| /* 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_HLO_MODULE_DCE_H_ |
| #define TENSORFLOW_COMPILER_XLA_SERVICE_HLO_MODULE_DCE_H_ |
| |
| #include "tensorflow/compiler/xla/service/hlo_module.h" |
| #include "tensorflow/compiler/xla/service/hlo_pass_interface.h" |
| #include "tensorflow/compiler/xla/statusor.h" |
| |
| namespace xla { |
| |
| // HLO pass which removes dead code from computations in the module using |
| // HloModule-scoped analysis (HloLivenessAnalysis). |
| // |
| // Sweeps through live instructions which cross computation boundaries (kWhile), |
| // and removes code at dead shape indices. |
| // |
| class HloModuleDCE : public HloModulePass { |
| public: |
| ~HloModuleDCE() override {} |
| absl::string_view name() const override { return "hlo-module-dce"; } |
| |
| // Run the pass on the given module. Returns whether the module was changed |
| // (instructions were removed). |
| StatusOr<bool> Run(HloModule* module) override; |
| }; |
| |
| } // namespace xla |
| |
| #endif // TENSORFLOW_COMPILER_XLA_SERVICE_HLO_MODULE_DCE_H_ |