<120xf32>
-    %386 = flow.variable.load.indirect %114 : !util.ptr<tensor<120xf32>> -> tensor<120xf32>
-    %387 = flow.variable.load.indirect %113 : !util.ptr<tensor<120xf32>> -> tensor<120xf32>
-    %388 = flow.variable.load.indirect %112 : !util.ptr<tensor<120xf32>> -> tensor<120xf32>
-    %389 = flow.variable.load.indirect %111 : !util.ptr<tensor<5x5x120x1xf32>> -> tensor<5x5x120x1xf32>
-    %390 = flow.variable.load.indirect %110 : !util.ptr<tensor<120xf32>> -> tensor<120xf32>
-    %391 = flow.variable.load.indirect %109 : !util.ptr<tensor<120xf32>> -> tensor<120xf32>
-    %392 = flow.variable.load.indirect %108 : !util.ptr<tensor<120xf32>> -> tensor<120xf32>
-    %393 = flow.variable.load.indirect %107 : !util.ptr<tensor<120xf32>> -> tensor<120xf32>
-    %394 = flow.variable.load.indirect %106 : !util.ptr<tensor<1x1x40x120xf32>> -> tensor<1x1x40x120xf32>
-    %395 = flow.variable.load.indirect %124 : !util.ptr<tensor<48xf32>> -> tensor<48xf32>
-    %396 = flow.variable.load.indirect %123 : !util.ptr<tensor<48xf32>> -> tensor<48xf32>
-    %397 = flow.variable.load.indirect %122 : !util.ptr<tensor<48xf32>> -> tensor<48xf32>
-    %398 = flow.variable.load.indirect %121 : !util.ptr<tensor<48xf32>> -> tensor<48xf32>
-    %399 = flow.variable.load.indirect %120 : !util.ptr<tensor<1x1x120x48xf32>> -> tensor<1x1x120x48xf32>
-    %400 = flow.variable.load.indirect %119 : !util.ptr<tensor<120xf32>> -> tensor<120xf32>
-    %401 = flow.variable.load.indirect %118 : !util.ptr<tensor<1x1x32x120xf32>> -> tensor<1x1x32x120xf32>
-    %402 = flow.variable.load.indirect %117 : !util.ptr<tensor<32xf32>> -> tensor<32xf32>
-    %403 = flow.variable.load.indirect %116 : !util.ptr<tensor<1x1x120x32xf32>> -> tensor<1x1x120x32xf32>
-    %404 = flow.variable.load.indirect %134 : !util.ptr<tensor<144xf32>> -> tensor<144xf32>
-    %405 = flow.variable.load.indirect %133 : !util.ptr<tensor<144xf32>> -> tensor<144xf32>
-    %406 = flow.variable.load.indirect %132 : !util.ptr<tensor<144xf32>> -> tensor<144xf32>
-    %407 = flow.variable.load.indirect %131 : !util.ptr<tensor<144xf32>> -> tensor<144xf32>
-    %408 = flow.variable.load.indirect %130 : !util.ptr<tensor<5x5x144x1xf32>> -> tensor<5x5x144x1xf32>
-    %409 = flow.variable.load.indirect %129 : !util.ptr<tensor<144xf32>> -> tensor<144xf32>
-    %410 = flow.variable.load.indirect %128 : !util.ptr<tensor<144xf32>> -> tensor<144xf32>
-    %411 = flow.variable.load.indirect %127 : !util.ptr<tensor<144xf32>> -> tensor<144xf32>
-    %412 = flow.variable.load.indirect %126 : !util.ptr<tensor<144xf32>> -> tensor<144xf32>
-    %413 = flow.variable.load.indirect %125 : !util.ptr<tensor<1x1x48x144xf32>> -> tensor<1x1x48x144xf32>
-    %414 = flow.variable.load.indirect %143 : !util.ptr<tensor<48xf32>> -> tensor<48xf32>
-    %415 = flow.variable.load.indirect %142 : !util.ptr<tensor<48xf32>> -> tensor<48xf32>
-    %416 = flow.variable.load.indirect %141 : !util.ptr<tensor<48xf32>> -> tensor<48xf32>
-    %417 = flow.variable.load.indirect %140 : !util.ptr<tensor<48xf32>> -> tensor<48xf32>
-    %418 = flow.variable.load.indirect %139 : !util.ptr<tensor<1x1x144x48xf32>> -> tensor<1x1x144x48xf32>
-    %419 = flow.variable.load.indirect %138 : !util.ptr<tensor<144xf32>> -> tensor<144xf32>
-    %420 = flow.variable.load.indirect %137 : !util.ptr<tensor<1x1x40x144xf32>> -> tensor<1x1x40x144xf32>
-    %421 = flow.variable.load.indirect %136 : !util.ptr<tensor<40xf32>> -> tensor<40xf32>
-    %422 = flow.variable.load.indirect %135 : !util.ptr<tensor<1x1x144x40xf32>> -> tensor<1x1x144x40xf32>
-    %423 = flow.variable.load.indirect %153 : !util.ptr<tensor<288xf32>> -> tensor<288xf32>
-    %424 = flow.variable.load.indirect %152 : !util.ptr<tensor<288xf32>> -> tensor<288xf32>
-    %425 = flow.variable.load.indirect %151 : !util.ptr<tensor<288xf32>> -> tensor<288xf32>
-    %426 = flow.variable.load.indirect %150 : !util.ptr<tensor<288xf32>> -> tensor<288xf32>
-    %427 = flow.variable.load.indirect %149 : !util.ptr<tensor<5x5x288x1xf32>> -> tensor<5x5x288x1xf32>
-    %428 = flow.variable.load.indirect %148 : !util.ptr<tensor<288xf32>> -> tensor<288xf32>
-    %429 = flow.variable.load.indirect %147 : !util.ptr<tensor<288xf32>> -> tensor<288xf32>
-    %430 = flow.variable.load.indirect %146 : !util.ptr<tensor<288xf32>> -> tensor<288xf32>
-    %431 = flow.variable.load.indirect %145 : !util.ptr<tensor<288xf32>> -> tensor<288xf32>
-    %432 = flow.variable.load.indirect %144 : !util.ptr<tensor<1x1x48x288xf32>> -> tensor<1x1x48x288xf32>
-    %433 = flow.variable.load.indirect %162 : !util.ptr<tensor<96xf32>> -> tensor<96xf32>
-    %434 = flow.variable.load.indirect %161 : !util.ptr<tensor<96xf32>> -> tensor<96xf32>
-    %435 = flow.variable.load.indirect %160 : !util.ptr<tensor<96xf32>> -> tensor<96xf32>
-    %436 = flow.variable.load.indirect %159 : !util.ptr<tensor<96xf32>> -> tensor<96xf32>
-    %437 = flow.variable.load.indirect %158 : !util.ptr<tensor<1x1x288x96xf32>> -> tensor<1x1x288x96xf32>
-    %438 = flow.variable.load.indirect %157 : !util.ptr<tensor<288xf32>> -> tensor<288xf32>
-    %439 = flow.variable.load.indirect %156 : !util.ptr<tensor<1x1x72x288xf32>> -> tensor<1x1x72x288xf32>
-    %440 = flow.variable.load.indirect %155 : !util.ptr<tensor<72xf32>> -> tensor<72xf32>
-    %441 = flow.variable.load.indirect %154 : !util.ptr<tensor<1x1x288x72xf32>> -> tensor<1x1x288x72xf32>
-    %442 = flow.variable.load.indirect %172 : !util.ptr<tensor<576xf32>> -> tensor<576xf32>
-    %443 = flow.variable.load.indirect %171 : !util.ptr<tensor<576xf32>> -> tensor<576xf32>
-    %444 = flow.variable.load.indirect %170 : !util.ptr<tensor<576xf32>> -> tensor<576xf32>
-    %445 = flow.variable.load.indirect %169 : !util.ptr<tensor<576xf32>> -> tensor<576xf32>
-    %446 = flow.variable.load.indirect %168 : !util.ptr<tensor<5x5x576x1xf32>> -> tensor<5x5x576x1xf32>
-    %447 = flow.variable.load.indirect %167 : !util.ptr<tensor<576xf32>> -> tensor<576xf32>
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-    %449 = flow.variable.load.indirect %165 : !util.ptr<tensor<576xf32>> -> tensor<576xf32>
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+    %445 = util.global.load.indirect %169 : !util.ptr<tensor<576xf32>> -> tensor<576xf32>
+    %446 = util.global.load.indirect %168 : !util.ptr<tensor<5x5x576x1xf32>> -> tensor<5x5x576x1xf32>
+    %447 = util.global.load.indirect %167 : !util.ptr<tensor<576xf32>> -> tensor<576xf32>
+    %448 = util.global.load.indirect %166 : !util.ptr<tensor<576xf32>> -> tensor<576xf32>
+    %449 = util.global.load.indirect %165 : !util.ptr<tensor<576xf32>> -> tensor<576xf32>
+    %450 = util.global.load.indirect %164 : !util.ptr<tensor<576xf32>> -> tensor<576xf32>
+    %451 = util.global.load.indirect %163 : !util.ptr<tensor<1x1x96x576xf32>> -> tensor<1x1x96x576xf32>
+    %452 = util.global.load.indirect %181 : !util.ptr<tensor<96xf32>> -> tensor<96xf32>
+    %453 = util.global.load.indirect %180 : !util.ptr<tensor<96xf32>> -> tensor<96xf32>
+    %454 = util.global.load.indirect %179 : !util.ptr<tensor<96xf32>> -> tensor<96xf32>
+    %455 = util.global.load.indirect %178 : !util.ptr<tensor<96xf32>> -> tensor<96xf32>
+    %456 = util.global.load.indirect %177 : !util.ptr<tensor<1x1x576x96xf32>> -> tensor<1x1x576x96xf32>
+    %457 = util.global.load.indirect %176 : !util.ptr<tensor<576xf32>> -> tensor<576xf32>
+    %458 = util.global.load.indirect %175 : !util.ptr<tensor<1x1x144x576xf32>> -> tensor<1x1x144x576xf32>
+    %459 = util.global.load.indirect %174 : !util.ptr<tensor<144xf32>> -> tensor<144xf32>
+    %460 = util.global.load.indirect %173 : !util.ptr<tensor<1x1x576x144xf32>> -> tensor<1x1x576x144xf32>
+    %461 = util.global.load.indirect %9 : !util.ptr<tensor<16xf32>> -> tensor<16xf32>
+    %462 = util.global.load.indirect %8 : !util.ptr<tensor<16xf32>> -> tensor<16xf32>
+    %463 = util.global.load.indirect %7 : !util.ptr<tensor<16xf32>> -> tensor<16xf32>
+    %464 = util.global.load.indirect %6 : !util.ptr<tensor<16xf32>> -> tensor<16xf32>
+    %465 = util.global.load.indirect %5 : !util.ptr<tensor<3x3x16x1xf32>> -> tensor<3x3x16x1xf32>
+    %466 = util.global.load.indirect %18 : !util.ptr<tensor<16xf32>> -> tensor<16xf32>
+    %467 = util.global.load.indirect %17 : !util.ptr<tensor<16xf32>> -> tensor<16xf32>
+    %468 = util.global.load.indirect %16 : !util.ptr<tensor<16xf32>> -> tensor<16xf32>
+    %469 = util.global.load.indirect %15 : !util.ptr<tensor<16xf32>> -> tensor<16xf32>
+    %470 = util.global.load.indirect %14 : !util.ptr<tensor<1x1x16x16xf32>> -> tensor<1x1x16x16xf32>
+    %471 = util.global.load.indirect %13 : !util.ptr<tensor<16xf32>> -> tensor<16xf32>
+    %472 = util.global.load.indirect %12 : !util.ptr<tensor<1x1x8x16xf32>> -> tensor<1x1x8x16xf32>
+    %473 = util.global.load.indirect %11 : !util.ptr<tensor<8xf32>> -> tensor<8xf32>
+    %474 = util.global.load.indirect %10 : !util.ptr<tensor<1x1x16x8xf32>> -> tensor<1x1x16x8xf32>
+    %475 = util.global.load.indirect %209 : !util.ptr<tensor<1000xf32>> -> tensor<1000xf32>
+    %476 = util.global.load.indirect %208 : !util.ptr<tensor<1x1x1024x1000xf32>> -> tensor<1x1x1024x1000xf32>
     %477 = mhlo.multiply %arg0, %210 : tensor<1x224x224x3xf32>
     %478 = mhlo.add %477, %211 : tensor<1x224x224x3xf32>
     %479 = "mhlo.convolution"(%478, %278) {batch_group_count = 1 : i64, dimension_numbers = {input_batch_dimension = 0 : i64, input_feature_dimension = 3 : i64, input_spatial_dimensions = dense<[1, 2]> : tensor<2xi64>, kernel_input_feature_dimension = 2 : i64, kernel_output_feature_dimension = 3 : i64, kernel_spatial_dimensions = dense<[0, 1]> : tensor<2xi64>, output_batch_dimension = 0 : i64, output_feature_dimension = 3 : i64, output_spatial_dimensions = dense<[1, 2]> : tensor<2xi64>}, feature_group_count = 1 : i64, padding = dense<[[0, 1], [0, 1]]> : tensor<2x2xi64>, rhs_dilation = dense<1> : tensor<2xi64>, window_strides = dense<2> : tensor<2xi64>} : (tensor<1x224x224x3xf32>, tensor<3x3x3x16xf32>) -> tensor<1x112x112x16xf32>
diff --git a/iree/test/e2e/models/resnet50_fake_weights.mlir b/iree/test/e2e/models/resnet50_fake_weights.mlir
index 14fca46..764d1fa 100644
--- a/iree/test/e2e/models/resnet50_fake_weights.mlir
+++ b/iree/test/e2e/models/resnet50_fake_weights.mlir
@@ -5,648 +5,648 @@
 // RUN: [[ $IREE_VULKAN_DISABLE == 1 ]] || (iree-run-mlir --iree-input-type=mhlo -iree-hal-target-backends=vulkan-spirv %s -function-input="1x224x224x3xf32" | IreeFileCheck %s)
 
