text: /* 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 "tensorflow/compiler/mlir/hlo/include/mlir-hlo/Dialect/mhlo/transforms/rewriters.h"
  #include "tensorflow/compiler/mlir/tools/kernel_gen/transforms/passes.h"
  
  namespace mlir {
  namespace kernel_gen {
  namespace transforms {
  namespace {
  
  #define GEN_PASS_CLASSES
  #include "tensorflow/compiler/mlir/tools/kernel_gen/transforms/kernel_gen_passes.h.inc"
  
  struct UnfuseBatchNormPass
      : public UnfuseBatchNormPassBase<UnfuseBatchNormPass> {
    void runOnFunction() override {
      mlir::OwningRewritePatternList patterns;
      mlir::mhlo::PopulateUnfuseBatchNormPatterns(&getContext(), &patterns);
      mlir::applyPatternsAndFoldGreedily(getOperation(), patterns);
    }
  };
  
  }  // namespace
  
  std::unique_ptr<mlir::FunctionPass> CreateUnfuseBatchNormPass() {
    return std::make_unique<UnfuseBatchNormPass>();
  }
  
  }  // namespace transforms
  }  // namespace kernel_gen
  }  // namespace mlir
  