106 lines
3.9 KiB
C++
106 lines
3.9 KiB
C++
/* Copyright 2019 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#ifndef TENSORFLOW_COMPILER_MLIR_HLO_INCLUDE_MLIR_HLO_DIALECT_MHLO_TRANSFORMS_PASSES_H_
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#define TENSORFLOW_COMPILER_MLIR_HLO_INCLUDE_MLIR_HLO_DIALECT_MHLO_TRANSFORMS_PASSES_H_
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#include <memory>
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#include "third_party/llvm/llvm-project/llvm/include/llvm/ADT/ArrayRef.h"
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namespace mlir {
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class FuncOp;
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class ModuleOp;
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class Operation;
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template <typename T>
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class OperationPass;
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class Pass;
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namespace mhlo {
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/// Lowers HLO control flow ops to the Standard dialect.
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std::unique_ptr<OperationPass<FuncOp>> createLegalizeControlFlowPass();
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/// Lowers from HLO dialect to Standard dialect.
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std::unique_ptr<OperationPass<FuncOp>> createLegalizeToStdPass();
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/// Lowers from HLO dialect to LHLO dialect allocating/deallocating temporary
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/// buffers if necessary. If `results_escape_functions` is set to true,
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/// allocated buffers for function results will be returned and escape the
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/// function. Otherwise, the signature is rewritten with extra arguments for the
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/// buffers that are to be used for results.
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std::unique_ptr<OperationPass<ModuleOp>> createLegalizeToLhloPass(
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bool results_escape_functions = false);
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// Lowers from HLO dialect to Linalg dialect.
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std::unique_ptr<OperationPass<FuncOp>> createLegalizeHloToLinalgPass();
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// Transforms unranked HLO operations to ranked ones where possible.
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std::unique_ptr<OperationPass<FuncOp>> createTransformUnrankedHloPass();
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// Sinks constants implicitly captured in control flow regions. This is
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// necessary to export to XLA.
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std::unique_ptr<OperationPass<FuncOp>> createSinkConstantsToControlFlowPass();
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// fuse mhlo ops to kLoop/kInput fusion patterns
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std::unique_ptr<OperationPass<FuncOp>> createMhloFusionPass();
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} // namespace mhlo
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namespace lmhlo {
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// Lowers from LHLO dialect to Affine dialect.
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std::unique_ptr<OperationPass<FuncOp>> createLegalizeToAffinePass();
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// Lowers from LHLO dialect to Linalg dialect.
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std::unique_ptr<OperationPass<FuncOp>> createLegalizeLhloToLinalgPass();
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// Lowers from LHLO dialect to GPU dialect.
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std::unique_ptr<OperationPass<FuncOp>> createLegalizeToGpuPass();
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// Fuses linalg ops obtained after LHLO lowering. To enable fusion,
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// operations are first tiled.
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//
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// When 'use_parallel_loops' is set, the tiling will use scf.parallel
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// operations. Otherwise, scf.for operations are used.
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//
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// 'tile_sizes' provides the tile sizes to use for tiling. If the linalg
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// operation has more dimensions than tile sizes provided, 1 is used as
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// default.
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std::unique_ptr<OperationPass<FuncOp>> createLhloFuseLinalg(
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bool use_parallel_loops = false, llvm::ArrayRef<unsigned> tile_sizes = {});
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// Removes unnecessary LHLO copies which copy from the allocated buffers to the
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// block arguments. The block arguments are used instead of all uses of these
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// buffers. The buffers are freed. This pass only works in regions that contain
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// a single block.
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std::unique_ptr<Pass> createLhloCopyRemovalPass();
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// Lowers from LHLO dialect to parallel loops.
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std::unique_ptr<OperationPass<FuncOp>> createLegalizeLhloToParallelLoopsPass();
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} // namespace lmhlo
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namespace hlo {
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/// Lowers the standard TanhOp to an approximation that does not use intrinsics.
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std::unique_ptr<OperationPass<FuncOp>> createLegalizeTanhToApproximationPass();
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} // namespace hlo
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} // namespace mlir
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#endif // TENSORFLOW_COMPILER_MLIR_HLO_INCLUDE_MLIR_HLO_DIALECT_MHLO_TRANSFORMS_PASSES_H_
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