 module {
-  flow.variable @"__iree_flow___sm_node188__m.layer-2.kernel" dense<1.000000e+00> : tensor<7x7x3x64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node189__m.layer-2.bias" dense<5.000000e-01> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node195__m.layer-3.gamma" dense<0.333333343> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node196__m.layer-3.beta" dense<2.500000e-01> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node197__m.layer-3.moving_mean" dense<2.000000e-01> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node198__m.layer-3.moving_variance" dense<0.166666672> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node215__m.layer-7.kernel" dense<0.142857149> : tensor<1x1x64x64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node216__m.layer-7.bias" dense<1.250000e-01> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node222__m.layer-8.gamma" dense<0.111111112> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node223__m.layer-8.beta" dense<1.000000e-01> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node224__m.layer-8.moving_mean" dense<0.0909090936> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node225__m.layer-8.moving_variance" dense<0.0833333358> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node234__m.layer-10.kernel" dense<0.0769230798> : tensor<3x3x64x64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node235__m.layer-10.bias" dense<0.0714285746> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node241__m.layer-11.gamma" dense<0.0666666701> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node242__m.layer-11.beta" dense<6.250000e-02> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node243__m.layer-11.moving_mean" dense<0.0588235296> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node244__m.layer-11.moving_variance" dense<0.055555556> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node253__m.layer-13.kernel" dense<0.0526315793> : tensor<1x1x64x256xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node254__m.layer-13.bias" dense<5.000000e-02> : tensor<256xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node259__m.layer-14.kernel" dense<0.0476190485> : tensor<1x1x64x256xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node260__m.layer-14.bias" dense<0.0454545468> : tensor<256xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node266__m.layer-15.gamma" dense<0.0434782617> : tensor<256xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node267__m.layer-15.beta" dense<0.0416666679> : tensor<256xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node268__m.layer-15.moving_mean" dense<4.000000e-02> : tensor<256xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node269__m.layer-15.moving_variance" dense<0.0384615399> : tensor<256xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node275__m.layer-16.gamma" dense<0.0370370373> : tensor<256xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node276__m.layer-16.beta" dense<0.0357142873> : tensor<256xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node277__m.layer-16.moving_mean" dense<0.0344827585> : tensor<256xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node278__m.layer-16.moving_variance" dense<0.0333333351> : tensor<256xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node291__m.layer-19.kernel" dense<0.0322580636> : tensor<1x1x256x64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node292__m.layer-19.bias" dense<3.125000e-02> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node298__m.layer-20.gamma" dense<0.0303030312> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node299__m.layer-20.beta" dense<0.0294117648> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node300__m.layer-20.moving_mean" dense<0.0285714287> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node301__m.layer-20.moving_variance" dense<0.027777778> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node310__m.layer-22.kernel" dense<0.0270270277> : tensor<3x3x64x64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node311__m.layer-22.bias" dense<0.0263157897> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node317__m.layer-23.gamma" dense<0.025641026> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node318__m.layer-23.beta" dense<2.500000e-02> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node319__m.layer-23.moving_mean" dense<0.024390243> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node320__m.layer-23.moving_variance" dense<0.0238095243> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node329__m.layer-25.kernel" dense<0.0232558139> : tensor<1x1x64x256xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node330__m.layer-25.bias" dense<0.0227272734> : tensor<256xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node336__m.layer-26.gamma" dense<0.0222222228> : tensor<256xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node337__m.layer-26.beta" dense<0.0217391308> : tensor<256xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node338__m.layer-26.moving_mean" dense<0.0212765951> : tensor<256xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node339__m.layer-26.moving_variance" dense<0.020833334> : tensor<256xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node352__m.layer-29.kernel" dense<0.0204081628> : tensor<1x1x256x64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node353__m.layer-29.bias" dense<2.000000e-02> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node359__m.layer-30.gamma" dense<0.0196078438> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node360__m.layer-30.beta" dense<0.0192307699> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node361__m.layer-30.moving_mean" dense<0.0188679248> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node362__m.layer-30.moving_variance" dense<0.0185185187> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node371__m.layer-32.kernel" dense<0.0181818176> : tensor<3x3x64x64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node372__m.layer-32.bias" dense<0.0178571437> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node378__m.layer-33.gamma" dense<0.0175438598> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node379__m.layer-33.beta" dense<0.0172413792> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node380__m.layer-33.moving_mean" dense<0.0169491526> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node381__m.layer-33.moving_variance" dense<0.0166666675> : tensor<64xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node390__m.layer-35.kernel" dense<0.0163934417> : tensor<1x1x64x256xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node391__m.layer-35.bias" dense<0.0161290318> : tensor<256xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node397__m.layer-36.gamma" dense<0.0158730168> : tensor<256xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node398__m.layer-36.beta" dense<1.562500e-02> : tensor<256xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node399__m.layer-36.moving_mean" dense<0.0153846154> : tensor<256xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node400__m.layer-36.moving_variance" dense<0.0151515156> : tensor<256xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node413__m.layer-39.kernel" dense<0.0149253728> : tensor<1x1x256x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node414__m.layer-39.bias" dense<0.0147058824> : tensor<128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node420__m.layer-40.gamma" dense<0.0144927539> : tensor<128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node421__m.layer-40.beta" dense<0.0142857144> : tensor<128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node422__m.layer-40.moving_mean" dense<0.0140845068> : tensor<128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node423__m.layer-40.moving_variance" dense<0.013888889> : tensor<128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node432__m.layer-42.kernel" dense<0.01369863> : tensor<3x3x128x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node433__m.layer-42.bias" dense<0.0135135138> : tensor<128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node439__m.layer-43.gamma" dense<0.0133333337> : tensor<128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node440__m.layer-43.beta" dense<0.0131578948> : tensor<128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node441__m.layer-43.moving_mean" dense<0.012987013> : tensor<128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node442__m.layer-43.moving_variance" dense<0.012820513> : tensor<128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node451__m.layer-45.kernel" dense<0.0126582282> : tensor<1x1x256x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node452__m.layer-45.bias" dense<1.250000e-02> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node457__m.layer-46.kernel" dense<0.0123456791> : tensor<1x1x128x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node458__m.layer-46.bias" dense<0.0121951215> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node464__m.layer-47.gamma" dense<0.0120481923> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node465__m.layer-47.beta" dense<0.0119047621> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node466__m.layer-47.moving_mean" dense<0.0117647061> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node467__m.layer-47.moving_variance" dense<0.0116279069> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node473__m.layer-48.gamma" dense<0.0114942528> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node474__m.layer-48.beta" dense<0.0113636367> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node475__m.layer-48.moving_mean" dense<0.0112359552> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node476__m.layer-48.moving_variance" dense<0.0111111114> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node489__m.layer-51.kernel" dense<0.0109890113> : tensor<1x1x512x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node490__m.layer-51.bias" dense<0.0108695654> : tensor<128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node496__m.layer-52.gamma" dense<0.0107526882> : tensor<128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node497__m.layer-52.beta" dense<0.0106382975> : tensor<128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node498__m.layer-52.moving_mean" dense<0.0105263162> : tensor<128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node499__m.layer-52.moving_variance" dense<0.010416667> : tensor<128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node508__m.layer-54.kernel" dense<0.010309278> : tensor<3x3x128x128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node509__m.layer-54.bias" dense<0.0102040814> : tensor<128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node515__m.layer-55.gamma" dense<0.0101010101> : tensor<128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node516__m.layer-55.beta" dense<0.00999999977> : tensor<128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node517__m.layer-55.moving_mean" dense<9.900990e-03> : tensor<128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node518__m.layer-55.moving_variance" dense<0.00980392192> : tensor<128xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node527__m.layer-57.kernel" dense<0.00970873795> : tensor<1x1x128x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node528__m.layer-57.bias" dense<0.00961538497> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node534__m.layer-58.gamma" dense<9.523810e-03> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node535__m.layer-58.beta" dense<0.0094339624> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node536__m.layer-58.moving_mean" dense<0.00934579409> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node537__m.layer-58.moving_variance" dense<0.00925925932> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node550__m.layer-61.kernel" dense<0.00917431153> : tensor<1x1x512x128xf32> attributes {noinline, sym_visibility = "private"}
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-  flow.variable @"__iree_flow___sm_node1021__m.layer-137.moving_variance" dense<0.0039682542> : tensor<256xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1030__m.layer-139.kernel" dense<0.00395256933> : tensor<1x1x256x1024xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1031__m.layer-139.bias" dense<0.00393700786> : tensor<1024xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1037__m.layer-140.gamma" dense<0.00392156886> : tensor<1024xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1038__m.layer-140.beta" dense<3.906250e-03> : tensor<1024xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1039__m.layer-140.moving_mean" dense<0.00389105058> : tensor<1024xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1040__m.layer-140.moving_variance" dense<0.00387596898> : tensor<1024xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1053__m.layer-143.kernel" dense<0.00386100379> : tensor<1x1x1024x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1054__m.layer-143.bias" dense<0.00384615385> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1060__m.layer-144.gamma" dense<0.00383141753> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1061__m.layer-144.beta" dense<0.00381679391> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1062__m.layer-144.moving_mean" dense<0.00380228134> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1063__m.layer-144.moving_variance" dense<0.0037878789> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1072__m.layer-146.kernel" dense<0.00377358496> : tensor<3x3x512x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1073__m.layer-146.bias" dense<0.00375939859> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1079__m.layer-147.gamma" dense<0.00374531839> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1080__m.layer-147.beta" dense<0.0037313432> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1081__m.layer-147.moving_mean" dense<0.00371747208> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1082__m.layer-147.moving_variance" dense<0.00370370364> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1091__m.layer-149.kernel" dense<0.00369003695> : tensor<1x1x1024x2048xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1092__m.layer-149.bias" dense<0.0036764706> : tensor<2048xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1097__m.layer-150.kernel" dense<0.00366300368> : tensor<1x1x512x2048xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1098__m.layer-150.bias" dense<0.00364963501> : tensor<2048xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1104__m.layer-151.gamma" dense<0.00363636366> : tensor<2048xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1105__m.layer-151.beta" dense<0.00362318847> : tensor<2048xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1106__m.layer-151.moving_mean" dense<0.00361010828> : tensor<2048xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1107__m.layer-151.moving_variance" dense<0.00359712238> : tensor<2048xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1113__m.layer-152.gamma" dense<0.00358422939> : tensor<2048xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1114__m.layer-152.beta" dense<0.00357142859> : tensor<2048xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1115__m.layer-152.moving_mean" dense<0.00355871883> : tensor<2048xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1116__m.layer-152.moving_variance" dense<0.00354609918> : tensor<2048xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1129__m.layer-155.kernel" dense<0.00353356893> : tensor<1x1x2048x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1130__m.layer-155.bias" dense<0.00352112669> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1136__m.layer-156.gamma" dense<0.003508772> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1137__m.layer-156.beta" dense<0.00349650346> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1138__m.layer-156.moving_mean" dense<0.00348432059> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1139__m.layer-156.moving_variance" dense<0.00347222225> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1148__m.layer-158.kernel" dense<0.00346020772> : tensor<3x3x512x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1149__m.layer-158.bias" dense<0.00344827585> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1155__m.layer-159.gamma" dense<0.00343642617> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1156__m.layer-159.beta" dense<0.00342465751> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1157__m.layer-159.moving_mean" dense<0.00341296918> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1158__m.layer-159.moving_variance" dense<0.00340136047> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1167__m.layer-161.kernel" dense<0.00338983047> : tensor<1x1x512x2048xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1168__m.layer-161.bias" dense<0.00337837846> : tensor<2048xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1174__m.layer-162.gamma" dense<0.00336700329> : tensor<2048xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1175__m.layer-162.beta" dense<0.00335570471> : tensor<2048xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1176__m.layer-162.moving_mean" dense<0.00334448158> : tensor<2048xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1177__m.layer-162.moving_variance" dense<0.00333333341> : tensor<2048xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1190__m.layer-165.kernel" dense<0.00332225906> : tensor<1x1x2048x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1191__m.layer-165.bias" dense<0.00331125828> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1197__m.layer-166.gamma" dense<0.00330033014> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1198__m.layer-166.beta" dense<0.00328947371> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1199__m.layer-166.moving_mean" dense<0.00327868853> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1200__m.layer-166.moving_variance" dense<0.00326797389> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1209__m.layer-168.kernel" dense<0.00325732888> : tensor<3x3x512x512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1210__m.layer-168.bias" dense<0.00324675324> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1216__m.layer-169.gamma" dense<0.00323624606> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1217__m.layer-169.beta" dense<0.0032258064> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1218__m.layer-169.moving_mean" dense<0.00321543403> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1219__m.layer-169.moving_variance" dense<0.00320512825> : tensor<512xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1228__m.layer-171.kernel" dense<0.00319488812> : tensor<1x1x512x2048xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1229__m.layer-171.bias" dense<0.00318471342> : tensor<2048xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1235__m.layer-172.gamma" dense<0.00317460322> : tensor<2048xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1236__m.layer-172.beta" dense<0.00316455704> : tensor<2048xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1237__m.layer-172.moving_mean" dense<0.00315457419> : tensor<2048xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1238__m.layer-172.moving_variance" dense<0.00314465398> : tensor<2048xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1255__m.layer-176.kernel" dense<0.00313479616> : tensor<2048x1000xf32> attributes {noinline, sym_visibility = "private"}
-  flow.variable @"__iree_flow___sm_node1256__m.layer-176.bias" dense<3.125000e-03> : tensor<1000xf32> attributes {noinline, sym_visibility = "private"}
+  util.global private @"__iree_flow___sm_node188__m.layer-2.kernel" {noinline} = dense<1.000000e+00> : tensor<7x7x3x64xf32>
+  util.global private @"__iree_flow___sm_node189__m.layer-2.bias" {noinline} = dense<5.000000e-01> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node195__m.layer-3.gamma" {noinline} = dense<0.333333343> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node196__m.layer-3.beta" {noinline} = dense<2.500000e-01> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node197__m.layer-3.moving_mean" {noinline} = dense<2.000000e-01> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node198__m.layer-3.moving_variance" {noinline} = dense<0.166666672> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node215__m.layer-7.kernel" {noinline} = dense<0.142857149> : tensor<1x1x64x64xf32>
+  util.global private @"__iree_flow___sm_node216__m.layer-7.bias" {noinline} = dense<1.250000e-01> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node222__m.layer-8.gamma" {noinline} = dense<0.111111112> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node223__m.layer-8.beta" {noinline} = dense<1.000000e-01> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node224__m.layer-8.moving_mean" {noinline} = dense<0.0909090936> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node225__m.layer-8.moving_variance" {noinline} = dense<0.0833333358> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node234__m.layer-10.kernel" {noinline} = dense<0.0769230798> : tensor<3x3x64x64xf32>
+  util.global private @"__iree_flow___sm_node235__m.layer-10.bias" {noinline} = dense<0.0714285746> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node241__m.layer-11.gamma" {noinline} = dense<0.0666666701> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node242__m.layer-11.beta" {noinline} = dense<6.250000e-02> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node243__m.layer-11.moving_mean" {noinline} = dense<0.0588235296> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node244__m.layer-11.moving_variance" {noinline} = dense<0.055555556> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node253__m.layer-13.kernel" {noinline} = dense<0.0526315793> : tensor<1x1x64x256xf32>
+  util.global private @"__iree_flow___sm_node254__m.layer-13.bias" {noinline} = dense<5.000000e-02> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node259__m.layer-14.kernel" {noinline} = dense<0.0476190485> : tensor<1x1x64x256xf32>
+  util.global private @"__iree_flow___sm_node260__m.layer-14.bias" {noinline} = dense<0.0454545468> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node266__m.layer-15.gamma" {noinline} = dense<0.0434782617> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node267__m.layer-15.beta" {noinline} = dense<0.0416666679> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node268__m.layer-15.moving_mean" {noinline} = dense<4.000000e-02> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node269__m.layer-15.moving_variance" {noinline} = dense<0.0384615399> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node275__m.layer-16.gamma" {noinline} = dense<0.0370370373> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node276__m.layer-16.beta" {noinline} = dense<0.0357142873> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node277__m.layer-16.moving_mean" {noinline} = dense<0.0344827585> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node278__m.layer-16.moving_variance" {noinline} = dense<0.0333333351> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node291__m.layer-19.kernel" {noinline} = dense<0.0322580636> : tensor<1x1x256x64xf32>
+  util.global private @"__iree_flow___sm_node292__m.layer-19.bias" {noinline} = dense<3.125000e-02> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node298__m.layer-20.gamma" {noinline} = dense<0.0303030312> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node299__m.layer-20.beta" {noinline} = dense<0.0294117648> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node300__m.layer-20.moving_mean" {noinline} = dense<0.0285714287> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node301__m.layer-20.moving_variance" {noinline} = dense<0.027777778> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node310__m.layer-22.kernel" {noinline} = dense<0.0270270277> : tensor<3x3x64x64xf32>
+  util.global private @"__iree_flow___sm_node311__m.layer-22.bias" {noinline} = dense<0.0263157897> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node317__m.layer-23.gamma" {noinline} = dense<0.025641026> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node318__m.layer-23.beta" {noinline} = dense<2.500000e-02> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node319__m.layer-23.moving_mean" {noinline} = dense<0.024390243> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node320__m.layer-23.moving_variance" {noinline} = dense<0.0238095243> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node329__m.layer-25.kernel" {noinline} = dense<0.0232558139> : tensor<1x1x64x256xf32>
+  util.global private @"__iree_flow___sm_node330__m.layer-25.bias" {noinline} = dense<0.0227272734> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node336__m.layer-26.gamma" {noinline} = dense<0.0222222228> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node337__m.layer-26.beta" {noinline} = dense<0.0217391308> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node338__m.layer-26.moving_mean" {noinline} = dense<0.0212765951> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node339__m.layer-26.moving_variance" {noinline} = dense<0.020833334> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node352__m.layer-29.kernel" {noinline} = dense<0.0204081628> : tensor<1x1x256x64xf32>
+  util.global private @"__iree_flow___sm_node353__m.layer-29.bias" {noinline} = dense<2.000000e-02> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node359__m.layer-30.gamma" {noinline} = dense<0.0196078438> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node360__m.layer-30.beta" {noinline} = dense<0.0192307699> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node361__m.layer-30.moving_mean" {noinline} = dense<0.0188679248> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node362__m.layer-30.moving_variance" {noinline} = dense<0.0185185187> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node371__m.layer-32.kernel" {noinline} = dense<0.0181818176> : tensor<3x3x64x64xf32>
+  util.global private @"__iree_flow___sm_node372__m.layer-32.bias" {noinline} = dense<0.0178571437> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node378__m.layer-33.gamma" {noinline} = dense<0.0175438598> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node379__m.layer-33.beta" {noinline} = dense<0.0172413792> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node380__m.layer-33.moving_mean" {noinline} = dense<0.0169491526> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node381__m.layer-33.moving_variance" {noinline} = dense<0.0166666675> : tensor<64xf32>
