50 lines
1.8 KiB
C++
50 lines
1.8 KiB
C++
/* Copyright 2020 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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#include "mlir-hlo/Dialect/mhlo/IR/hlo_ops.h"
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#include "mlir-hlo/Dialect/mhlo/transforms/PassDetail.h"
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#include "mlir-hlo/Dialect/mhlo/transforms/passes.h"
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#include "mlir-hlo/Dialect/mhlo/transforms/rewriters.h"
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#include "mlir/Dialect/StandardOps/IR/Ops.h"
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#include "mlir/IR/MLIRContext.h"
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#include "mlir/IR/Operation.h"
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#include "mlir/Pass/Pass.h"
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#include "mlir/Transforms/DialectConversion.h"
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#include "mlir/Transforms/GreedyPatternRewriteDriver.h"
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namespace mlir {
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namespace mhlo {
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namespace {
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class OptimizeMhloPass : public OptimizeMhloPassBase<OptimizeMhloPass> {
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public:
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/// Performs the lowering to MHLO dialect.
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void runOnFunction() override;
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};
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// Lowers the complex operations that can be represented using other operations.
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void OptimizeMhloPass::runOnFunction() {
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// Add lowering patterns to the list.
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OwningRewritePatternList patterns(&getContext());
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PopulateOptimizeMHLOPatterns(&getContext(), &patterns);
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(void)applyPatternsAndFoldGreedily(getFunction(), std::move(patterns));
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}
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} // end anonymous namespace
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} // namespace mhlo
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} // namespace mlir
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std::unique_ptr<mlir::FunctionPass> mlir::mhlo::createOptimizeMhloPass() {
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return std::make_unique<mlir::mhlo::OptimizeMhloPass>();
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}
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