Fix error in bufferization analysis. (#8134)
Check if a value is part of the equivalence set before checking if it
has a leader.
diff --git a/integrations/tensorflow/test/iree_tf_tests/math/llvmaot__complex_cumprod.run b/integrations/tensorflow/test/iree_tf_tests/math/llvmaot__complex_cumprod.run
index 7aee027..2632fa1 100644
--- a/integrations/tensorflow/test/iree_tf_tests/math/llvmaot__complex_cumprod.run
+++ b/integrations/tensorflow/test/iree_tf_tests/math/llvmaot__complex_cumprod.run
@@ -1,3 +1,2 @@
-# XFAIL: *
# REQUIRES: llvmaot
# RUN: %PYTHON -m iree_tf_tests.math.math_test --target_backends=iree_llvmaot --dynamic_dims=false --functions=cumprod -artifacts_dir=%t
diff --git a/integrations/tensorflow/test/iree_tf_tests/math/llvmaot__complex_cumsum.run b/integrations/tensorflow/test/iree_tf_tests/math/llvmaot__complex_cumsum.run
index dd4d33a..76fdcf1 100644
--- a/integrations/tensorflow/test/iree_tf_tests/math/llvmaot__complex_cumsum.run
+++ b/integrations/tensorflow/test/iree_tf_tests/math/llvmaot__complex_cumsum.run
@@ -1,3 +1,2 @@
-# XFAIL: *
# REQUIRES: llvmaot
# RUN: %PYTHON -m iree_tf_tests.math.math_test --target_backends=iree_llvmaot --dynamic_dims=false --functions=cumsum -artifacts_dir=%t
diff --git a/integrations/tensorflow/test/iree_tf_tests/math/llvmaot__cumprod.run b/integrations/tensorflow/test/iree_tf_tests/math/llvmaot__cumprod.run
index 7aee027..2632fa1 100644
--- a/integrations/tensorflow/test/iree_tf_tests/math/llvmaot__cumprod.run
+++ b/integrations/tensorflow/test/iree_tf_tests/math/llvmaot__cumprod.run
@@ -1,3 +1,2 @@
-# XFAIL: *
# REQUIRES: llvmaot
# RUN: %PYTHON -m iree_tf_tests.math.math_test --target_backends=iree_llvmaot --dynamic_dims=false --functions=cumprod -artifacts_dir=%t
diff --git a/integrations/tensorflow/test/iree_tf_tests/math/llvmaot__cumsum.run b/integrations/tensorflow/test/iree_tf_tests/math/llvmaot__cumsum.run
index dd4d33a..76fdcf1 100644
--- a/integrations/tensorflow/test/iree_tf_tests/math/llvmaot__cumsum.run
+++ b/integrations/tensorflow/test/iree_tf_tests/math/llvmaot__cumsum.run
@@ -1,3 +1,2 @@
-# XFAIL: *
# REQUIRES: llvmaot
# RUN: %PYTHON -m iree_tf_tests.math.math_test --target_backends=iree_llvmaot --dynamic_dims=false --functions=cumsum -artifacts_dir=%t
diff --git a/iree/compiler/Codegen/Common/BufferizationAnalysis.h b/iree/compiler/Codegen/Common/BufferizationAnalysis.h
index 80c6c16..e324eeb 100644
--- a/iree/compiler/Codegen/Common/BufferizationAnalysis.h
+++ b/iree/compiler/Codegen/Common/BufferizationAnalysis.h
@@ -64,13 +64,22 @@
/// Queries if the value `v` is in the same equivalence class as the result of
/// the dispatch region.
- bool isInStoreSet(Value v) { return storeLeaders.count(getLeaderValue(v)); }
+ bool isInStoreSet(Value v) {
+ Value leader = getLeaderValue(v);
+ if (!leader) return false;
+ return storeLeaders.count(leader);
+ }
void dump();
private:
Value getLeaderValue(Value v1) const {
- return getValue(mappedTensors.getLeaderValue(getPointer(v1)));
+ void *ptr = getPointer(v1);
+ auto it = mappedTensors.findLeader(ptr);
+ if (it == mappedTensors.member_end()) {
+ return nullptr;
+ }
+ return getValue(*it);
}
void *getPointer(Value v) const { return v.getAsOpaquePointer(); }
diff --git a/iree/compiler/Codegen/Common/test/convert_to_destination_passing_style.mlir b/iree/compiler/Codegen/Common/test/convert_to_destination_passing_style.mlir
index 008b92d..2df64a0 100644
--- a/iree/compiler/Codegen/Common/test/convert_to_destination_passing_style.mlir
+++ b/iree/compiler/Codegen/Common/test/convert_to_destination_passing_style.mlir
@@ -399,3 +399,72 @@
// CHECK-SAME: outs(%[[RESULT0_TILE]], %[[RESULT1_TILE]]
// CHECK: flow.dispatch.tensor.store %[[GENERIC_TILE]]#0, %[[RESULT0]]
// CHECK: flow.dispatch.tensor.store %[[GENERIC_TILE]]#1, %[[RESULT1]]
+
+// -----
+
+func @unused_ins_operand() {
+ %c64 = arith.constant 64 : index
+ %c32 = arith.constant 32 : index
+ %c0 = arith.constant 0 : index
+ %0 = hal.interface.constant.load[0] : i32
+ %1 = hal.interface.constant.load[1] : i32
+ %2 = hal.interface.constant.load[2] : i32