+  util.global private @"__iree_flow___sm_node390__m.layer-35.kernel" {noinline} = dense<0.0163934417> : tensor<1x1x64x256xf32>
+  util.global private @"__iree_flow___sm_node391__m.layer-35.bias" {noinline} = dense<0.0161290318> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node397__m.layer-36.gamma" {noinline} = dense<0.0158730168> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node398__m.layer-36.beta" {noinline} = dense<1.562500e-02> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node399__m.layer-36.moving_mean" {noinline} = dense<0.0153846154> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node400__m.layer-36.moving_variance" {noinline} = dense<0.0151515156> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node413__m.layer-39.kernel" {noinline} = dense<0.0149253728> : tensor<1x1x256x128xf32>
+  util.global private @"__iree_flow___sm_node414__m.layer-39.bias" {noinline} = dense<0.0147058824> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node420__m.layer-40.gamma" {noinline} = dense<0.0144927539> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node421__m.layer-40.beta" {noinline} = dense<0.0142857144> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node422__m.layer-40.moving_mean" {noinline} = dense<0.0140845068> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node423__m.layer-40.moving_variance" {noinline} = dense<0.013888889> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node432__m.layer-42.kernel" {noinline} = dense<0.01369863> : tensor<3x3x128x128xf32>
+  util.global private @"__iree_flow___sm_node433__m.layer-42.bias" {noinline} = dense<0.0135135138> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node439__m.layer-43.gamma" {noinline} = dense<0.0133333337> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node440__m.layer-43.beta" {noinline} = dense<0.0131578948> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node441__m.layer-43.moving_mean" {noinline} = dense<0.012987013> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node442__m.layer-43.moving_variance" {noinline} = dense<0.012820513> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node451__m.layer-45.kernel" {noinline} = dense<0.0126582282> : tensor<1x1x256x512xf32>
+  util.global private @"__iree_flow___sm_node452__m.layer-45.bias" {noinline} = dense<1.250000e-02> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node457__m.layer-46.kernel" {noinline} = dense<0.0123456791> : tensor<1x1x128x512xf32>
+  util.global private @"__iree_flow___sm_node458__m.layer-46.bias" {noinline} = dense<0.0121951215> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node464__m.layer-47.gamma" {noinline} = dense<0.0120481923> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node465__m.layer-47.beta" {noinline} = dense<0.0119047621> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node466__m.layer-47.moving_mean" {noinline} = dense<0.0117647061> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node467__m.layer-47.moving_variance" {noinline} = dense<0.0116279069> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node473__m.layer-48.gamma" {noinline} = dense<0.0114942528> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node474__m.layer-48.beta" {noinline} = dense<0.0113636367> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node475__m.layer-48.moving_mean" {noinline} = dense<0.0112359552> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node476__m.layer-48.moving_variance" {noinline} = dense<0.0111111114> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node489__m.layer-51.kernel" {noinline} = dense<0.0109890113> : tensor<1x1x512x128xf32>
+  util.global private @"__iree_flow___sm_node490__m.layer-51.bias" {noinline} = dense<0.0108695654> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node496__m.layer-52.gamma" {noinline} = dense<0.0107526882> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node497__m.layer-52.beta" {noinline} = dense<0.0106382975> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node498__m.layer-52.moving_mean" {noinline} = dense<0.0105263162> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node499__m.layer-52.moving_variance" {noinline} = dense<0.010416667> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node508__m.layer-54.kernel" {noinline} = dense<0.010309278> : tensor<3x3x128x128xf32>
+  util.global private @"__iree_flow___sm_node509__m.layer-54.bias" {noinline} = dense<0.0102040814> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node515__m.layer-55.gamma" {noinline} = dense<0.0101010101> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node516__m.layer-55.beta" {noinline} = dense<0.00999999977> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node517__m.layer-55.moving_mean" {noinline} = dense<9.900990e-03> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node518__m.layer-55.moving_variance" {noinline} = dense<0.00980392192> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node527__m.layer-57.kernel" {noinline} = dense<0.00970873795> : tensor<1x1x128x512xf32>
+  util.global private @"__iree_flow___sm_node528__m.layer-57.bias" {noinline} = dense<0.00961538497> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node534__m.layer-58.gamma" {noinline} = dense<9.523810e-03> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node535__m.layer-58.beta" {noinline} = dense<0.0094339624> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node536__m.layer-58.moving_mean" {noinline} = dense<0.00934579409> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node537__m.layer-58.moving_variance" {noinline} = dense<0.00925925932> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node550__m.layer-61.kernel" {noinline} = dense<0.00917431153> : tensor<1x1x512x128xf32>
+  util.global private @"__iree_flow___sm_node551__m.layer-61.bias" {noinline} = dense<0.0090909088> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node557__m.layer-62.gamma" {noinline} = dense<0.00900900922> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node558__m.layer-62.beta" {noinline} = dense<0.00892857183> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node559__m.layer-62.moving_mean" {noinline} = dense<0.00884955748> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node560__m.layer-62.moving_variance" {noinline} = dense<0.00877192988> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node569__m.layer-64.kernel" {noinline} = dense<0.00869565178> : tensor<3x3x128x128xf32>
+  util.global private @"__iree_flow___sm_node570__m.layer-64.bias" {noinline} = dense<8.620690e-03> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node576__m.layer-65.gamma" {noinline} = dense<0.00854700897> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node577__m.layer-65.beta" {noinline} = dense<0.00847457629> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node578__m.layer-65.moving_mean" {noinline} = dense<0.00840336177> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node579__m.layer-65.moving_variance" {noinline} = dense<0.00833333377> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node588__m.layer-67.kernel" {noinline} = dense<0.00826446246> : tensor<1x1x128x512xf32>
+  util.global private @"__iree_flow___sm_node589__m.layer-67.bias" {noinline} = dense<0.00819672085> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node595__m.layer-68.gamma" {noinline} = dense<0.008130081> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node596__m.layer-68.beta" {noinline} = dense<0.00806451589> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node597__m.layer-68.moving_mean" {noinline} = dense<8.000000e-03> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node598__m.layer-68.moving_variance" {noinline} = dense<0.00793650839> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node611__m.layer-71.kernel" {noinline} = dense<0.00787401571> : tensor<1x1x512x128xf32>
+  util.global private @"__iree_flow___sm_node612__m.layer-71.bias" {noinline} = dense<7.812500e-03> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node618__m.layer-72.gamma" {noinline} = dense<0.00775193795> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node619__m.layer-72.beta" {noinline} = dense<0.0076923077> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node620__m.layer-72.moving_mean" {noinline} = dense<0.00763358781> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node621__m.layer-72.moving_variance" {noinline} = dense<0.0075757578> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node630__m.layer-74.kernel" {noinline} = dense<0.00751879718> : tensor<3x3x128x128xf32>
+  util.global private @"__iree_flow___sm_node631__m.layer-74.bias" {noinline} = dense<0.00746268639> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node637__m.layer-75.gamma" {noinline} = dense<0.00740740728> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node638__m.layer-75.beta" {noinline} = dense<0.0073529412> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node639__m.layer-75.moving_mean" {noinline} = dense<7.299270e-03> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node640__m.layer-75.moving_variance" {noinline} = dense<0.00724637694> : tensor<128xf32>
+  util.global private @"__iree_flow___sm_node649__m.layer-77.kernel" {noinline} = dense<0.00719424477> : tensor<1x1x128x512xf32>
+  util.global private @"__iree_flow___sm_node650__m.layer-77.bias" {noinline} = dense<0.00714285718> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node656__m.layer-78.gamma" {noinline} = dense<0.00709219835> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node657__m.layer-78.beta" {noinline} = dense<0.00704225338> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node658__m.layer-78.moving_mean" {noinline} = dense<0.00699300691> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node659__m.layer-78.moving_variance" {noinline} = dense<0.0069444445> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node672__m.layer-81.kernel" {noinline} = dense<0.0068965517> : tensor<1x1x512x256xf32>
+  util.global private @"__iree_flow___sm_node673__m.layer-81.bias" {noinline} = dense<0.00684931502> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node679__m.layer-82.gamma" {noinline} = dense<0.00680272094> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node680__m.layer-82.beta" {noinline} = dense<0.00675675692> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node681__m.layer-82.moving_mean" {noinline} = dense<0.00671140943> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node682__m.layer-82.moving_variance" {noinline} = dense<0.00666666683> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node691__m.layer-84.kernel" {noinline} = dense<0.00662251655> : tensor<3x3x256x256xf32>
+  util.global private @"__iree_flow___sm_node692__m.layer-84.bias" {noinline} = dense<0.00657894742> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node698__m.layer-85.gamma" {noinline} = dense<0.00653594779> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node699__m.layer-85.beta" {noinline} = dense<0.00649350649> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node700__m.layer-85.moving_mean" {noinline} = dense<0.0064516128> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node701__m.layer-85.moving_variance" {noinline} = dense<0.00641025649> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node710__m.layer-87.kernel" {noinline} = dense<0.00636942684> : tensor<1x1x512x1024xf32>
+  util.global private @"__iree_flow___sm_node711__m.layer-87.bias" {noinline} = dense<0.00632911408> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node716__m.layer-88.kernel" {noinline} = dense<0.00628930796> : tensor<1x1x256x1024xf32>
+  util.global private @"__iree_flow___sm_node717__m.layer-88.bias" {noinline} = dense<6.250000e-03> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node723__m.layer-89.gamma" {noinline} = dense<0.00621118024> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node724__m.layer-89.beta" {noinline} = dense<0.00617283955> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node725__m.layer-89.moving_mean" {noinline} = dense<0.00613496918> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node726__m.layer-89.moving_variance" {noinline} = dense<0.00609756075> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node732__m.layer-90.gamma" {noinline} = dense<0.00606060587> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node733__m.layer-90.beta" {noinline} = dense<0.00602409616> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node734__m.layer-90.moving_mean" {noinline} = dense<0.00598802418> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node735__m.layer-90.moving_variance" {noinline} = dense<0.00595238106> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node748__m.layer-93.kernel" {noinline} = dense<5.917160e-03> : tensor<1x1x1024x256xf32>
+  util.global private @"__iree_flow___sm_node749__m.layer-93.bias" {noinline} = dense<0.00588235306> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node755__m.layer-94.gamma" {noinline} = dense<0.00584795326> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node756__m.layer-94.beta" {noinline} = dense<0.00581395347> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node757__m.layer-94.moving_mean" {noinline} = dense<0.00578034669> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node758__m.layer-94.moving_variance" {noinline} = dense<0.00574712642> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node767__m.layer-96.kernel" {noinline} = dense<0.00571428565> : tensor<3x3x256x256xf32>
+  util.global private @"__iree_flow___sm_node768__m.layer-96.bias" {noinline} = dense<0.00568181835> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node774__m.layer-97.gamma" {noinline} = dense<0.00564971752> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node775__m.layer-97.beta" {noinline} = dense<0.00561797759> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node776__m.layer-97.moving_mean" {noinline} = dense<0.00558659201> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node777__m.layer-97.moving_variance" {noinline} = dense<0.00555555569> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node786__m.layer-99.kernel" {noinline} = dense<0.00552486209> : tensor<1x1x256x1024xf32>
+  util.global private @"__iree_flow___sm_node787__m.layer-99.bias" {noinline} = dense<0.00549450563> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node793__m.layer-100.gamma" {noinline} = dense<0.00546448072> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node794__m.layer-100.beta" {noinline} = dense<0.00543478271> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node795__m.layer-100.moving_mean" {noinline} = dense<0.00540540554> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node796__m.layer-100.moving_variance" {noinline} = dense<0.00537634408> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node809__m.layer-103.kernel" {noinline} = dense<0.00534759369> : tensor<1x1x1024x256xf32>
+  util.global private @"__iree_flow___sm_node810__m.layer-103.bias" {noinline} = dense<0.00531914877> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node816__m.layer-104.gamma" {noinline} = dense<0.00529100513> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node817__m.layer-104.beta" {noinline} = dense<0.00526315812> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node818__m.layer-104.moving_mean" {noinline} = dense<0.00523560215> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node819__m.layer-104.moving_variance" {noinline} = dense<0.00520833349> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node828__m.layer-106.kernel" {noinline} = dense<0.00518134702> : tensor<3x3x256x256xf32>
+  util.global private @"__iree_flow___sm_node829__m.layer-106.bias" {noinline} = dense<0.00515463902> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node835__m.layer-107.gamma" {noinline} = dense<0.00512820529> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node836__m.layer-107.beta" {noinline} = dense<0.00510204071> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node837__m.layer-107.moving_mean" {noinline} = dense<0.00507614203> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node838__m.layer-107.moving_variance" {noinline} = dense<0.00505050505> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node847__m.layer-109.kernel" {noinline} = dense<0.00502512557> : tensor<1x1x256x1024xf32>
+  util.global private @"__iree_flow___sm_node848__m.layer-109.bias" {noinline} = dense<5.000000e-03> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node854__m.layer-110.gamma" {noinline} = dense<0.00497512426> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node855__m.layer-110.beta" {noinline} = dense<0.00495049497> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node856__m.layer-110.moving_mean" {noinline} = dense<0.00492610829> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node857__m.layer-110.moving_variance" {noinline} = dense<0.00490196096> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node870__m.layer-113.kernel" {noinline} = dense<0.00487804879> : tensor<1x1x1024x256xf32>
+  util.global private @"__iree_flow___sm_node871__m.layer-113.bias" {noinline} = dense<0.00485436898> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node877__m.layer-114.gamma" {noinline} = dense<0.00483091781> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node878__m.layer-114.beta" {noinline} = dense<0.00480769249> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node879__m.layer-114.moving_mean" {noinline} = dense<0.00478468882> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node880__m.layer-114.moving_variance" {noinline} = dense<0.00476190494> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node889__m.layer-116.kernel" {noinline} = dense<0.00473933667> : tensor<3x3x256x256xf32>
+  util.global private @"__iree_flow___sm_node890__m.layer-116.bias" {noinline} = dense<0.0047169812> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node896__m.layer-117.gamma" {noinline} = dense<0.00469483575> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node897__m.layer-117.beta" {noinline} = dense<0.00467289705> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node898__m.layer-117.moving_mean" {noinline} = dense<0.00465116277> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node899__m.layer-117.moving_variance" {noinline} = dense<0.00462962966> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node908__m.layer-119.kernel" {noinline} = dense<0.00460829493> : tensor<1x1x256x1024xf32>
+  util.global private @"__iree_flow___sm_node909__m.layer-119.bias" {noinline} = dense<0.00458715577> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node915__m.layer-120.gamma" {noinline} = dense<4.566210e-03> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node916__m.layer-120.beta" {noinline} = dense<0.0045454544> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node917__m.layer-120.moving_mean" {noinline} = dense<0.00452488707> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node918__m.layer-120.moving_variance" {noinline} = dense<0.00450450461> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node931__m.layer-123.kernel" {noinline} = dense<0.00448430516> : tensor<1x1x1024x256xf32>
+  util.global private @"__iree_flow___sm_node932__m.layer-123.bias" {noinline} = dense<0.00446428591> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node938__m.layer-124.gamma" {noinline} = dense<0.00444444455> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node939__m.layer-124.beta" {noinline} = dense<0.00442477874> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node940__m.layer-124.moving_mean" {noinline} = dense<0.00440528616> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node941__m.layer-124.moving_variance" {noinline} = dense<0.00438596494> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node950__m.layer-126.kernel" {noinline} = dense<0.0043668123> : tensor<3x3x256x256xf32>
+  util.global private @"__iree_flow___sm_node951__m.layer-126.bias" {noinline} = dense<0.00434782589> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node957__m.layer-127.gamma" {noinline} = dense<0.00432900432> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node958__m.layer-127.beta" {noinline} = dense<0.00431034481> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node959__m.layer-127.moving_mean" {noinline} = dense<0.00429184549> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node960__m.layer-127.moving_variance" {noinline} = dense<0.00427350448> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node969__m.layer-129.kernel" {noinline} = dense<0.00425531901> : tensor<1x1x256x1024xf32>
+  util.global private @"__iree_flow___sm_node970__m.layer-129.bias" {noinline} = dense<0.00423728814> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node976__m.layer-130.gamma" {noinline} = dense<0.00421940908> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node977__m.layer-130.beta" {noinline} = dense<0.00420168089> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node978__m.layer-130.moving_mean" {noinline} = dense<0.00418410031> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node979__m.layer-130.moving_variance" {noinline} = dense<0.00416666688> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node992__m.layer-133.kernel" {noinline} = dense<0.00414937781> : tensor<1x1x1024x256xf32>
+  util.global private @"__iree_flow___sm_node993__m.layer-133.bias" {noinline} = dense<0.00413223123> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node999__m.layer-134.gamma" {noinline} = dense<0.00411522621> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node1000__m.layer-134.beta" {noinline} = dense<0.00409836043> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node1001__m.layer-134.moving_mean" {noinline} = dense<0.00408163248> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node1002__m.layer-134.moving_variance" {noinline} = dense<0.0040650405> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node1011__m.layer-136.kernel" {noinline} = dense<0.0040485831> : tensor<3x3x256x256xf32>
+  util.global private @"__iree_flow___sm_node1012__m.layer-136.bias" {noinline} = dense<0.00403225794> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node1018__m.layer-137.gamma" {noinline} = dense<0.00401606411> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node1019__m.layer-137.beta" {noinline} = dense<4.000000e-03> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node1020__m.layer-137.moving_mean" {noinline} = dense<0.00398406386> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node1021__m.layer-137.moving_variance" {noinline} = dense<0.0039682542> : tensor<256xf32>
+  util.global private @"__iree_flow___sm_node1030__m.layer-139.kernel" {noinline} = dense<0.00395256933> : tensor<1x1x256x1024xf32>
+  util.global private @"__iree_flow___sm_node1031__m.layer-139.bias" {noinline} = dense<0.00393700786> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node1037__m.layer-140.gamma" {noinline} = dense<0.00392156886> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node1038__m.layer-140.beta" {noinline} = dense<3.906250e-03> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node1039__m.layer-140.moving_mean" {noinline} = dense<0.00389105058> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node1040__m.layer-140.moving_variance" {noinline} = dense<0.00387596898> : tensor<1024xf32>
+  util.global private @"__iree_flow___sm_node1053__m.layer-143.kernel" {noinline} = dense<0.00386100379> : tensor<1x1x1024x512xf32>
+  util.global private @"__iree_flow___sm_node1054__m.layer-143.bias" {noinline} = dense<0.00384615385> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1060__m.layer-144.gamma" {noinline} = dense<0.00383141753> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1061__m.layer-144.beta" {noinline} = dense<0.00381679391> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1062__m.layer-144.moving_mean" {noinline} = dense<0.00380228134> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1063__m.layer-144.moving_variance" {noinline} = dense<0.0037878789> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1072__m.layer-146.kernel" {noinline} = dense<0.00377358496> : tensor<3x3x512x512xf32>
+  util.global private @"__iree_flow___sm_node1073__m.layer-146.bias" {noinline} = dense<0.00375939859> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1079__m.layer-147.gamma" {noinline} = dense<0.00374531839> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1080__m.layer-147.beta" {noinline} = dense<0.0037313432> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1081__m.layer-147.moving_mean" {noinline} = dense<0.00371747208> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1082__m.layer-147.moving_variance" {noinline} = dense<0.00370370364> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1091__m.layer-149.kernel" {noinline} = dense<0.00369003695> : tensor<1x1x1024x2048xf32>
+  util.global private @"__iree_flow___sm_node1092__m.layer-149.bias" {noinline} = dense<0.0036764706> : tensor<2048xf32>
+  util.global private @"__iree_flow___sm_node1097__m.layer-150.kernel" {noinline} = dense<0.00366300368> : tensor<1x1x512x2048xf32>
+  util.global private @"__iree_flow___sm_node1098__m.layer-150.bias" {noinline} = dense<0.00364963501> : tensor<2048xf32>
+  util.global private @"__iree_flow___sm_node1104__m.layer-151.gamma" {noinline} = dense<0.00363636366> : tensor<2048xf32>
+  util.global private @"__iree_flow___sm_node1105__m.layer-151.beta" {noinline} = dense<0.00362318847> : tensor<2048xf32>
+  util.global private @"__iree_flow___sm_node1106__m.layer-151.moving_mean" {noinline} = dense<0.00361010828> : tensor<2048xf32>
+  util.global private @"__iree_flow___sm_node1107__m.layer-151.moving_variance" {noinline} = dense<0.00359712238> : tensor<2048xf32>
+  util.global private @"__iree_flow___sm_node1113__m.layer-152.gamma" {noinline} = dense<0.00358422939> : tensor<2048xf32>
+  util.global private @"__iree_flow___sm_node1114__m.layer-152.beta" {noinline} = dense<0.00357142859> : tensor<2048xf32>
+  util.global private @"__iree_flow___sm_node1115__m.layer-152.moving_mean" {noinline} = dense<0.00355871883> : tensor<2048xf32>
+  util.global private @"__iree_flow___sm_node1116__m.layer-152.moving_variance" {noinline} = dense<0.00354609918> : tensor<2048xf32>
+  util.global private @"__iree_flow___sm_node1129__m.layer-155.kernel" {noinline} = dense<0.00353356893> : tensor<1x1x2048x512xf32>
