| /* Copyright 2020 The TensorFlow Authors. All Rights Reserved. |
| |
| 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 |
| |
| http://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 <memory> |
| |
| #include "mlir/IR/PatternMatch.h" // from @llvm-project |
| #include "mlir/Pass/Pass.h" // from @llvm-project |
| #include "mlir/Transforms/GreedyPatternRewriteDriver.h" // from @llvm-project |
| #include "tensorflow/compiler/mlir/tensorflow/transforms/passes_detail.h" |
| #include "tensorflow/compiler/mlir/tensorflow/transforms/tf_data_optimization.h" |
| |
| namespace mlir { |
| namespace TF { |
| namespace { |
| |
| // Perform tf.data optimizations. |
| struct TFDataOptimization |
| : public TFDataOptimizationPassBase<TFDataOptimization> { |
| void runOnOperation() override { |
| RewritePatternSet patterns(&getContext()); |
| mlir::TF::PopulateTFDataOptimizationPatterns(&getContext(), &patterns); |
| |
| (void)applyPatternsAndFoldGreedily(getOperation(), std::move(patterns)); |
| } |
| }; |
| |
| } // namespace |
| |
| std::unique_ptr<OperationPass<func::FuncOp>> CreateTFDataOptimizationPass() { |
| return std::make_unique<TFDataOptimization>(); |
| } |
| |
| } // namespace TF |
| } // namespace mlir |