+ %3 = hal.interface.constant.load[3] : i32
+ %4 = hal.interface.constant.load[4] : i32
+ %5 = hal.interface.constant.load[5] : i32
+ %6 = arith.index_cast %0 : i32 to index
+ %7 = arith.index_cast %1 : i32 to index
+ %8 = arith.index_cast %2 : i32 to index
+ %9 = arith.index_cast %3 : i32 to index
+ %10 = arith.index_cast %4 : i32 to index
+ %11 = arith.index_cast %5 : i32 to index
+ %12 = hal.interface.binding.subspan set(0) binding(0) type(storage_buffer) offset(%c32) alignment(32) : !flow.dispatch.tensor<readonly:?x?x?xi32>{%6, %7, %8}
+ %13 = hal.interface.binding.subspan set(0) binding(1) type(storage_buffer) offset(%c64) alignment(32) : !flow.dispatch.tensor<readonly:?x?x?xi32>{%9, %10, %11}
+ %14 = hal.interface.binding.subspan set(0) binding(2) type(storage_buffer) offset(%c0) alignment(32) : !flow.dispatch.tensor<writeonly:?x?x?xi32>{%9, %10, %8}
+ %15 = flow.dispatch.tensor.load %13, offsets = [0, 0, 0], sizes = [%9, %10, %11], strides = [1, 1, 1] : !flow.dispatch.tensor<readonly:?x?x?xi32>{%9, %10, %11} -> tensor<?x?x?xi32>
+ %workgroup_id_x = hal.interface.workgroup.id[0] : index
+ %workgroup_count_x = hal.interface.workgroup.count[0] : index
+ %workgroup_id_y = hal.interface.workgroup.id[1] : index
+ %workgroup_count_y = hal.interface.workgroup.count[1] : index
+ %workgroup_id_z = hal.interface.workgroup.id[2] : index
+ %workgroup_count_z = hal.interface.workgroup.count[2] : index
+ %16 = affine.apply affine_map<()[s0] -> (s0 * 64)>()[%workgroup_id_z]
+ %17 = affine.apply affine_map<()[s0] -> (s0 * 64)>()[%workgroup_count_z]
+ scf.for %arg0 = %16 to %6 step %17 {
+ %18 = affine.apply affine_map<()[s0] -> (s0 * 64)>()[%workgroup_id_y]
+ %19 = affine.apply affine_map<()[s0] -> (s0 * 64)>()[%workgroup_count_y]
+ scf.for %arg1 = %18 to %7 step %19 {
+ %20 = affine.apply affine_map<()[s0] -> (s0 * 64)>()[%workgroup_id_x]
+ %21 = affine.apply affine_map<()[s0] -> (s0 * 64)>()[%workgroup_count_x]
+ scf.for %arg2 = %20 to %8 step %21 {
+ %22 = affine.min affine_map<(d0)[s0] -> (64, -d0 + s0)>(%arg0)[%6]
+ %23 = affine.min affine_map<(d0)[s0] -> (64, -d0 + s0)>(%arg1)[%7]
+ %24 = affine.min affine_map<(d0)[s0] -> (64, -d0 + s0)>(%arg2)[%8]
+ %25 = flow.dispatch.tensor.load %12, offsets = [%arg0, %arg1, %arg2], sizes = [%22, %23, %24], strides = [1, 1, 1] : !flow.dispatch.tensor<readonly:?x?x?xi32>{%6, %7, %8} -> tensor<?x?x?xi32>
+ %26 = linalg.init_tensor [%22, %23] : tensor<?x?xi32>
+ %27 = linalg.init_tensor [%22, %23, %24] : tensor<?x?x?xi32>
+ %28 = linalg.generic {indexing_maps = [affine_map<(d0, d1, d2) -> (d0, d1, d2)>, affine_map<(d0, d1, d2) -> (d0, d1)>, affine_map<(d0, d1, d2) -> (d0, d1, d2)>], iterator_types = ["parallel", "parallel", "parallel"]} ins(%25, %26 : tensor<?x?x?xi32>, tensor<?x?xi32>) outs(%27 : tensor<?x?x?xi32>) attrs = {lowering.config = #iree_codegen.lowering.config<tile_sizes = [[], [1, 4, 4]], native_vector_size = [1, 4, 4]>} {
+ ^bb0(%arg3: i32, %arg4: i32, %arg5: i32): // no predecessors
+ %29 = arith.index_cast %arg3 : i32 to index
+ %30 = linalg.index 0 : index
+ %31 = affine.apply affine_map<(d0, d1) -> (d0 + d1)>(%30, %arg0)
+ %32 = linalg.index 1 : index
+ %33 = affine.apply affine_map<(d0, d1) -> (d0 + d1)>(%32, %arg1)
+ %34 = tensor.extract %15[%31, %33, %29] : tensor<?x?x?xi32>
+ linalg.yield %34 : i32
+ } -> tensor<?x?x?xi32>
+ flow.dispatch.tensor.store %28, %14, offsets = [%arg0, %arg1, %arg2], sizes = [%22, %23, %24], strides = [1, 1, 1] : tensor<?x?x?xi32> -> !flow.dispatch.tensor<writeonly:?x?x?xi32>{%9, %10, %8}
+ }
+ }
+ }
+ return
+}
+// CHECK-LABEL: func @unused_ins_operand()
+// CHECK-DAG: %[[IN:.+]] = hal.interface.binding.subspan set(0) binding(0)
+// CHECK-DAG: %[[OUT:.+]] = hal.interface.binding.subspan set(0) binding(2)
+// CHECK-DAG: %[[IN_VIEW:.+]] = flow.dispatch.tensor.load %[[IN]]
+// CHECK-DAG: %[[OUT_VIEW:.+]] = flow.dispatch.tensor.load %[[OUT]]
+// CHECK-DAG: %[[INIT:.+]] = linalg.init_tensor
+// CHECK: linalg.generic
+// CHECK-SAME: ins(%[[IN_VIEW]], %[[INIT]]
+// CHECK-SAME: outs(%[[OUT_VIEW]]