+  util.global private @"__iree_flow___sm_node1130__m.layer-155.bias" {noinline} = dense<0.00352112669> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1136__m.layer-156.gamma" {noinline} = dense<0.003508772> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1137__m.layer-156.beta" {noinline} = dense<0.00349650346> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1138__m.layer-156.moving_mean" {noinline} = dense<0.00348432059> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1139__m.layer-156.moving_variance" {noinline} = dense<0.00347222225> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1148__m.layer-158.kernel" {noinline} = dense<0.00346020772> : tensor<3x3x512x512xf32>
+  util.global private @"__iree_flow___sm_node1149__m.layer-158.bias" {noinline} = dense<0.00344827585> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1155__m.layer-159.gamma" {noinline} = dense<0.00343642617> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1156__m.layer-159.beta" {noinline} = dense<0.00342465751> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1157__m.layer-159.moving_mean" {noinline} = dense<0.00341296918> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1158__m.layer-159.moving_variance" {noinline} = dense<0.00340136047> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1167__m.layer-161.kernel" {noinline} = dense<0.00338983047> : tensor<1x1x512x2048xf32>
+  util.global private @"__iree_flow___sm_node1168__m.layer-161.bias" {noinline} = dense<0.00337837846> : tensor<2048xf32>
+  util.global private @"__iree_flow___sm_node1174__m.layer-162.gamma" {noinline} = dense<0.00336700329> : tensor<2048xf32>
+  util.global private @"__iree_flow___sm_node1175__m.layer-162.beta" {noinline} = dense<0.00335570471> : tensor<2048xf32>
+  util.global private @"__iree_flow___sm_node1176__m.layer-162.moving_mean" {noinline} = dense<0.00334448158> : tensor<2048xf32>
+  util.global private @"__iree_flow___sm_node1177__m.layer-162.moving_variance" {noinline} = dense<0.00333333341> : tensor<2048xf32>
+  util.global private @"__iree_flow___sm_node1190__m.layer-165.kernel" {noinline} = dense<0.00332225906> : tensor<1x1x2048x512xf32>
+  util.global private @"__iree_flow___sm_node1191__m.layer-165.bias" {noinline} = dense<0.00331125828> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1197__m.layer-166.gamma" {noinline} = dense<0.00330033014> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1198__m.layer-166.beta" {noinline} = dense<0.00328947371> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1199__m.layer-166.moving_mean" {noinline} = dense<0.00327868853> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1200__m.layer-166.moving_variance" {noinline} = dense<0.00326797389> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1209__m.layer-168.kernel" {noinline} = dense<0.00325732888> : tensor<3x3x512x512xf32>
+  util.global private @"__iree_flow___sm_node1210__m.layer-168.bias" {noinline} = dense<0.00324675324> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1216__m.layer-169.gamma" {noinline} = dense<0.00323624606> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1217__m.layer-169.beta" {noinline} = dense<0.0032258064> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1218__m.layer-169.moving_mean" {noinline} = dense<0.00321543403> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1219__m.layer-169.moving_variance" {noinline} = dense<0.00320512825> : tensor<512xf32>
+  util.global private @"__iree_flow___sm_node1228__m.layer-171.kernel" {noinline} = dense<0.00319488812> : tensor<1x1x512x2048xf32>
+  util.global private @"__iree_flow___sm_node1229__m.layer-171.bias" {noinline} = dense<0.00318471342> : tensor<2048xf32>
+  util.global private @"__iree_flow___sm_node1235__m.layer-172.gamma" {noinline} = dense<0.00317460322> : tensor<2048xf32>
+  util.global private @"__iree_flow___sm_node1236__m.layer-172.beta" {noinline} = dense<0.00316455704> : tensor<2048xf32>
+  util.global private @"__iree_flow___sm_node1237__m.layer-172.moving_mean" {noinline} = dense<0.00315457419> : tensor<2048xf32>
+  util.global private @"__iree_flow___sm_node1238__m.layer-172.moving_variance" {noinline} = dense<0.00314465398> : tensor<2048xf32>
+  util.global private @"__iree_flow___sm_node1255__m.layer-176.kernel" {noinline} = dense<0.00313479616> : tensor<2048x1000xf32>
+  util.global private @"__iree_flow___sm_node1256__m.layer-176.bias" {noinline} = dense<3.125000e-03> : tensor<1000xf32>
   // CHECK-LABEL: EXEC @predict
   func @predict(%arg0: tensor<1x224x224x3xf32>) -> tensor<1x1000xf32> attributes {iree.module.export, iree.reflection = {abi = "sip", abiv = 1 : i32, sip = "I8!S5!k0_0R3!_0"}} {
-    %0 = flow.variable.address @"__iree_flow___sm_node188__m.layer-2.kernel" : !util.ptr<tensor<7x7x3x64xf32>>
-    %1 = flow.variable.address @"__iree_flow___sm_node189__m.layer-2.bias" : !util.ptr<tensor<64xf32>>
-    %2 = flow.variable.address @"__iree_flow___sm_node195__m.layer-3.gamma" : !util.ptr<tensor<64xf32>>
-    %3 = flow.variable.address @"__iree_flow___sm_node196__m.layer-3.beta" : !util.ptr<tensor<64xf32>>
-    %4 = flow.variable.address @"__iree_flow___sm_node197__m.layer-3.moving_mean" : !util.ptr<tensor<64xf32>>
-    %5 = flow.variable.address @"__iree_flow___sm_node198__m.layer-3.moving_variance" : !util.ptr<tensor<64xf32>>
-    %6 = flow.variable.address @"__iree_flow___sm_node215__m.layer-7.kernel" : !util.ptr<tensor<1x1x64x64xf32>>
-    %7 = flow.variable.address @"__iree_flow___sm_node216__m.layer-7.bias" : !util.ptr<tensor<64xf32>>
-    %8 = flow.variable.address @"__iree_flow___sm_node222__m.layer-8.gamma" : !util.ptr<tensor<64xf32>>
-    %9 = flow.variable.address @"__iree_flow___sm_node223__m.layer-8.beta" : !util.ptr<tensor<64xf32>>
-    %10 = flow.variable.address @"__iree_flow___sm_node224__m.layer-8.moving_mean" : !util.ptr<tensor<64xf32>>
-    %11 = flow.variable.address @"__iree_flow___sm_node225__m.layer-8.moving_variance" : !util.ptr<tensor<64xf32>>
-    %12 = flow.variable.address @"__iree_flow___sm_node234__m.layer-10.kernel" : !util.ptr<tensor<3x3x64x64xf32>>
-    %13 = flow.variable.address @"__iree_flow___sm_node235__m.layer-10.bias" : !util.ptr<tensor<64xf32>>
-    %14 = flow.variable.address @"__iree_flow___sm_node241__m.layer-11.gamma" : !util.ptr<tensor<64xf32>>
-    %15 = flow.variable.address @"__iree_flow___sm_node242__m.layer-11.beta" : !util.ptr<tensor<64xf32>>
-    %16 = flow.variable.address @"__iree_flow___sm_node243__m.layer-11.moving_mean" : !util.ptr<tensor<64xf32>>
-    %17 = flow.variable.address @"__iree_flow___sm_node244__m.layer-11.moving_variance" : !util.ptr<tensor<64xf32>>
-    %18 = flow.variable.address @"__iree_flow___sm_node259__m.layer-14.kernel" : !util.ptr<tensor<1x1x64x256xf32>>
-    %19 = flow.variable.address @"__iree_flow___sm_node260__m.layer-14.bias" : !util.ptr<tensor<256xf32>>
-    %20 = flow.variable.address @"__iree_flow___sm_node253__m.layer-13.kernel" : !util.ptr<tensor<1x1x64x256xf32>>
-    %21 = flow.variable.address @"__iree_flow___sm_node254__m.layer-13.bias" : !util.ptr<tensor<256xf32>>
-    %22 = flow.variable.address @"__iree_flow___sm_node266__m.layer-15.gamma" : !util.ptr<tensor<256xf32>>
-    %23 = flow.variable.address @"__iree_flow___sm_node267__m.layer-15.beta" : !util.ptr<tensor<256xf32>>
-    %24 = flow.variable.address @"__iree_flow___sm_node268__m.layer-15.moving_mean" : !util.ptr<tensor<256xf32>>
-    %25 = flow.variable.address @"__iree_flow___sm_node269__m.layer-15.moving_variance" : !util.ptr<tensor<256xf32>>
-    %26 = flow.variable.address @"__iree_flow___sm_node275__m.layer-16.gamma" : !util.ptr<tensor<256xf32>>
-    %27 = flow.variable.address @"__iree_flow___sm_node276__m.layer-16.beta" : !util.ptr<tensor<256xf32>>
-    %28 = flow.variable.address @"__iree_flow___sm_node277__m.layer-16.moving_mean" : !util.ptr<tensor<256xf32>>
-    %29 = flow.variable.address @"__iree_flow___sm_node278__m.layer-16.moving_variance" : !util.ptr<tensor<256xf32>>
-    %30 = flow.variable.address @"__iree_flow___sm_node291__m.layer-19.kernel" : !util.ptr<tensor<1x1x256x64xf32>>
-    %31 = flow.variable.address @"__iree_flow___sm_node292__m.layer-19.bias" : !util.ptr<tensor<64xf32>>
-    %32 = flow.variable.address @"__iree_flow___sm_node298__m.layer-20.gamma" : !util.ptr<tensor<64xf32>>
-    %33 = flow.variable.address @"__iree_flow___sm_node299__m.layer-20.beta" : !util.ptr<tensor<64xf32>>
-    %34 = flow.variable.address @"__iree_flow___sm_node300__m.layer-20.moving_mean" : !util.ptr<tensor<64xf32>>
-    %35 = flow.variable.address @"__iree_flow___sm_node301__m.layer-20.moving_variance" : !util.ptr<tensor<64xf32>>
-    %36 = flow.variable.address @"__iree_flow___sm_node310__m.layer-22.kernel" : !util.ptr<tensor<3x3x64x64xf32>>
-    %37 = flow.variable.address @"__iree_flow___sm_node311__m.layer-22.bias" : !util.ptr<tensor<64xf32>>
-    %38 = flow.variable.address @"__iree_flow___sm_node317__m.layer-23.gamma" : !util.ptr<tensor<64xf32>>
-    %39 = flow.variable.address @"__iree_flow___sm_node318__m.layer-23.beta" : !util.ptr<tensor<64xf32>>
-    %40 = flow.variable.address @"__iree_flow___sm_node319__m.layer-23.moving_mean" : !util.ptr<tensor<64xf32>>
-    %41 = flow.variable.address @"__iree_flow___sm_node320__m.layer-23.moving_variance" : !util.ptr<tensor<64xf32>>
-    %42 = flow.variable.address @"__iree_flow___sm_node329__m.layer-25.kernel" : !util.ptr<tensor<1x1x64x256xf32>>
-    %43 = flow.variable.address @"__iree_flow___sm_node330__m.layer-25.bias" : !util.ptr<tensor<256xf32>>
-    %44 = flow.variable.address @"__iree_flow___sm_node336__m.layer-26.gamma" : !util.ptr<tensor<256xf32>>
-    %45 = flow.variable.address @"__iree_flow___sm_node337__m.layer-26.beta" : !util.ptr<tensor<256xf32>>
-    %46 = flow.variable.address @"__iree_flow___sm_node338__m.layer-26.moving_mean" : !util.ptr<tensor<256xf32>>
-    %47 = flow.variable.address @"__iree_flow___sm_node339__m.layer-26.moving_variance" : !util.ptr<tensor<256xf32>>
-    %48 = flow.variable.address @"__iree_flow___sm_node352__m.layer-29.kernel" : !util.ptr<tensor<1x1x256x64xf32>>
-    %49 = flow.variable.address @"__iree_flow___sm_node353__m.layer-29.bias" : !util.ptr<tensor<64xf32>>
-    %50 = flow.variable.address @"__iree_flow___sm_node359__m.layer-30.gamma" : !util.ptr<tensor<64xf32>>
-    %51 = flow.variable.address @"__iree_flow___sm_node360__m.layer-30.beta" : !util.ptr<tensor<64xf32>>
-    %52 = flow.variable.address @"__iree_flow___sm_node361__m.layer-30.moving_mean" : !util.ptr<tensor<64xf32>>
-    %53 = flow.variable.address @"__iree_flow___sm_node362__m.layer-30.moving_variance" : !util.ptr<tensor<64xf32>>
-    %54 = flow.variable.address @"__iree_flow___sm_node371__m.layer-32.kernel" : !util.ptr<tensor<3x3x64x64xf32>>
-    %55 = flow.variable.address @"__iree_flow___sm_node372__m.layer-32.bias" : !util.ptr<tensor<64xf32>>
-    %56 = flow.variable.address @"__iree_flow___sm_node378__m.layer-33.gamma" : !util.ptr<tensor<64xf32>>
-    %57 = flow.variable.address @"__iree_flow___sm_node379__m.layer-33.beta" : !util.ptr<tensor<64xf32>>
-    %58 = flow.variable.address @"__iree_flow___sm_node380__m.layer-33.moving_mean" : !util.ptr<tensor<64xf32>>
-    %59 = flow.variable.address @"__iree_flow___sm_node381__m.layer-33.moving_variance" : !util.ptr<tensor<64xf32>>
-    %60 = flow.variable.address @"__iree_flow___sm_node390__m.layer-35.kernel" : !util.ptr<tensor<1x1x64x256xf32>>
-    %61 = flow.variable.address @"__iree_flow___sm_node391__m.layer-35.bias" : !util.ptr<tensor<256xf32>>
-    %62 = flow.variable.address @"__iree_flow___sm_node397__m.layer-36.gamma" : !util.ptr<tensor<256xf32>>
-    %63 = flow.variable.address @"__iree_flow___sm_node398__m.layer-36.beta" : !util.ptr<tensor<256xf32>>
-    %64 = flow.variable.address @"__iree_flow___sm_node399__m.layer-36.moving_mean" : !util.ptr<tensor<256xf32>>
-    %65 = flow.variable.address @"__iree_flow___sm_node400__m.layer-36.moving_variance" : !util.ptr<tensor<256xf32>>
-    %66 = flow.variable.address @"__iree_flow___sm_node413__m.layer-39.kernel" : !util.ptr<tensor<1x1x256x128xf32>>
-    %67 = flow.variable.address @"__iree_flow___sm_node414__m.layer-39.bias" : !util.ptr<tensor<128xf32>>
-    %68 = flow.variable.address @"__iree_flow___sm_node420__m.layer-40.gamma" : !util.ptr<tensor<128xf32>>
-    %69 = flow.variable.address @"__iree_flow___sm_node421__m.layer-40.beta" : !util.ptr<tensor<128xf32>>
-    %70 = flow.variable.address @"__iree_flow___sm_node422__m.layer-40.moving_mean" : !util.ptr<tensor<128xf32>>
-    %71 = flow.variable.address @"__iree_flow___sm_node423__m.layer-40.moving_variance" : !util.ptr<tensor<128xf32>>
-    %72 = flow.variable.address @"__iree_flow___sm_node432__m.layer-42.kernel" : !util.ptr<tensor<3x3x128x128xf32>>
-    %73 = flow.variable.address @"__iree_flow___sm_node433__m.layer-42.bias" : !util.ptr<tensor<128xf32>>
-    %74 = flow.variable.address @"__iree_flow___sm_node439__m.layer-43.gamma" : !util.ptr<tensor<128xf32>>
-    %75 = flow.variable.address @"__iree_flow___sm_node440__m.layer-43.beta" : !util.ptr<tensor<128xf32>>
-    %76 = flow.variable.address @"__iree_flow___sm_node441__m.layer-43.moving_mean" : !util.ptr<tensor<128xf32>>
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-    %251 = flow.variable.address @"__iree_flow___sm_node1021__m.layer-137.moving_variance" : !util.ptr<tensor<256xf32>>
-    %252 = flow.variable.address @"__iree_flow___sm_node1030__m.layer-139.kernel" : !util.ptr<tensor<1x1x256x1024xf32>>
-    %253 = flow.variable.address @"__iree_flow___sm_node1031__m.layer-139.bias" : !util.ptr<tensor<1024xf32>>
-    %254 = flow.variable.address @"__iree_flow___sm_node1037__m.layer-140.gamma" : !util.ptr<tensor<1024xf32>>
-    %255 = flow.variable.address @"__iree_flow___sm_node1038__m.layer-140.beta" : !util.ptr<tensor<1024xf32>>
-    %256 = flow.variable.address @"__iree_flow___sm_node1039__m.layer-140.moving_mean" : !util.ptr<tensor<1024xf32>>
-    %257 = flow.variable.address @"__iree_flow___sm_node1040__m.layer-140.moving_variance" : !util.ptr<tensor<1024xf32>>
-    %258 = flow.variable.address @"__iree_flow___sm_node1053__m.layer-143.kernel" : !util.ptr<tensor<1x1x1024x512xf32>>
-    %259 = flow.variable.address @"__iree_flow___sm_node1054__m.layer-143.bias" : !util.ptr<tensor<512xf32>>
-    %260 = flow.variable.address @"__iree_flow___sm_node1060__m.layer-144.gamma" : !util.ptr<tensor<512xf32>>
-    %261 = flow.variable.address @"__iree_flow___sm_node1061__m.layer-144.beta" : !util.ptr<tensor<512xf32>>
-    %262 = flow.variable.address @"__iree_flow___sm_node1062__m.layer-144.moving_mean" : !util.ptr<tensor<512xf32>>
-    %263 = flow.variable.address @"__iree_flow___sm_node1063__m.layer-144.moving_variance" : !util.ptr<tensor<512xf32>>
-    %264 = flow.variable.address @"__iree_flow___sm_node1072__m.layer-146.kernel" : !util.ptr<tensor<3x3x512x512xf32>>
-    %265 = flow.variable.address @"__iree_flow___sm_node1073__m.layer-146.bias" : !util.ptr<tensor<512xf32>>
-    %266 = flow.variable.address @"__iree_flow___sm_node1079__m.layer-147.gamma" : !util.ptr<tensor<512xf32>>
-    %267 = flow.variable.address @"__iree_flow___sm_node1080__m.layer-147.beta" : !util.ptr<tensor<512xf32>>
-    %268 = flow.variable.address @"__iree_flow___sm_node1081__m.layer-147.moving_mean" : !util.ptr<tensor<512xf32>>
-    %269 = flow.variable.address @"__iree_flow___sm_node1082__m.layer-147.moving_variance" : !util.ptr<tensor<512xf32>>
-    %270 = flow.variable.address @"__iree_flow___sm_node1097__m.layer-150.kernel" : !util.ptr<tensor<1x1x512x2048xf32>>
-    %271 = flow.variable.address @"__iree_flow___sm_node1098__m.layer-150.bias" : !util.ptr<tensor<2048xf32>>
-    %272 = flow.variable.address @"__iree_flow___sm_node1091__m.layer-149.kernel" : !util.ptr<tensor<1x1x1024x2048xf32>>
-    %273 = flow.variable.address @"__iree_flow___sm_node1092__m.layer-149.bias" : !util.ptr<tensor<2048xf32>>
-    %274 = flow.variable.address @"__iree_flow___sm_node1104__m.layer-151.gamma" : !util.ptr<tensor<2048xf32>>
-    %275 = flow.variable.address @"__iree_flow___sm_node1105__m.layer-151.beta" : !util.ptr<tensor<2048xf32>>
-    %276 = flow.variable.address @"__iree_flow___sm_node1106__m.layer-151.moving_mean" : !util.ptr<tensor<2048xf32>>
-    %277 = flow.variable.address @"__iree_flow___sm_node1107__m.layer-151.moving_variance" : !util.ptr<tensor<2048xf32>>
-    %278 = flow.variable.address @"__iree_flow___sm_node1113__m.layer-152.gamma" : !util.ptr<tensor<2048xf32>>
-    %279 = flow.variable.address @"__iree_flow___sm_node1114__m.layer-152.beta" : !util.ptr<tensor<2048xf32>>
-    %280 = flow.variable.address @"__iree_flow___sm_node1115__m.layer-152.moving_mean" : !util.ptr<tensor<2048xf32>>
-    %281 = flow.variable.address @"__iree_flow___sm_node1116__m.layer-152.moving_variance" : !util.ptr<tensor<2048xf32>>
-    %282 = flow.variable.address @"__iree_flow___sm_node1129__m.layer-155.kernel" : !util.ptr<tensor<1x1x2048x512xf32>>
-    %283 = flow.variable.address @"__iree_flow___sm_node1130__m.layer-155.bias" : !util.ptr<tensor<512xf32>>
-    %284 = flow.variable.address @"__iree_flow___sm_node1136__m.layer-156.gamma" : !util.ptr<tensor<512xf32>>
-    %285 = flow.variable.address @"__iree_flow___sm_node1137__m.layer-156.beta" : !util.ptr<tensor<512xf32>>
-    %286 = flow.variable.address @"__iree_flow___sm_node1138__m.layer-156.moving_mean" : !util.ptr<tensor<512xf32>>
-    %287 = flow.variable.address @"__iree_flow___sm_node1139__m.layer-156.moving_variance" : !util.ptr<tensor<512xf32>>
-    %288 = flow.variable.address @"__iree_flow___sm_node1148__m.layer-158.kernel" : !util.ptr<tensor<3x3x512x512xf32>>
-    %289 = flow.variable.address @"__iree_flow___sm_node1149__m.layer-158.bias" : !util.ptr<tensor<512xf32>>
-    %290 = flow.variable.address @"__iree_flow___sm_node1155__m.layer-159.gamma" : !util.ptr<tensor<512xf32>>
-    %291 = flow.variable.address @"__iree_flow___sm_node1156__m.layer-159.beta" : !util.ptr<tensor<512xf32>>
-    %292 = flow.variable.address @"__iree_flow___sm_node1157__m.layer-159.moving_mean" : !util.ptr<tensor<512xf32>>
-    %293 = flow.variable.address @"__iree_flow___sm_node1158__m.layer-159.moving_variance" : !util.ptr<tensor<512xf32>>
-    %294 = flow.variable.address @"__iree_flow___sm_node1167__m.layer-161.kernel" : !util.ptr<tensor<1x1x512x2048xf32>>
-    %295 = flow.variable.address @"__iree_flow___sm_node1168__m.layer-161.bias" : !util.ptr<tensor<2048xf32>>
-    %296 = flow.variable.address @"__iree_flow___sm_node1174__m.layer-162.gamma" : !util.ptr<tensor<2048xf32>>
-    %297 = flow.variable.address @"__iree_flow___sm_node1175__m.layer-162.beta" : !util.ptr<tensor<2048xf32>>
-    %298 = flow.variable.address @"__iree_flow___sm_node1176__m.layer-162.moving_mean" : !util.ptr<tensor<2048xf32>>
-    %299 = flow.variable.address @"__iree_flow___sm_node1177__m.layer-162.moving_variance" : !util.ptr<tensor<2048xf32>>
-    %300 = flow.variable.address @"__iree_flow___sm_node1190__m.layer-165.kernel" : !util.ptr<tensor<1x1x2048x512xf32>>
-    %301 = flow.variable.address @"__iree_flow___sm_node1191__m.layer-165.bias" : !util.ptr<tensor<512xf32>>
-    %302 = flow.variable.address @"__iree_flow___sm_node1197__m.layer-166.gamma" : !util.ptr<tensor<512xf32>>
-    %303 = flow.variable.address @"__iree_flow___sm_node1198__m.layer-166.beta" : !util.ptr<tensor<512xf32>>
-    %304 = flow.variable.address @"__iree_flow___sm_node1199__m.layer-166.moving_mean" : !util.ptr<tensor<512xf32>>
-    %305 = flow.variable.address @"__iree_flow___sm_node1200__m.layer-166.moving_variance" : !util.ptr<tensor<512xf32>>
-    %306 = flow.variable.address @"__iree_flow___sm_node1209__m.layer-168.kernel" : !util.ptr<tensor<3x3x512x512xf32>>
-    %307 = flow.variable.address @"__iree_flow___sm_node1210__m.layer-168.bias" : !util.ptr<tensor<512xf32>>
-    %308 = flow.variable.address @"__iree_flow___sm_node1216__m.layer-169.gamma" : !util.ptr<tensor<512xf32>>
-    %309 = flow.variable.address @"__iree_flow___sm_node1217__m.layer-169.beta" : !util.ptr<tensor<512xf32>>
-    %310 = flow.variable.address @"__iree_flow___sm_node1218__m.layer-169.moving_mean" : !util.ptr<tensor<512xf32>>
-    %311 = flow.variable.address @"__iree_flow___sm_node1219__m.layer-169.moving_variance" : !util.ptr<tensor<512xf32>>
-    %312 = flow.variable.address @"__iree_flow___sm_node1228__m.layer-171.kernel" : !util.ptr<tensor<1x1x512x2048xf32>>
-    %313 = flow.variable.address @"__iree_flow___sm_node1229__m.layer-171.bias" : !util.ptr<tensor<2048xf32>>
-    %314 = flow.variable.address @"__iree_flow___sm_node1235__m.layer-172.gamma" : !util.ptr<tensor<2048xf32>>
-    %315 = flow.variable.address @"__iree_flow___sm_node1236__m.layer-172.beta" : !util.ptr<tensor<2048xf32>>
-    %316 = flow.variable.address @"__iree_flow___sm_node1237__m.layer-172.moving_mean" : !util.ptr<tensor<2048xf32>>
-    %317 = flow.variable.address @"__iree_flow___sm_node1238__m.layer-172.moving_variance" : !util.ptr<tensor<2048xf32>>
-    %318 = flow.variable.address @"__iree_flow___sm_node1255__m.layer-176.kernel" : !util.ptr<tensor<2048x1000xf32>>
-    %319 = flow.variable.address @"__iree_flow___sm_node1256__m.layer-176.bias" : !util.ptr<tensor<1000xf32>>
+    %0 = util.global.address @"__iree_flow___sm_node188__m.layer-2.kernel" : !util.ptr<tensor<7x7x3x64xf32>>
+    %1 = util.global.address @"__iree_flow___sm_node189__m.layer-2.bias" : !util.ptr<tensor<64xf32>>
+    %2 = util.global.address @"__iree_flow___sm_node195__m.layer-3.gamma" : !util.ptr<tensor<64xf32>>
+    %3 = util.global.address @"__iree_flow___sm_node196__m.layer-3.beta" : !util.ptr<tensor<64xf32>>
+    %4 = util.global.address @"__iree_flow___sm_node197__m.layer-3.moving_mean" : !util.ptr<tensor<64xf32>>
+    %5 = util.global.address @"__iree_flow___sm_node198__m.layer-3.moving_variance" : !util.ptr<tensor<64xf32>>
+    %6 = util.global.address @"__iree_flow___sm_node215__m.layer-7.kernel" : !util.ptr<tensor<1x1x64x64xf32>>
+    %7 = util.global.address @"__iree_flow___sm_node216__m.layer-7.bias" : !util.ptr<tensor<64xf32>>
+    %8 = util.global.address @"__iree_flow___sm_node222__m.layer-8.gamma" : !util.ptr<tensor<64xf32>>
+    %9 = util.global.address @"__iree_flow___sm_node223__m.layer-8.beta" : !util.ptr<tensor<64xf32>>
+    %10 = util.global.address @"__iree_flow___sm_node224__m.layer-8.moving_mean" : !util.ptr<tensor<64xf32>>
+    %11 = util.global.address @"__iree_flow___sm_node225__m.layer-8.moving_variance" : !util.ptr<tensor<64xf32>>
+    %12 = util.global.address @"__iree_flow___sm_node234__m.layer-10.kernel" : !util.ptr<tensor<3x3x64x64xf32>>
+    %13 = util.global.address @"__iree_flow___sm_node235__m.layer-10.bias" : !util.ptr<tensor<64xf32>>
+    %14 = util.global.address @"__iree_flow___sm_node241__m.layer-11.gamma" : !util.ptr<tensor<64xf32>>
+    %15 = util.global.address @"__iree_flow___sm_node242__m.layer-11.beta" : !util.ptr<tensor<64xf32>>
+    %16 = util.global.address @"__iree_flow___sm_node243__m.layer-11.moving_mean" : !util.ptr<tensor<64xf32>>
+    %17 = util.global.address @"__iree_flow___sm_node244__m.layer-11.moving_variance" : !util.ptr<tensor<64xf32>>
+    %18 = util.global.address @"__iree_flow___sm_node259__m.layer-14.kernel" : !util.ptr<tensor<1x1x64x256xf32>>
+    %19 = util.global.address @"__iree_flow___sm_node260__m.layer-14.bias" : !util.ptr<tensor<256xf32>>
+    %20 = util.global.address @"__iree_flow___sm_node253__m.layer-13.kernel" : !util.ptr<tensor<1x1x64x256xf32>>
+    %21 = util.global.address @"__iree_flow___sm_node254__m.layer-13.bias" : !util.ptr<tensor<256xf32>>
+    %22 = util.global.address @"__iree_flow___sm_node266__m.layer-15.gamma" : !util.ptr<tensor<256xf32>>
+    %23 = util.global.address @"__iree_flow___sm_node267__m.layer-15.beta" : !util.ptr<tensor<256xf32>>
+    %24 = util.global.address @"__iree_flow___sm_node268__m.layer-15.moving_mean" : !util.ptr<tensor<256xf32>>
+    %25 = util.global.address @"__iree_flow___sm_node269__m.layer-15.moving_variance" : !util.ptr<tensor<256xf32>>
+    %26 = util.global.address @"__iree_flow___sm_node275__m.layer-16.gamma" : !util.ptr<tensor<256xf32>>
+    %27 = util.global.address @"__iree_flow___sm_node276__m.layer-16.beta" : !util.ptr<tensor<256xf32>>
+    %28 = util.global.address @"__iree_flow___sm_node277__m.layer-16.moving_mean" : !util.ptr<tensor<256xf32>>
+    %29 = util.global.address @"__iree_flow___sm_node278__m.layer-16.moving_variance" : !util.ptr<tensor<256xf32>>
+    %30 = util.global.address @"__iree_flow___sm_node291__m.layer-19.kernel" : !util.ptr<tensor<1x1x256x64xf32>>
+    %31 = util.global.address @"__iree_flow___sm_node292__m.layer-19.bias" : !util.ptr<tensor<64xf32>>
+    %32 = util.global.address @"__iree_flow___sm_node298__m.layer-20.gamma" : !util.ptr<tensor<64xf32>>
+    %33 = util.global.address @"__iree_flow___sm_node299__m.layer-20.beta" : !util.ptr<tensor<64xf32>>
+    %34 = util.global.address @"__iree_flow___sm_node300__m.layer-20.moving_mean" : !util.ptr<tensor<64xf32>>
+    %35 = util.global.address @"__iree_flow___sm_node301__m.layer-20.moving_variance" : !util.ptr<tensor<64xf32>>
+    %36 = util.global.address @"__iree_flow___sm_node310__m.layer-22.kernel" : !util.ptr<tensor<3x3x64x64xf32>>
+    %37 = util.global.address @"__iree_flow___sm_node311__m.layer-22.bias" : !util.ptr<tensor<64xf32>>
+    %38 = util.global.address @"__iree_flow___sm_node317__m.layer-23.gamma" : !util.ptr<tensor<64xf32>>
+    %39 = util.global.address @"__iree_flow___sm_node318__m.layer-23.beta" : !util.ptr<tensor<64xf32>>
+    %40 = util.global.address @"__iree_flow___sm_node319__m.layer-23.moving_mean" : !util.ptr<tensor<64xf32>>
+    %41 = util.global.address @"__iree_flow___sm_node320__m.layer-23.moving_variance" : !util.ptr<tensor<64xf32>>
+    %42 = util.global.address @"__iree_flow___sm_node329__m.layer-25.kernel" : !util.ptr<tensor<1x1x64x256xf32>>
+    %43 = util.global.address @"__iree_flow___sm_node330__m.layer-25.bias" : !util.ptr<tensor<256xf32>>
+    %44 = util.global.address @"__iree_flow___sm_node336__m.layer-26.gamma" : !util.ptr<tensor<256xf32>>
+    %45 = util.global.address @"__iree_flow___sm_node337__m.layer-26.beta" : !util.ptr<tensor<256xf32>>
+    %46 = util.global.address @"__iree_flow___sm_node338__m.layer-26.moving_mean" : !util.ptr<tensor<256xf32>>
+    %47 = util.global.address @"__iree_flow___sm_node339__m.layer-26.moving_variance" : !util.ptr<tensor<256xf32>>
+    %48 = util.global.address @"__iree_flow___sm_node352__m.layer-29.kernel" : !util.ptr<tensor<1x1x256x64xf32>>
