| /* Copyright 2018 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. |
| ==============================================================================*/ |
| |
| #ifndef TENSORFLOW_COMPILER_XLA_SERVICE_DESPECIALIZER_H_ |
| #define TENSORFLOW_COMPILER_XLA_SERVICE_DESPECIALIZER_H_ |
| |
| #include "tensorflow/compiler/xla/service/hlo_module.h" |
| #include "tensorflow/compiler/xla/service/hlo_pass_interface.h" |
| #include "tensorflow/compiler/xla/service/hlo_pass_pipeline.h" |
| #include "tensorflow/compiler/xla/statusor.h" |
| |
| namespace xla { |
| |
| // Creates an HloPassPipeline containing multiple HloPasses that can |
| // despecialize an optimized HloModule. This is useful to run an HloModule |
| // optimized for one specific platform on a different platform (undoing platform |
| // specific passes) with matching numerics for comparison. |
| // |
| // Current despecialization passes are Defuser, ImplicitBroadcastRemover, |
| // and BFloat16MixedPrecisionRemoval. |
| class Despecializer : public HloModulePass { |
| public: |
| Despecializer(); |
| absl::string_view name() const override { return "despecializer"; } |
| StatusOr<bool> Run(HloModule* module) override; |
| |
| private: |
| HloPassPipeline pipeline_; |
| }; |
| |
| } // namespace xla |
| |
| #endif // TENSORFLOW_COMPILER_XLA_SERVICE_DESPECIALIZER_H_ |