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// Copyright 2019 Google LLC
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
// https://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
#include "iree_tf_compiler/TF/Passes.h"
#include "iree/compiler/Dialect/Shape/Conversion/Passes.h"
#include "iree/compiler/Dialect/Shape/Transforms/Passes.h"
#include "iree_tf_compiler/dialect/tf_strings/ir/dialect.h"
#include "iree_tf_compiler/dialect/tf_tensorlist/ir/tf_tensorlist_dialect.h"
#include "mlir/Dialect/Shape/Transforms/Passes.h"
#include "mlir/Pass/PassManager.h"
#include "mlir/Pass/PassRegistry.h"
#include "mlir/Transforms/Passes.h"
#include "tensorflow/compiler/mlir/tensorflow/transforms/passes.h"
#include "tensorflow/compiler/mlir/tensorflow/transforms/tf_saved_model_passes.h"
namespace mlir {
namespace iree_integrations {
namespace TF {
void registerAllDialects(mlir::DialectRegistry &registry) {
registry.insert<tf_strings::TFStringsDialect>();
registry.insert<tf_tensorlist::TFTensorListDialect>();
}
// All IREE-specific passes that lower TF representations before reaching the
// IREE core should go here.
void buildTFImportPassPipeline(OpPassManager &pm) {
//----------------------------------------------------------------------------
// Clean up tf_executor and extraneous unused functions.
//----------------------------------------------------------------------------
pm.addPass(createSymbolDCEPass());
pm.addPass(tf_executor::CreateTFExecutorGraphPruningPass());
pm.addPass(::mlir::TF::CreateGuaranteeAllFuncsOneUsePass());
::mlir::TF::CreateTFStandardPipeline(pm,
::mlir::TF::StandardPipelineOptions());
pm.addPass(::mlir::TF::CreateDeviceIndexSelectorPass());
//----------------------------------------------------------------------------
// Try to get the IR in good condition.
//----------------------------------------------------------------------------
pm.addPass(createInlinerPass());
pm.addPass(createCanonicalizerPass());
pm.addPass(TFDevice::CreateDecomposeResourceOpsPass());
pm.addPass(createPropagateResourceCastsPass());
pm.addPass(::mlir::TF::CreateTFShapeInferencePass());
//----------------------------------------------------------------------------
// Lower to CFG.
// After this point, most TF optimizations won't work properly besides
// simple canonicalizations.
//----------------------------------------------------------------------------
pm.addPass(::mlir::TF::CreateTFFunctionalControlFlowToCFG());
// Inline, as tf-functional-control-flow-to-cfg leaves in calls.
pm.addPass(createInlinerPass());
//----------------------------------------------------------------------------
// Some further cleanups now that control flow is in better shape.
//----------------------------------------------------------------------------
pm.addPass(createSymbolDCEPass());
pm.addPass(createCanonicalizerPass());
//----------------------------------------------------------------------------
// Lowering module specific TF behavior to intermediate dialects.
//----------------------------------------------------------------------------
pm.addPass(tf_strings::createConvertTFToTFStringsPass());
pm.addPass(tf_tensorlist::createConvertTFToTFTensorListPass());
//----------------------------------------------------------------------------
// Legalize to XLA
//----------------------------------------------------------------------------
pm.addPass(createConvertToMHLOPass());
pm.addPass(createCanonicalizerPass());
//----------------------------------------------------------------------------
// Now that the IR is starting to look nice, optimize global tensors.
//----------------------------------------------------------------------------
pm.addPass(tf_saved_model::CreateOptimizeGlobalTensorsPass());
//----------------------------------------------------------------------------
// Lowering shape-related constructs.
//----------------------------------------------------------------------------
pm.addPass(iree_compiler::Shape::createConvertHLOToShapePass());
// TODO(GH-2277): Lower HLO shape constraints instead of eliding them here.
pm.addPass(createRemoveShapeConstraintsPass());
pm.addPass(createCanonicalizerPass());
pm.addPass(iree_compiler::Shape::createConvertShapeToShapexPass());
pm.addPass(createCanonicalizerPass());
//----------------------------------------------------------------------------
// Lowering intermediate dialects to module specific dialects.
//----------------------------------------------------------------------------
pm.addPass(tf_strings::createConvertTFStringsToStringsPass());
pm.addPass(tf_tensorlist::createConvertTFTensorListToTensorListPass());
//----------------------------------------------------------------------------
// Lowering tf_saved_model dialect to IREE dialects
//----------------------------------------------------------------------------
// First, eliminate tf_saved_model.global_tensor's and corresponding
// tf_saved_model.bound_input's.
pm.addPass(createLowerGlobalTensorsPass());
// Lower exported functions.
//
// This pass must run second because:
// - It assumes that tf_saved_model.bound_inputs have been eliminated
// - It removes tf_saved_model.semantics from the module, which we can only
// do at the very end.
pm.addPass(createLowerExportedFunctionsPass());
//----------------------------------------------------------------------------
// Ensure that all Tensorflow has been legalized away
//----------------------------------------------------------------------------
pm.addPass(createStripModuleMetadataPass());
pm.nest<ModuleOp>().addPass(createStripFunctionMetadataPass());
pm.addPass(createVerifyFullyConvertedPass());
////////////////////////////////////////////////////////////////////////////
// Temporary: Does some special case fixups of HLO ops with dynamic
// shapes until these can be done properly upstream.
////////////////////////////////////////////////////////////////////////////
pm.addPass(iree_compiler::Shape::createConvertHLOToShapePass());
}
void registerTFImportPassPipeline() {
mlir::PassPipelineRegistration<> pipeline(
"iree-tf-import-pipeline",
"Run IREE-specific passes for importing TF code into IREE",
[](OpPassManager &passManager) {
buildTFImportPassPipeline(passManager);
});
}
} // namespace TF
} // namespace iree_integrations
} // namespace mlir