+    %49 = util.global.address @"__iree_flow___sm_node353__m.layer-29.bias" : !util.ptr<tensor<64xf32>>
+    %50 = util.global.address @"__iree_flow___sm_node359__m.layer-30.gamma" : !util.ptr<tensor<64xf32>>
+    %51 = util.global.address @"__iree_flow___sm_node360__m.layer-30.beta" : !util.ptr<tensor<64xf32>>
+    %52 = util.global.address @"__iree_flow___sm_node361__m.layer-30.moving_mean" : !util.ptr<tensor<64xf32>>
+    %53 = util.global.address @"__iree_flow___sm_node362__m.layer-30.moving_variance" : !util.ptr<tensor<64xf32>>
+    %54 = util.global.address @"__iree_flow___sm_node371__m.layer-32.kernel" : !util.ptr<tensor<3x3x64x64xf32>>
+    %55 = util.global.address @"__iree_flow___sm_node372__m.layer-32.bias" : !util.ptr<tensor<64xf32>>
+    %56 = util.global.address @"__iree_flow___sm_node378__m.layer-33.gamma" : !util.ptr<tensor<64xf32>>
+    %57 = util.global.address @"__iree_flow___sm_node379__m.layer-33.beta" : !util.ptr<tensor<64xf32>>
+    %58 = util.global.address @"__iree_flow___sm_node380__m.layer-33.moving_mean" : !util.ptr<tensor<64xf32>>
+    %59 = util.global.address @"__iree_flow___sm_node381__m.layer-33.moving_variance" : !util.ptr<tensor<64xf32>>
+    %60 = util.global.address @"__iree_flow___sm_node390__m.layer-35.kernel" : !util.ptr<tensor<1x1x64x256xf32>>
+    %61 = util.global.address @"__iree_flow___sm_node391__m.layer-35.bias" : !util.ptr<tensor<256xf32>>
+    %62 = util.global.address @"__iree_flow___sm_node397__m.layer-36.gamma" : !util.ptr<tensor<256xf32>>
+    %63 = util.global.address @"__iree_flow___sm_node398__m.layer-36.beta" : !util.ptr<tensor<256xf32>>
+    %64 = util.global.address @"__iree_flow___sm_node399__m.layer-36.moving_mean" : !util.ptr<tensor<256xf32>>
+    %65 = util.global.address @"__iree_flow___sm_node400__m.layer-36.moving_variance" : !util.ptr<tensor<256xf32>>
+    %66 = util.global.address @"__iree_flow___sm_node413__m.layer-39.kernel" : !util.ptr<tensor<1x1x256x128xf32>>
+    %67 = util.global.address @"__iree_flow___sm_node414__m.layer-39.bias" : !util.ptr<tensor<128xf32>>
+    %68 = util.global.address @"__iree_flow___sm_node420__m.layer-40.gamma" : !util.ptr<tensor<128xf32>>
+    %69 = util.global.address @"__iree_flow___sm_node421__m.layer-40.beta" : !util.ptr<tensor<128xf32>>
+    %70 = util.global.address @"__iree_flow___sm_node422__m.layer-40.moving_mean" : !util.ptr<tensor<128xf32>>
+    %71 = util.global.address @"__iree_flow___sm_node423__m.layer-40.moving_variance" : !util.ptr<tensor<128xf32>>
+    %72 = util.global.address @"__iree_flow___sm_node432__m.layer-42.kernel" : !util.ptr<tensor<3x3x128x128xf32>>
+    %73 = util.global.address @"__iree_flow___sm_node433__m.layer-42.bias" : !util.ptr<tensor<128xf32>>
+    %74 = util.global.address @"__iree_flow___sm_node439__m.layer-43.gamma" : !util.ptr<tensor<128xf32>>
+    %75 = util.global.address @"__iree_flow___sm_node440__m.layer-43.beta" : !util.ptr<tensor<128xf32>>
+    %76 = util.global.address @"__iree_flow___sm_node441__m.layer-43.moving_mean" : !util.ptr<tensor<128xf32>>
+    %77 = util.global.address @"__iree_flow___sm_node442__m.layer-43.moving_variance" : !util.ptr<tensor<128xf32>>
+    %78 = util.global.address @"__iree_flow___sm_node457__m.layer-46.kernel" : !util.ptr<tensor<1x1x128x512xf32>>
+    %79 = util.global.address @"__iree_flow___sm_node458__m.layer-46.bias" : !util.ptr<tensor<512xf32>>
+    %80 = util.global.address @"__iree_flow___sm_node451__m.layer-45.kernel" : !util.ptr<tensor<1x1x256x512xf32>>
+    %81 = util.global.address @"__iree_flow___sm_node452__m.layer-45.bias" : !util.ptr<tensor<512xf32>>
+    %82 = util.global.address @"__iree_flow___sm_node464__m.layer-47.gamma" : !util.ptr<tensor<512xf32>>
+    %83 = util.global.address @"__iree_flow___sm_node465__m.layer-47.beta" : !util.ptr<tensor<512xf32>>
+    %84 = util.global.address @"__iree_flow___sm_node466__m.layer-47.moving_mean" : !util.ptr<tensor<512xf32>>
+    %85 = util.global.address @"__iree_flow___sm_node467__m.layer-47.moving_variance" : !util.ptr<tensor<512xf32>>
+    %86 = util.global.address @"__iree_flow___sm_node473__m.layer-48.gamma" : !util.ptr<tensor<512xf32>>
+    %87 = util.global.address @"__iree_flow___sm_node474__m.layer-48.beta" : !util.ptr<tensor<512xf32>>
+    %88 = util.global.address @"__iree_flow___sm_node475__m.layer-48.moving_mean" : !util.ptr<tensor<512xf32>>
+    %89 = util.global.address @"__iree_flow___sm_node476__m.layer-48.moving_variance" : !util.ptr<tensor<512xf32>>
+    %90 = util.global.address @"__iree_flow___sm_node489__m.layer-51.kernel" : !util.ptr<tensor<1x1x512x128xf32>>
+    %91 = util.global.address @"__iree_flow___sm_node490__m.layer-51.bias" : !util.ptr<tensor<128xf32>>
+    %92 = util.global.address @"__iree_flow___sm_node496__m.layer-52.gamma" : !util.ptr<tensor<128xf32>>
+    %93 = util.global.address @"__iree_flow___sm_node497__m.layer-52.beta" : !util.ptr<tensor<128xf32>>
+    %94 = util.global.address @"__iree_flow___sm_node498__m.layer-52.moving_mean" : !util.ptr<tensor<128xf32>>
+    %95 = util.global.address @"__iree_flow___sm_node499__m.layer-52.moving_variance" : !util.ptr<tensor<128xf32>>
+    %96 = util.global.address @"__iree_flow___sm_node508__m.layer-54.kernel" : !util.ptr<tensor<3x3x128x128xf32>>
+    %97 = util.global.address @"__iree_flow___sm_node509__m.layer-54.bias" : !util.ptr<tensor<128xf32>>
+    %98 = util.global.address @"__iree_flow___sm_node515__m.layer-55.gamma" : !util.ptr<tensor<128xf32>>
+    %99 = util.global.address @"__iree_flow___sm_node516__m.layer-55.beta" : !util.ptr<tensor<128xf32>>
+    %100 = util.global.address @"__iree_flow___sm_node517__m.layer-55.moving_mean" : !util.ptr<tensor<128xf32>>
+    %101 = util.global.address @"__iree_flow___sm_node518__m.layer-55.moving_variance" : !util.ptr<tensor<128xf32>>
+    %102 = util.global.address @"__iree_flow___sm_node527__m.layer-57.kernel" : !util.ptr<tensor<1x1x128x512xf32>>
+    %103 = util.global.address @"__iree_flow___sm_node528__m.layer-57.bias" : !util.ptr<tensor<512xf32>>
+    %104 = util.global.address @"__iree_flow___sm_node534__m.layer-58.gamma" : !util.ptr<tensor<512xf32>>
+    %105 = util.global.address @"__iree_flow___sm_node535__m.layer-58.beta" : !util.ptr<tensor<512xf32>>
+    %106 = util.global.address @"__iree_flow___sm_node536__m.layer-58.moving_mean" : !util.ptr<tensor<512xf32>>
+    %107 = util.global.address @"__iree_flow___sm_node537__m.layer-58.moving_variance" : !util.ptr<tensor<512xf32>>
+    %108 = util.global.address @"__iree_flow___sm_node550__m.layer-61.kernel" : !util.ptr<tensor<1x1x512x128xf32>>
+    %109 = util.global.address @"__iree_flow___sm_node551__m.layer-61.bias" : !util.ptr<tensor<128xf32>>
+    %110 = util.global.address @"__iree_flow___sm_node557__m.layer-62.gamma" : !util.ptr<tensor<128xf32>>
+    %111 = util.global.address @"__iree_flow___sm_node558__m.layer-62.beta" : !util.ptr<tensor<128xf32>>
+    %112 = util.global.address @"__iree_flow___sm_node559__m.layer-62.moving_mean" : !util.ptr<tensor<128xf32>>
+    %113 = util.global.address @"__iree_flow___sm_node560__m.layer-62.moving_variance" : !util.ptr<tensor<128xf32>>
+    %114 = util.global.address @"__iree_flow___sm_node569__m.layer-64.kernel" : !util.ptr<tensor<3x3x128x128xf32>>
+    %115 = util.global.address @"__iree_flow___sm_node570__m.layer-64.bias" : !util.ptr<tensor<128xf32>>
+    %116 = util.global.address @"__iree_flow___sm_node576__m.layer-65.gamma" : !util.ptr<tensor<128xf32>>
+    %117 = util.global.address @"__iree_flow___sm_node577__m.layer-65.beta" : !util.ptr<tensor<128xf32>>
+    %118 = util.global.address @"__iree_flow___sm_node578__m.layer-65.moving_mean" : !util.ptr<tensor<128xf32>>
+    %119 = util.global.address @"__iree_flow___sm_node579__m.layer-65.moving_variance" : !util.ptr<tensor<128xf32>>
+    %120 = util.global.address @"__iree_flow___sm_node588__m.layer-67.kernel" : !util.ptr<tensor<1x1x128x512xf32>>
+    %121 = util.global.address @"__iree_flow___sm_node589__m.layer-67.bias" : !util.ptr<tensor<512xf32>>
+    %122 = util.global.address @"__iree_flow___sm_node595__m.layer-68.gamma" : !util.ptr<tensor<512xf32>>
+    %123 = util.global.address @"__iree_flow___sm_node596__m.layer-68.beta" : !util.ptr<tensor<512xf32>>
+    %124 = util.global.address @"__iree_flow___sm_node597__m.layer-68.moving_mean" : !util.ptr<tensor<512xf32>>
+    %125 = util.global.address @"__iree_flow___sm_node598__m.layer-68.moving_variance" : !util.ptr<tensor<512xf32>>
+    %126 = util.global.address @"__iree_flow___sm_node611__m.layer-71.kernel" : !util.ptr<tensor<1x1x512x128xf32>>
+    %127 = util.global.address @"__iree_flow___sm_node612__m.layer-71.bias" : !util.ptr<tensor<128xf32>>
+    %128 = util.global.address @"__iree_flow___sm_node618__m.layer-72.gamma" : !util.ptr<tensor<128xf32>>
+    %129 = util.global.address @"__iree_flow___sm_node619__m.layer-72.beta" : !util.ptr<tensor<128xf32>>
+    %130 = util.global.address @"__iree_flow___sm_node620__m.layer-72.moving_mean" : !util.ptr<tensor<128xf32>>
+    %131 = util.global.address @"__iree_flow___sm_node621__m.layer-72.moving_variance" : !util.ptr<tensor<128xf32>>
+    %132 = util.global.address @"__iree_flow___sm_node630__m.layer-74.kernel" : !util.ptr<tensor<3x3x128x128xf32>>
+    %133 = util.global.address @"__iree_flow___sm_node631__m.layer-74.bias" : !util.ptr<tensor<128xf32>>
+    %134 = util.global.address @"__iree_flow___sm_node637__m.layer-75.gamma" : !util.ptr<tensor<128xf32>>
+    %135 = util.global.address @"__iree_flow___sm_node638__m.layer-75.beta" : !util.ptr<tensor<128xf32>>
+    %136 = util.global.address @"__iree_flow___sm_node639__m.layer-75.moving_mean" : !util.ptr<tensor<128xf32>>
+    %137 = util.global.address @"__iree_flow___sm_node640__m.layer-75.moving_variance" : !util.ptr<tensor<128xf32>>
+    %138 = util.global.address @"__iree_flow___sm_node649__m.layer-77.kernel" : !util.ptr<tensor<1x1x128x512xf32>>
+    %139 = util.global.address @"__iree_flow___sm_node650__m.layer-77.bias" : !util.ptr<tensor<512xf32>>
+    %140 = util.global.address @"__iree_flow___sm_node656__m.layer-78.gamma" : !util.ptr<tensor<512xf32>>
+    %141 = util.global.address @"__iree_flow___sm_node657__m.layer-78.beta" : !util.ptr<tensor<512xf32>>
+    %142 = util.global.address @"__iree_flow___sm_node658__m.layer-78.moving_mean" : !util.ptr<tensor<512xf32>>
+    %143 = util.global.address @"__iree_flow___sm_node659__m.layer-78.moving_variance" : !util.ptr<tensor<512xf32>>
+    %144 = util.global.address @"__iree_flow___sm_node672__m.layer-81.kernel" : !util.ptr<tensor<1x1x512x256xf32>>
+    %145 = util.global.address @"__iree_flow___sm_node673__m.layer-81.bias" : !util.ptr<tensor<256xf32>>
+    %146 = util.global.address @"__iree_flow___sm_node679__m.layer-82.gamma" : !util.ptr<tensor<256xf32>>
+    %147 = util.global.address @"__iree_flow___sm_node680__m.layer-82.beta" : !util.ptr<tensor<256xf32>>
+    %148 = util.global.address @"__iree_flow___sm_node681__m.layer-82.moving_mean" : !util.ptr<tensor<256xf32>>
+    %149 = util.global.address @"__iree_flow___sm_node682__m.layer-82.moving_variance" : !util.ptr<tensor<256xf32>>
+    %150 = util.global.address @"__iree_flow___sm_node691__m.layer-84.kernel" : !util.ptr<tensor<3x3x256x256xf32>>
+    %151 = util.global.address @"__iree_flow___sm_node692__m.layer-84.bias" : !util.ptr<tensor<256xf32>>
+    %152 = util.global.address @"__iree_flow___sm_node698__m.layer-85.gamma" : !util.ptr<tensor<256xf32>>
+    %153 = util.global.address @"__iree_flow___sm_node699__m.layer-85.beta" : !util.ptr<tensor<256xf32>>
+    %154 = util.global.address @"__iree_flow___sm_node700__m.layer-85.moving_mean" : !util.ptr<tensor<256xf32>>
+    %155 = util.global.address @"__iree_flow___sm_node701__m.layer-85.moving_variance" : !util.ptr<tensor<256xf32>>
+    %156 = util.global.address @"__iree_flow___sm_node716__m.layer-88.kernel" : !util.ptr<tensor<1x1x256x1024xf32>>
+    %157 = util.global.address @"__iree_flow___sm_node717__m.layer-88.bias" : !util.ptr<tensor<1024xf32>>
+    %158 = util.global.address @"__iree_flow___sm_node710__m.layer-87.kernel" : !util.ptr<tensor<1x1x512x1024xf32>>
+    %159 = util.global.address @"__iree_flow___sm_node711__m.layer-87.bias" : !util.ptr<tensor<1024xf32>>
+    %160 = util.global.address @"__iree_flow___sm_node723__m.layer-89.gamma" : !util.ptr<tensor<1024xf32>>
+    %161 = util.global.address @"__iree_flow___sm_node724__m.layer-89.beta" : !util.ptr<tensor<1024xf32>>
+    %162 = util.global.address @"__iree_flow___sm_node725__m.layer-89.moving_mean" : !util.ptr<tensor<1024xf32>>
+    %163 = util.global.address @"__iree_flow___sm_node726__m.layer-89.moving_variance" : !util.ptr<tensor<1024xf32>>
+    %164 = util.global.address @"__iree_flow___sm_node732__m.layer-90.gamma" : !util.ptr<tensor<1024xf32>>
+    %165 = util.global.address @"__iree_flow___sm_node733__m.layer-90.beta" : !util.ptr<tensor<1024xf32>>
+    %166 = util.global.address @"__iree_flow___sm_node734__m.layer-90.moving_mean" : !util.ptr<tensor<1024xf32>>
+    %167 = util.global.address @"__iree_flow___sm_node735__m.layer-90.moving_variance" : !util.ptr<tensor<1024xf32>>
+    %168 = util.global.address @"__iree_flow___sm_node748__m.layer-93.kernel" : !util.ptr<tensor<1x1x1024x256xf32>>
+    %169 = util.global.address @"__iree_flow___sm_node749__m.layer-93.bias" : !util.ptr<tensor<256xf32>>
+    %170 = util.global.address @"__iree_flow___sm_node755__m.layer-94.gamma" : !util.ptr<tensor<256xf32>>
+    %171 = util.global.address @"__iree_flow___sm_node756__m.layer-94.beta" : !util.ptr<tensor<256xf32>>
+    %172 = util.global.address @"__iree_flow___sm_node757__m.layer-94.moving_mean" : !util.ptr<tensor<256xf32>>
+    %173 = util.global.address @"__iree_flow___sm_node758__m.layer-94.moving_variance" : !util.ptr<tensor<256xf32>>
+    %174 = util.global.address @"__iree_flow___sm_node767__m.layer-96.kernel" : !util.ptr<tensor<3x3x256x256xf32>>
+    %175 = util.global.address @"__iree_flow___sm_node768__m.layer-96.bias" : !util.ptr<tensor<256xf32>>
+    %176 = util.global.address @"__iree_flow___sm_node774__m.layer-97.gamma" : !util.ptr<tensor<256xf32>>
+    %177 = util.global.address @"__iree_flow___sm_node775__m.layer-97.beta" : !util.ptr<tensor<256xf32>>
+    %178 = util.global.address @"__iree_flow___sm_node776__m.layer-97.moving_mean" : !util.ptr<tensor<256xf32>>
+    %179 = util.global.address @"__iree_flow___sm_node777__m.layer-97.moving_variance" : !util.ptr<tensor<256xf32>>
+    %180 = util.global.address @"__iree_flow___sm_node786__m.layer-99.kernel" : !util.ptr<tensor<1x1x256x1024xf32>>
+    %181 = util.global.address @"__iree_flow___sm_node787__m.layer-99.bias" : !util.ptr<tensor<1024xf32>>
+    %182 = util.global.address @"__iree_flow___sm_node793__m.layer-100.gamma" : !util.ptr<tensor<1024xf32>>
+    %183 = util.global.address @"__iree_flow___sm_node794__m.layer-100.beta" : !util.ptr<tensor<1024xf32>>
+    %184 = util.global.address @"__iree_flow___sm_node795__m.layer-100.moving_mean" : !util.ptr<tensor<1024xf32>>
+    %185 = util.global.address @"__iree_flow___sm_node796__m.layer-100.moving_variance" : !util.ptr<tensor<1024xf32>>
+    %186 = util.global.address @"__iree_flow___sm_node809__m.layer-103.kernel" : !util.ptr<tensor<1x1x1024x256xf32>>
+    %187 = util.global.address @"__iree_flow___sm_node810__m.layer-103.bias" : !util.ptr<tensor<256xf32>>
+    %188 = util.global.address @"__iree_flow___sm_node816__m.layer-104.gamma" : !util.ptr<tensor<256xf32>>
+    %189 = util.global.address @"__iree_flow___sm_node817__m.layer-104.beta" : !util.ptr<tensor<256xf32>>
+    %190 = util.global.address @"__iree_flow___sm_node818__m.layer-104.moving_mean" : !util.ptr<tensor<256xf32>>
+    %191 = util.global.address @"__iree_flow___sm_node819__m.layer-104.moving_variance" : !util.ptr<tensor<256xf32>>
+    %192 = util.global.address @"__iree_flow___sm_node828__m.layer-106.kernel" : !util.ptr<tensor<3x3x256x256xf32>>
+    %193 = util.global.address @"__iree_flow___sm_node829__m.layer-106.bias" : !util.ptr<tensor<256xf32>>
+    %194 = util.global.address @"__iree_flow___sm_node835__m.layer-107.gamma" : !util.ptr<tensor<256xf32>>
+    %195 = util.global.address @"__iree_flow___sm_node836__m.layer-107.beta" : !util.ptr<tensor<256xf32>>
+    %196 = util.global.address @"__iree_flow___sm_node837__m.layer-107.moving_mean" : !util.ptr<tensor<256xf32>>
+    %197 = util.global.address @"__iree_flow___sm_node838__m.layer-107.moving_variance" : !util.ptr<tensor<256xf32>>
+    %198 = util.global.address @"__iree_flow___sm_node847__m.layer-109.kernel" : !util.ptr<tensor<1x1x256x1024xf32>>
+    %199 = util.global.address @"__iree_flow___sm_node848__m.layer-109.bias" : !util.ptr<tensor<1024xf32>>
+    %200 = util.global.address @"__iree_flow___sm_node854__m.layer-110.gamma" : !util.ptr<tensor<1024xf32>>
+    %201 = util.global.address @"__iree_flow___sm_node855__m.layer-110.beta" : !util.ptr<tensor<1024xf32>>
+    %202 = util.global.address @"__iree_flow___sm_node856__m.layer-110.moving_mean" : !util.ptr<tensor<1024xf32>>
+    %203 = util.global.address @"__iree_flow___sm_node857__m.layer-110.moving_variance" : !util.ptr<tensor<1024xf32>>
+    %204 = util.global.address @"__iree_flow___sm_node870__m.layer-113.kernel" : !util.ptr<tensor<1x1x1024x256xf32>>
+    %205 = util.global.address @"__iree_flow___sm_node871__m.layer-113.bias" : !util.ptr<tensor<256xf32>>
+    %206 = util.global.address @"__iree_flow___sm_node877__m.layer-114.gamma" : !util.ptr<tensor<256xf32>>
+    %207 = util.global.address @"__iree_flow___sm_node878__m.layer-114.beta" : !util.ptr<tensor<256xf32>>
+    %208 = util.global.address @"__iree_flow___sm_node879__m.layer-114.moving_mean" : !util.ptr<tensor<256xf32>>
+    %209 = util.global.address @"__iree_flow___sm_node880__m.layer-114.moving_variance" : !util.ptr<tensor<256xf32>>
+    %210 = util.global.address @"__iree_flow___sm_node889__m.layer-116.kernel" : !util.ptr<tensor<3x3x256x256xf32>>
+    %211 = util.global.address @"__iree_flow___sm_node890__m.layer-116.bias" : !util.ptr<tensor<256xf32>>
+    %212 = util.global.address @"__iree_flow___sm_node896__m.layer-117.gamma" : !util.ptr<tensor<256xf32>>
+    %213 = util.global.address @"__iree_flow___sm_node897__m.layer-117.beta" : !util.ptr<tensor<256xf32>>
+    %214 = util.global.address @"__iree_flow___sm_node898__m.layer-117.moving_mean" : !util.ptr<tensor<256xf32>>
+    %215 = util.global.address @"__iree_flow___sm_node899__m.layer-117.moving_variance" : !util.ptr<tensor<256xf32>>
+    %216 = util.global.address @"__iree_flow___sm_node908__m.layer-119.kernel" : !util.ptr<tensor<1x1x256x1024xf32>>
+    %217 = util.global.address @"__iree_flow___sm_node909__m.layer-119.bias" : !util.ptr<tensor<1024xf32>>
+    %218 = util.global.address @"__iree_flow___sm_node915__m.layer-120.gamma" : !util.ptr<tensor<1024xf32>>
+    %219 = util.global.address @"__iree_flow___sm_node916__m.layer-120.beta" : !util.ptr<tensor<1024xf32>>
+    %220 = util.global.address @"__iree_flow___sm_node917__m.layer-120.moving_mean" : !util.ptr<tensor<1024xf32>>
+    %221 = util.global.address @"__iree_flow___sm_node918__m.layer-120.moving_variance" : !util.ptr<tensor<1024xf32>>
+    %222 = util.global.address @"__iree_flow___sm_node931__m.layer-123.kernel" : !util.ptr<tensor<1x1x1024x256xf32>>
+    %223 = util.global.address @"__iree_flow___sm_node932__m.layer-123.bias" : !util.ptr<tensor<256xf32>>
+    %224 = util.global.address @"__iree_flow___sm_node938__m.layer-124.gamma" : !util.ptr<tensor<256xf32>>
+    %225 = util.global.address @"__iree_flow___sm_node939__m.layer-124.beta" : !util.ptr<tensor<256xf32>>
+    %226 = util.global.address @"__iree_flow___sm_node940__m.layer-124.moving_mean" : !util.ptr<tensor<256xf32>>
+    %227 = util.global.address @"__iree_flow___sm_node941__m.layer-124.moving_variance" : !util.ptr<tensor<256xf32>>
+    %228 = util.global.address @"__iree_flow___sm_node950__m.layer-126.kernel" : !util.ptr<tensor<3x3x256x256xf32>>
+    %229 = util.global.address @"__iree_flow___sm_node951__m.layer-126.bias" : !util.ptr<tensor<256xf32>>
+    %230 = util.global.address @"__iree_flow___sm_node957__m.layer-127.gamma" : !util.ptr<tensor<256xf32>>
+    %231 = util.global.address @"__iree_flow___sm_node958__m.layer-127.beta" : !util.ptr<tensor<256xf32>>
+    %232 = util.global.address @"__iree_flow___sm_node959__m.layer-127.moving_mean" : !util.ptr<tensor<256xf32>>
+    %233 = util.global.address @"__iree_flow___sm_node960__m.layer-127.moving_variance" : !util.ptr<tensor<256xf32>>
+    %234 = util.global.address @"__iree_flow___sm_node969__m.layer-129.kernel" : !util.ptr<tensor<1x1x256x1024xf32>>
+    %235 = util.global.address @"__iree_flow___sm_node970__m.layer-129.bias" : !util.ptr<tensor<1024xf32>>
+    %236 = util.global.address @"__iree_flow___sm_node976__m.layer-130.gamma" : !util.ptr<tensor<1024xf32>>
+    %237 = util.global.address @"__iree_flow___sm_node977__m.layer-130.beta" : !util.ptr<tensor<1024xf32>>
+    %238 = util.global.address @"__iree_flow___sm_node978__m.layer-130.moving_mean" : !util.ptr<tensor<1024xf32>>
+    %239 = util.global.address @"__iree_flow___sm_node979__m.layer-130.moving_variance" : !util.ptr<tensor<1024xf32>>
+    %240 = util.global.address @"__iree_flow___sm_node992__m.layer-133.kernel" : !util.ptr<tensor<1x1x1024x256xf32>>
+    %241 = util.global.address @"__iree_flow___sm_node993__m.layer-133.bias" : !util.ptr<tensor<256xf32>>
+    %242 = util.global.address @"__iree_flow___sm_node999__m.layer-134.gamma" : !util.ptr<tensor<256xf32>>
+    %243 = util.global.address @"__iree_flow___sm_node1000__m.layer-134.beta" : !util.ptr<tensor<256xf32>>
+    %244 = util.global.address @"__iree_flow___sm_node1001__m.layer-134.moving_mean" : !util.ptr<tensor<256xf32>>
+    %245 = util.global.address @"__iree_flow___sm_node1002__m.layer-134.moving_variance" : !util.ptr<tensor<256xf32>>
+    %246 = util.global.address @"__iree_flow___sm_node1011__m.layer-136.kernel" : !util.ptr<tensor<3x3x256x256xf32>>
+    %247 = util.global.address @"__iree_flow___sm_node1012__m.layer-136.bias" : !util.ptr<tensor<256xf32>>
+    %248 = util.global.address @"__iree_flow___sm_node1018__m.layer-137.gamma" : !util.ptr<tensor<256xf32>>
+    %249 = util.global.address @"__iree_flow___sm_node1019__m.layer-137.beta" : !util.ptr<tensor<256xf32>>
+    %250 = util.global.address @"__iree_flow___sm_node1020__m.layer-137.moving_mean" : !util.ptr<tensor<256xf32>>
+    %251 = util.global.address @"__iree_flow___sm_node1021__m.layer-137.moving_variance" : !util.ptr<tensor<256xf32>>
+    %252 = util.global.address @"__iree_flow___sm_node1030__m.layer-139.kernel" : !util.ptr<tensor<1x1x256x1024xf32>>
+    %253 = util.global.address @"__iree_flow___sm_node1031__m.layer-139.bias" : !util.ptr<tensor<1024xf32>>
+    %254 = util.global.address @"__iree_flow___sm_node1037__m.layer-140.gamma" : !util.ptr<tensor<1024xf32>>
+    %255 = util.global.address @"__iree_flow___sm_node1038__m.layer-140.beta" : !util.ptr<tensor<1024xf32>>
+    %256 = util.global.address @"__iree_flow___sm_node1039__m.layer-140.moving_mean" : !util.ptr<tensor<1024xf32>>
+    %257 = util.global.address @"__iree_flow___sm_node1040__m.layer-140.moving_variance" : !util.ptr<tensor<1024xf32>>
+    %258 = util.global.address @"__iree_flow___sm_node1053__m.layer-143.kernel" : !util.ptr<tensor<1x1x1024x512xf32>>
+    %259 = util.global.address @"__iree_flow___sm_node1054__m.layer-143.bias" : !util.ptr<tensor<512xf32>>
+    %260 = util.global.address @"__iree_flow___sm_node1060__m.layer-144.gamma" : !util.ptr<tensor<512xf32>>
+    %261 = util.global.address @"__iree_flow___sm_node1061__m.layer-144.beta" : !util.ptr<tensor<512xf32>>
+    %262 = util.global.address @"__iree_flow___sm_node1062__m.layer-144.moving_mean" : !util.ptr<tensor<512xf32>>
+    %263 = util.global.address @"__iree_flow___sm_node1063__m.layer-144.moving_variance" : !util.ptr<tensor<512xf32>>
+    %264 = util.global.address @"__iree_flow___sm_node1072__m.layer-146.kernel" : !util.ptr<tensor<3x3x512x512xf32>>
+    %265 = util.global.address @"__iree_flow___sm_node1073__m.layer-146.bias" : !util.ptr<tensor<512xf32>>
+    %266 = util.global.address @"__iree_flow___sm_node1079__m.layer-147.gamma" : !util.ptr<tensor<512xf32>>
+    %267 = util.global.address @"__iree_flow___sm_node1080__m.layer-147.beta" : !util.ptr<tensor<512xf32>>
+    %268 = util.global.address @"__iree_flow___sm_node1081__m.layer-147.moving_mean" : !util.ptr<tensor<512xf32>>
+    %269 = util.global.address @"__iree_flow___sm_node1082__m.layer-147.moving_variance" : !util.ptr<tensor<512xf32>>
+    %270 = util.global.address @"__iree_flow___sm_node1097__m.layer-150.kernel" : !util.ptr<tensor<1x1x512x2048xf32>>
+    %271 = util.global.address @"__iree_flow___sm_node1098__m.layer-150.bias" : !util.ptr<tensor<2048xf32>>
+    %272 = util.global.address @"__iree_flow___sm_node1091__m.layer-149.kernel" : !util.ptr<tensor<1x1x1024x2048xf32>>
+    %273 = util.global.address @"__iree_flow___sm_node1092__m.layer-149.bias" : !util.ptr<tensor<2048xf32>>
+    %274 = util.global.address @"__iree_flow___sm_node1104__m.layer-151.gamma" : !util.ptr<tensor<2048xf32>>
+    %275 = util.global.address @"__iree_flow___sm_node1105__m.layer-151.beta" : !util.ptr<tensor<2048xf32>>
+    %276 = util.global.address @"__iree_flow___sm_node1106__m.layer-151.moving_mean" : !util.ptr<tensor<2048xf32>>
+    %277 = util.global.address @"__iree_flow___sm_node1107__m.layer-151.moving_variance" : !util.ptr<tensor<2048xf32>>
+    %278 = util.global.address @"__iree_flow___sm_node1113__m.layer-152.gamma" : !util.ptr<tensor<2048xf32>>
+    %279 = util.global.address @"__iree_flow___sm_node1114__m.layer-152.beta" : !util.ptr<tensor<2048xf32>>
+    %280 = util.global.address @"__iree_flow___sm_node1115__m.layer-152.moving_mean" : !util.ptr<tensor<2048xf32>>
+    %281 = util.global.address @"__iree_flow___sm_node1116__m.layer-152.moving_variance" : !util.ptr<tensor<2048xf32>>
+    %282 = util.global.address @"__iree_flow___sm_node1129__m.layer-155.kernel" : !util.ptr<tensor<1x1x2048x512xf32>>
+    %283 = util.global.address @"__iree_flow___sm_node1130__m.layer-155.bias" : !util.ptr<tensor<512xf32>>
+    %284 = util.global.address @"__iree_flow___sm_node1136__m.layer-156.gamma" : !util.ptr<tensor<512xf32>>
+    %285 = util.global.address @"__iree_flow___sm_node1137__m.layer-156.beta" : !util.ptr<tensor<512xf32>>
+    %286 = util.global.address @"__iree_flow___sm_node1138__m.layer-156.moving_mean" : !util.ptr<tensor<512xf32>>
+    %287 = util.global.address @"__iree_flow___sm_node1139__m.layer-156.moving_variance" : !util.ptr<tensor<512xf32>>
+    %288 = util.global.address @"__iree_flow___sm_node1148__m.layer-158.kernel" : !util.ptr<tensor<3x3x512x512xf32>>
+    %289 = util.global.address @"__iree_flow___sm_node1149__m.layer-158.bias" : !util.ptr<tensor<512xf32>>
+    %290 = util.global.address @"__iree_flow___sm_node1155__m.layer-159.gamma" : !util.ptr<tensor<512xf32>>
+    %291 = util.global.address @"__iree_flow___sm_node1156__m.layer-159.beta" : !util.ptr<tensor<512xf32>>
+    %292 = util.global.address @"__iree_flow___sm_node1157__m.layer-159.moving_mean" : !util.ptr<tensor<512xf32>>
+    %293 = util.global.address @"__iree_flow___sm_node1158__m.layer-159.moving_variance" : !util.ptr<tensor<512xf32>>
+    %294 = util.global.address @"__iree_flow___sm_node1167__m.layer-161.kernel" : !util.ptr<tensor<1x1x512x2048xf32>>
+    %295 = util.global.address @"__iree_flow___sm_node1168__m.layer-161.bias" : !util.ptr<tensor<2048xf32>>
+    %296 = util.global.address @"__iree_flow___sm_node1174__m.layer-162.gamma" : !util.ptr<tensor<2048xf32>>
+    %297 = util.global.address @"__iree_flow___sm_node1175__m.layer-162.beta" : !util.ptr<tensor<2048xf32>>
+    %298 = util.global.address @"__iree_flow___sm_node1176__m.layer-162.moving_mean" : !util.ptr<tensor<2048xf32>>
+    %299 = util.global.address @"__iree_flow___sm_node1177__m.layer-162.moving_variance" : !util.ptr<tensor<2048xf32>>
+    %300 = util.global.address @"__iree_flow___sm_node1190__m.layer-165.kernel" : !util.ptr<tensor<1x1x2048x512xf32>>
+    %301 = util.global.address @"__iree_flow___sm_node1191__m.layer-165.bias" : !util.ptr<tensor<512xf32>>
+    %302 = util.global.address @"__iree_flow___sm_node1197__m.layer-166.gamma" : !util.ptr<tensor<512xf32>>
+    %303 = util.global.address @"__iree_flow___sm_node1198__m.layer-166.beta" : !util.ptr<tensor<512xf32>>
+    %304 = util.global.address @"__iree_flow___sm_node1199__m.layer-166.moving_mean" : !util.ptr<tensor<512xf32>>
+    %305 = util.global.address @"__iree_flow___sm_node1200__m.layer-166.moving_variance" : !util.ptr<tensor<512xf32>>
+    %306 = util.global.address @"__iree_flow___sm_node1209__m.layer-168.kernel" : !util.ptr<tensor<3x3x512x512xf32>>
+    %307 = util.global.address @"__iree_flow___sm_node1210__m.layer-168.bias" : !util.ptr<tensor<512xf32>>
+    %308 = util.global.address @"__iree_flow___sm_node1216__m.layer-169.gamma" : !util.ptr<tensor<512xf32>>
+    %309 = util.global.address @"__iree_flow___sm_node1217__m.layer-169.beta" : !util.ptr<tensor<512xf32>>
+    %310 = util.global.address @"__iree_flow___sm_node1218__m.layer-169.moving_mean" : !util.ptr<tensor<512xf32>>
+    %311 = util.global.address @"__iree_flow___sm_node1219__m.layer-169.moving_variance" : !util.ptr<tensor<512xf32>>
+    %312 = util.global.address @"__iree_flow___sm_node1228__m.layer-171.kernel" : !util.ptr<tensor<1x1x512x2048xf32>>
+    %313 = util.global.address @"__iree_flow___sm_node1229__m.layer-171.bias" : !util.ptr<tensor<2048xf32>>
+    %314 = util.global.address @"__iree_flow___sm_node1235__m.layer-172.gamma" : !util.ptr<tensor<2048xf32>>
+    %315 = util.global.address @"__iree_flow___sm_node1236__m.layer-172.beta" : !util.ptr<tensor<2048xf32>>
+    %316 = util.global.address @"__iree_flow___sm_node1237__m.layer-172.moving_mean" : !util.ptr<tensor<2048xf32>>
+    %317 = util.global.address @"__iree_flow___sm_node1238__m.layer-172.moving_variance" : !util.ptr<tensor<2048xf32>>
+    %318 = util.global.address @"__iree_flow___sm_node1255__m.layer-176.kernel" : !util.ptr<tensor<2048x1000xf32>>
+    %319 = util.global.address @"__iree_flow___sm_node1256__m.layer-176.bias" : !util.ptr<tensor<1000xf32>>
     %320 = mhlo.constant dense<0.000000e+00> : tensor<1x112x112x64xf32>
     %321 = mhlo.constant dense<0.000000e+00> : tensor<1x56x56x64xf32>
     %322 = mhlo.constant dense<0.000000e+00> : tensor<1x56x56x256xf32>
@@ -659,326 +659,326 @@
     %329 = mhlo.constant dense<4.900000e+01> : tensor<1x2048xf32>
     %330 = mhlo.constant dense<0xFF800000> : tensor<f32>
     %331 = mhlo.constant dense<0.000000e+00> : tensor<f32>
-    %332 = flow.variable.load.indirect %5 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %333 = flow.variable.load.indirect %4 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %334 = flow.variable.load.indirect %3 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %335 = flow.variable.load.indirect %2 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %336 = flow.variable.load.indirect %1 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %337 = flow.variable.load.indirect %0 : !util.ptr<tensor<7x7x3x64xf32>> -> tensor<7x7x3x64xf32>
-    %338 = flow.variable.load.indirect %25 : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
-    %339 = flow.variable.load.indirect %24 : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
-    %340 = flow.variable.load.indirect %23 : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
-    %341 = flow.variable.load.indirect %22 : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
-    %342 = flow.variable.load.indirect %21 : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
-    %343 = flow.variable.load.indirect %20 : !util.ptr<tensor<1x1x64x256xf32>> -> tensor<1x1x64x256xf32>
-    %344 = flow.variable.load.indirect %11 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %345 = flow.variable.load.indirect %10 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %346 = flow.variable.load.indirect %9 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %347 = flow.variable.load.indirect %8 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %348 = flow.variable.load.indirect %7 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %349 = flow.variable.load.indirect %6 : !util.ptr<tensor<1x1x64x64xf32>> -> tensor<1x1x64x64xf32>
-    %350 = flow.variable.load.indirect %17 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %351 = flow.variable.load.indirect %16 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %352 = flow.variable.load.indirect %15 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %353 = flow.variable.load.indirect %14 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %354 = flow.variable.load.indirect %13 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %355 = flow.variable.load.indirect %12 : !util.ptr<tensor<3x3x64x64xf32>> -> tensor<3x3x64x64xf32>
-    %356 = flow.variable.load.indirect %29 : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
-    %357 = flow.variable.load.indirect %28 : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
-    %358 = flow.variable.load.indirect %27 : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
-    %359 = flow.variable.load.indirect %26 : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
-    %360 = flow.variable.load.indirect %19 : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
-    %361 = flow.variable.load.indirect %18 : !util.ptr<tensor<1x1x64x256xf32>> -> tensor<1x1x64x256xf32>
-    %362 = flow.variable.load.indirect %35 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %363 = flow.variable.load.indirect %34 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %364 = flow.variable.load.indirect %33 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %365 = flow.variable.load.indirect %32 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %366 = flow.variable.load.indirect %31 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %367 = flow.variable.load.indirect %30 : !util.ptr<tensor<1x1x256x64xf32>> -> tensor<1x1x256x64xf32>
-    %368 = flow.variable.load.indirect %41 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %369 = flow.variable.load.indirect %40 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %370 = flow.variable.load.indirect %39 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %371 = flow.variable.load.indirect %38 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %372 = flow.variable.load.indirect %37 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %373 = flow.variable.load.indirect %36 : !util.ptr<tensor<3x3x64x64xf32>> -> tensor<3x3x64x64xf32>
-    %374 = flow.variable.load.indirect %47 : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
-    %375 = flow.variable.load.indirect %46 : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
-    %376 = flow.variable.load.indirect %45 : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
-    %377 = flow.variable.load.indirect %44 : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
-    %378 = flow.variable.load.indirect %43 : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
-    %379 = flow.variable.load.indirect %42 : !util.ptr<tensor<1x1x64x256xf32>> -> tensor<1x1x64x256xf32>
-    %380 = flow.variable.load.indirect %53 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %381 = flow.variable.load.indirect %52 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %382 = flow.variable.load.indirect %51 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %383 = flow.variable.load.indirect %50 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %384 = flow.variable.load.indirect %49 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %385 = flow.variable.load.indirect %48 : !util.ptr<tensor<1x1x256x64xf32>> -> tensor<1x1x256x64xf32>
-    %386 = flow.variable.load.indirect %59 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %387 = flow.variable.load.indirect %58 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %388 = flow.variable.load.indirect %57 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %389 = flow.variable.load.indirect %56 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %390 = flow.variable.load.indirect %55 : !util.ptr<tensor<64xf32>> -> tensor<64xf32>
-    %391 = flow.variable.load.indirect %54 : !util.ptr<tensor<3x3x64x64xf32>> -> tensor<3x3x64x64xf32>
-    %392 = flow.variable.load.indirect %65 : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
-    %393 = flow.variable.load.indirect %64 : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
-    %394 = flow.variable.load.indirect %63 : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
-    %395 = flow.variable.load.indirect %62 : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
-    %396 = flow.variable.load.indirect %61 : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
-    %397 = flow.variable.load.indirect %60 : !util.ptr<tensor<1x1x64x256xf32>> -> tensor<1x1x64x256xf32>
-    %398 = flow.variable.load.indirect %85 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %399 = flow.variable.load.indirect %84 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %400 = flow.variable.load.indirect %83 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %401 = flow.variable.load.indirect %82 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %402 = flow.variable.load.indirect %81 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %403 = flow.variable.load.indirect %80 : !util.ptr<tensor<1x1x256x512xf32>> -> tensor<1x1x256x512xf32>
-    %404 = flow.variable.load.indirect %71 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %405 = flow.variable.load.indirect %70 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %406 = flow.variable.load.indirect %69 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %407 = flow.variable.load.indirect %68 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %408 = flow.variable.load.indirect %67 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %409 = flow.variable.load.indirect %66 : !util.ptr<tensor<1x1x256x128xf32>> -> tensor<1x1x256x128xf32>
-    %410 = flow.variable.load.indirect %77 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %411 = flow.variable.load.indirect %76 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %412 = flow.variable.load.indirect %75 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %413 = flow.variable.load.indirect %74 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %414 = flow.variable.load.indirect %73 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %415 = flow.variable.load.indirect %72 : !util.ptr<tensor<3x3x128x128xf32>> -> tensor<3x3x128x128xf32>
-    %416 = flow.variable.load.indirect %89 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %417 = flow.variable.load.indirect %88 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %418 = flow.variable.load.indirect %87 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %419 = flow.variable.load.indirect %86 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %420 = flow.variable.load.indirect %79 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %421 = flow.variable.load.indirect %78 : !util.ptr<tensor<1x1x128x512xf32>> -> tensor<1x1x128x512xf32>
-    %422 = flow.variable.load.indirect %95 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %423 = flow.variable.load.indirect %94 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %424 = flow.variable.load.indirect %93 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %425 = flow.variable.load.indirect %92 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %426 = flow.variable.load.indirect %91 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %427 = flow.variable.load.indirect %90 : !util.ptr<tensor<1x1x512x128xf32>> -> tensor<1x1x512x128xf32>
-    %428 = flow.variable.load.indirect %101 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %429 = flow.variable.load.indirect %100 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %430 = flow.variable.load.indirect %99 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %431 = flow.variable.load.indirect %98 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %432 = flow.variable.load.indirect %97 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %433 = flow.variable.load.indirect %96 : !util.ptr<tensor<3x3x128x128xf32>> -> tensor<3x3x128x128xf32>
-    %434 = flow.variable.load.indirect %107 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %435 = flow.variable.load.indirect %106 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %436 = flow.variable.load.indirect %105 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %437 = flow.variable.load.indirect %104 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %438 = flow.variable.load.indirect %103 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %439 = flow.variable.load.indirect %102 : !util.ptr<tensor<1x1x128x512xf32>> -> tensor<1x1x128x512xf32>
-    %440 = flow.variable.load.indirect %113 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %441 = flow.variable.load.indirect %112 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %442 = flow.variable.load.indirect %111 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %443 = flow.variable.load.indirect %110 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %444 = flow.variable.load.indirect %109 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %445 = flow.variable.load.indirect %108 : !util.ptr<tensor<1x1x512x128xf32>> -> tensor<1x1x512x128xf32>
-    %446 = flow.variable.load.indirect %119 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %447 = flow.variable.load.indirect %118 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %448 = flow.variable.load.indirect %117 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %449 = flow.variable.load.indirect %116 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %450 = flow.variable.load.indirect %115 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %451 = flow.variable.load.indirect %114 : !util.ptr<tensor<3x3x128x128xf32>> -> tensor<3x3x128x128xf32>
-    %452 = flow.variable.load.indirect %125 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %453 = flow.variable.load.indirect %124 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %454 = flow.variable.load.indirect %123 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %455 = flow.variable.load.indirect %122 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %456 = flow.variable.load.indirect %121 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %457 = flow.variable.load.indirect %120 : !util.ptr<tensor<1x1x128x512xf32>> -> tensor<1x1x128x512xf32>
-    %458 = flow.variable.load.indirect %131 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %459 = flow.variable.load.indirect %130 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %460 = flow.variable.load.indirect %129 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %461 = flow.variable.load.indirect %128 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %462 = flow.variable.load.indirect %127 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %463 = flow.variable.load.indirect %126 : !util.ptr<tensor<1x1x512x128xf32>> -> tensor<1x1x512x128xf32>
-    %464 = flow.variable.load.indirect %137 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %465 = flow.variable.load.indirect %136 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %466 = flow.variable.load.indirect %135 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %467 = flow.variable.load.indirect %134 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %468 = flow.variable.load.indirect %133 : !util.ptr<tensor<128xf32>> -> tensor<128xf32>
-    %469 = flow.variable.load.indirect %132 : !util.ptr<tensor<3x3x128x128xf32>> -> tensor<3x3x128x128xf32>
-    %470 = flow.variable.load.indirect %143 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %471 = flow.variable.load.indirect %142 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %472 = flow.variable.load.indirect %141 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %473 = flow.variable.load.indirect %140 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %474 = flow.variable.load.indirect %139 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
-    %475 = flow.variable.load.indirect %138 : !util.ptr<tensor<1x1x128x512xf32>> -> tensor<1x1x128x512xf32>
-    %476 = flow.variable.load.indirect %163 : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
-    %477 = flow.variable.load.indirect %162 : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
-    %478 = flow.variable.load.indirect %161 : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
-    %479 = flow.variable.load.indirect %160 : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
-    %480 = flow.variable.load.indirect %159 : !util.ptr<tensor<1024xf32>> -> tensor<1024xf32>
-    %481 = flow.variable.load.indirect %158 : !util.ptr<tensor<1x1x512x1024xf32>> -> tensor<1x1x512x1024xf32>
-    %482 = flow.variable.load.indirect %149 : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
-    %483 = flow.variable.load.indirect %148 : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
-    %484 = flow.variable.load.indirect %147 : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
-    %485 = flow.variable.load.indirect %146 : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
-    %486 = flow.variable.load.indirect %145 : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
-    %487 = flow.variable.load.indirect %144 : !util.ptr<tensor<1x1x512x256xf32>> -> tensor<1x1x512x256xf32>
-    %488 = flow.variable.load.indirect %155 : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
-    %489 = flow.variable.load.indirect %154 : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
-    %490 = flow.variable.load.indirect %153 : !util.ptr<tensor<256xf32>> -> tensor<256xf32>
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+    %593 = util.global.load.indirect %274 : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
+    %594 = util.global.load.indirect %273 : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
+    %595 = util.global.load.indirect %272 : !util.ptr<tensor<1x1x1024x2048xf32>> -> tensor<1x1x1024x2048xf32>
+    %596 = util.global.load.indirect %263 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %597 = util.global.load.indirect %262 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %598 = util.global.load.indirect %261 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %599 = util.global.load.indirect %260 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %600 = util.global.load.indirect %259 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %601 = util.global.load.indirect %258 : !util.ptr<tensor<1x1x1024x512xf32>> -> tensor<1x1x1024x512xf32>
+    %602 = util.global.load.indirect %269 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %603 = util.global.load.indirect %268 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %604 = util.global.load.indirect %267 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %605 = util.global.load.indirect %266 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %606 = util.global.load.indirect %265 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %607 = util.global.load.indirect %264 : !util.ptr<tensor<3x3x512x512xf32>> -> tensor<3x3x512x512xf32>
+    %608 = util.global.load.indirect %281 : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
+    %609 = util.global.load.indirect %280 : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
+    %610 = util.global.load.indirect %279 : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
+    %611 = util.global.load.indirect %278 : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
+    %612 = util.global.load.indirect %271 : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
+    %613 = util.global.load.indirect %270 : !util.ptr<tensor<1x1x512x2048xf32>> -> tensor<1x1x512x2048xf32>
+    %614 = util.global.load.indirect %287 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %615 = util.global.load.indirect %286 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %616 = util.global.load.indirect %285 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %617 = util.global.load.indirect %284 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %618 = util.global.load.indirect %283 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %619 = util.global.load.indirect %282 : !util.ptr<tensor<1x1x2048x512xf32>> -> tensor<1x1x2048x512xf32>
+    %620 = util.global.load.indirect %293 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %621 = util.global.load.indirect %292 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %622 = util.global.load.indirect %291 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %623 = util.global.load.indirect %290 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %624 = util.global.load.indirect %289 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %625 = util.global.load.indirect %288 : !util.ptr<tensor<3x3x512x512xf32>> -> tensor<3x3x512x512xf32>
+    %626 = util.global.load.indirect %299 : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
+    %627 = util.global.load.indirect %298 : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
+    %628 = util.global.load.indirect %297 : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
+    %629 = util.global.load.indirect %296 : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
+    %630 = util.global.load.indirect %295 : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
+    %631 = util.global.load.indirect %294 : !util.ptr<tensor<1x1x512x2048xf32>> -> tensor<1x1x512x2048xf32>
+    %632 = util.global.load.indirect %305 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %633 = util.global.load.indirect %304 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %634 = util.global.load.indirect %303 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %635 = util.global.load.indirect %302 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %636 = util.global.load.indirect %301 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %637 = util.global.load.indirect %300 : !util.ptr<tensor<1x1x2048x512xf32>> -> tensor<1x1x2048x512xf32>
+    %638 = util.global.load.indirect %311 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %639 = util.global.load.indirect %310 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %640 = util.global.load.indirect %309 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %641 = util.global.load.indirect %308 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %642 = util.global.load.indirect %307 : !util.ptr<tensor<512xf32>> -> tensor<512xf32>
+    %643 = util.global.load.indirect %306 : !util.ptr<tensor<3x3x512x512xf32>> -> tensor<3x3x512x512xf32>
+    %644 = util.global.load.indirect %317 : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
+    %645 = util.global.load.indirect %316 : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
+    %646 = util.global.load.indirect %315 : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
+    %647 = util.global.load.indirect %314 : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
+    %648 = util.global.load.indirect %313 : !util.ptr<tensor<2048xf32>> -> tensor<2048xf32>
+    %649 = util.global.load.indirect %312 : !util.ptr<tensor<1x1x512x2048xf32>> -> tensor<1x1x512x2048xf32>
+    %650 = util.global.load.indirect %319 : !util.ptr<tensor<1000xf32>> -> tensor<1000xf32>
+    %651 = util.global.load.indirect %318 : !util.ptr<tensor<2048x1000xf32>> -> tensor<2048x1000xf32>
     %652 = "mhlo.pad"(%arg0, %331) {edge_padding_high = dense<[0, 3, 3, 0]> : tensor<4xi64>, edge_padding_low = dense<[0, 3, 3, 0]> : tensor<4xi64>, interior_padding = dense<0> : tensor<4xi64>} : (tensor<1x224x224x3xf32>, tensor<f32>) -> tensor<1x230x230x3xf32>
     %653 = "mhlo.convolution"(%652, %337) {batch_group_count = 1 : i64, dimension_numbers = {input_batch_dimension = 0 : i64, input_feature_dimension = 3 : i64, input_spatial_dimensions = dense<[1, 2]> : tensor<2xi64>, kernel_input_feature_dimension = 2 : i64, kernel_output_feature_dimension = 3 : i64, kernel_spatial_dimensions = dense<[0, 1]> : tensor<2xi64>, output_batch_dimension = 0 : i64, output_feature_dimension = 3 : i64, output_spatial_dimensions = dense<[1, 2]> : tensor<2xi64>}, feature_group_count = 1 : i64, padding = dense<0> : tensor<2x2xi64>, rhs_dilation = dense<1> : tensor<2xi64>, window_strides = dense<2> : tensor<2xi64>} : (tensor<1x230x230x3xf32>, tensor<7x7x3x64xf32>) -> tensor<1x112x112x64xf32>
     %654 = "mhlo.broadcast_in_dim"(%336) {broadcast_dimensions = dense<3> : tensor<1xi64>} : (tensor<64xf32>) -> tensor<1x112x112x64xf32>
diff --git a/iree/test/e2e/regression/globals.mlir b/iree/test/e2e/regression/globals.mlir
index f4c58f2..1a20207 100644
--- a/iree/test/e2e/regression/globals.mlir
+++ b/iree/test/e2e/regression/globals.mlir
@@ -2,22 +2,22 @@
 // RUN: [[ $IREE_VULKAN_DISABLE == 1 ]] || (iree-run-mlir --iree-input-type=mhlo -iree-hal-target-backends=vulkan-spirv %s | IreeFileCheck %s)
 
 module {
-  flow.variable @counter mutable dense<2.0> : tensor<f32>
+  util.global private mutable @counter = dense<2.0> : tensor<f32>
 
   // CHECK: EXEC @get_state
   func @get_state() -> tensor<f32> {
-    %0 = flow.variable.load @counter : tensor<f32>
+    %0 = util.global.load @counter : tensor<f32>
     return %0 : tensor<f32>
   }
   // CHECK: f32=2
 
   // CHECK: EXEC @inc
   func @inc() -> tensor<f32> {
-    %0 = flow.variable.load @counter : tensor<f32>
+    %0 = util.global.load @counter : tensor<f32>
     %c1 = constant dense<1.0> : tensor<f32>
     %1 = mhlo.add %0, %c1 : tensor<f32>
-    flow.variable.store %1, @counter : tensor<f32>
-    %2 = flow.variable.load @counter : tensor<f32>
+    util.global.store %1, @counter : tensor<f32>
+    %2 = util.global.load @counter : tensor<f32>
     return %2 : tensor<f32>
   }
   // CHECK: f32=3
diff --git a/llvm-external-projects/iree-dialects/include/iree-dialects/Dialect/IREE/IREEBase.td b/llvm-external-projects/iree-dialects/include/iree-dialects/Dialect/IREE/IREEBase.td
index 09e655e..3194b51 100644
--- a/llvm-external-projects/iree-dialects/include/iree-dialects/Dialect/IREE/IREEBase.td
+++ b/llvm-external-projects/iree-dialects/include/iree-dialects/Dialect/IREE/IREEBase.td
@@ -92,8 +92,8 @@
 def IREE_Shape : Variadic<IREE_Dim>;
 def IREE_ShapeDynamicDims : Variadic<IREE_Dim>;
 
-def IREE_VariableRefAttr : IREE_AliasedSymbolRefAttr;
-def IREE_VariablePtr : IREE_AnyPtrOf<[IREE_Tensor, IREE_PrimitiveType]>;
+def IREE_GlobalRefAttr : IREE_AliasedSymbolRefAttr;
+def IREE_AnyGlobalPtr : IREE_AnyPtrOf<[IREE_Tensor, IREE_PrimitiveType]>;
 
 class IREE_IndexAttrBase<string descr> :
     TypedAttrBase<
diff --git a/llvm-external-projects/iree-dialects/include/iree-dialects/Dialect/IREE/IREEOps.td b/llvm-external-projects/iree-dialects/include/iree-dialects/Dialect/IREE/IREEOps.td
index 608353b..41774ff 100644
--- a/llvm-external-projects/iree-dialects/include/iree-dialects/Dialect/IREE/IREEOps.td
+++ b/llvm-external-projects/iree-dialects/include/iree-dialects/Dialect/IREE/IREEOps.td
@@ -62,108 +62,121 @@
 // Global variables
 //===----------------------------------------------------------------------===//
 
-def IREE_VariableOp : IREE_Op<"variable", [
+def IREE_GlobalOp : IREE_Op<"global", [
     Symbol,
   ]> {
-  let summary = [{stateful variable declaration}];
+  let summary = [{stateful global variable declaration}];
   let description = [{
-    Declares a persistent variable that maintains its value.
+    Declares a global variable that maintains its value across invocations.
+    The value is tied to the execution context of the module and different
+    contexts will have different global storage.
   }];
 
   let arguments = (ins
-    StrAttr:$sym_name,
+    OptionalAttr<StrAttr>:$sym_visibility,
+    SymbolNameAttr:$sym_name,
     TypeAttr:$type,
     UnitAttr:$is_mutable,
     OptionalAttr<FlatSymbolRefAttr>:$initializer,
     OptionalAttr<AnyAttr>:$initial_value
   );
 
-  let skipDefaultBuilders = 1;
-  let builders = [
-    OpBuilder<(ins "StringRef":$name, "bool":$isMutable,
-      "FuncOp":$initializer, CArg<"ArrayRef<NamedAttribute>", "{}">:$attrs)>,
-    OpBuilder<(ins "StringRef":$name, "bool":$isMutable, "Type":$type,
-      "Attribute":$initialValue, CArg<"ArrayRef<NamedAttribute>", "{}">:$attrs)>,
-    OpBuilder<(ins "StringRef":$name, "bool":$isMutable, "Type":$type,
-      CArg<"ArrayRef<NamedAttribute>", "{}">:$attrs)>,
-  ];
+  // TODO(laurenzo): copy SymbolVisibility/TypeOrAttr from UtilOps.cpp.
+  // let assemblyFormat = [{
+  //   custom<SymbolVisibility>($sym_visibility)
+  //   (`mutable` $is_mutable^)?
+  //   $sym_name
+  //   attr-dict
+  //   (`initializer` `(` $initializer^ `)`):(``)?
+  //   custom<TypeOrAttr>($type, $initial_value)
+  // }];
 }
 
-def IREE_VariableAddressOp : IREE_PureOp<"variable.address"> {
-  let summary = [{returns an address reference to a variable}];
+def IREE_GlobalAddressOp : IREE_PureOp<"global.address"> {
+  let summary = [{returns an address reference to a global}];
   let description = [{
-    Returns the address of a variable as a typed reference. Can be used with the
-    variable load and store indirect ops.
+    Returns the address of a global as a typed reference. Can be used with the
+    global load and store indirect ops.
   }];
 
   let arguments = (ins
-    IREE_VariableRefAttr:$variable
+    IREE_GlobalRefAttr:$global
   );
   let results = (outs
-    IREE_VariablePtr:$result
+    IREE_AnyGlobalPtr:$result
   );
 
-  let assemblyFormat = "$variable attr-dict `:` type($result)";
+  let assemblyFormat = [{
+    $global attr-dict `:` type($result)
+  }];
 }
 
-def IREE_VariableLoadOp : IREE_Op<"variable.load"> {
+def IREE_GlobalLoadOp : IREE_Op<"global.load"> {
   let summary = [{loads a value from a global variable}];
   let description = [{
-    Returns a copy of the variable value.
+    Returns a copy of the global value.
   }];
 
   let arguments = (ins
-    IREE_VariableRefAttr:$variable
+    IREE_GlobalRefAttr:$global
   );
   let results = (outs
     AnyType:$result
   );
 
-  let assemblyFormat = "$variable attr-dict `:` type($result)";
+  let assemblyFormat = [{
+    $global attr-dict `:` type($result)
+  }];
 }
 
-def IREE_VariableLoadIndirectOp : IREE_Op<"variable.load.indirect"> {
+def IREE_GlobalLoadIndirectOp : IREE_Op<"global.load.indirect"> {
   let summary = [{loads a value from a global variable}];
   let description = [{
-    Returns a copy of the variable value.
+    Returns a copy of the global value.
   }];
 
   let arguments = (ins
-    IREE_VariablePtr:$variable
+    IREE_AnyGlobalPtr:$global
   );
   let results = (outs
     AnyType:$result
   );
 
-  let assemblyFormat = "$variable attr-dict `:` type($variable) `->` type($result)";
+  let assemblyFormat = [{
+    $global attr-dict `:` type($global) `->` type($result)
+  }];
 }
 
-def IREE_VariableStoreOp : IREE_Op<"variable.store"> {
+def IREE_GlobalStoreOp : IREE_Op<"global.store"> {
   let summary = [{stores a value into a global variable}];
   let description = [{
-    Stores a copy of the value into a variable.
+    Stores a copy of the value into a global.
   }];
 
   let arguments = (ins
     AnyType:$value,
-    IREE_VariableRefAttr:$variable
+    IREE_GlobalRefAttr:$global
   );
 
-  let assemblyFormat = "$value `,` $variable attr-dict `:` type($value)";
+  let assemblyFormat = [{
+    $value `,` $global attr-dict `:` type($value)
+  }];
 }
 
-def IREE_VariableStoreIndirectOp : IREE_Op<"variable.store.indirect"> {
+def IREE_GlobalStoreIndirectOp : IREE_Op<"global.store.indirect"> {
   let summary = [{stores a value into a global variable}];
   let description = [{
-    Stores a copy of the value into a variable.
+    Stores a copy of the value into a global.
   }];
 
   let arguments = (ins
     AnyType:$value,
-    IREE_VariablePtr:$variable
+    IREE_AnyGlobalPtr:$global
   );
 
-  let assemblyFormat = "$value `,` $variable attr-dict `:` type($value) `->` type($variable)";
+  let assemblyFormat = [{
+    $value `,` $global attr-dict `:` type($value) `->` type($global)
+  }];
 }
 
 //===----------------------------------------------------------------------===//