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/* 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.
==============================================================================*/
#ifndef TENSORFLOW_COMPILER_MLIR_LITE_QUANTIZATION_XLA_PASSES_H_
#define TENSORFLOW_COMPILER_MLIR_LITE_QUANTIZATION_XLA_PASSES_H_
#include <memory>
#include "mlir/IR/Function.h" // from @llvm-project
#include "mlir/Pass/Pass.h" // from @llvm-project
namespace mlir {
namespace xla_hlo {
// Propagate the quantization information to all the tensors according to the
// op quant spec.
std::unique_ptr<OperationPass<FuncOp>> CreatePropagateQuantPass();
// Rewrite the graph and quantize the constant.
std::unique_ptr<OperationPass<FuncOp>> CreateMaterializeToXlaPass();
// Fuse HLO ops into quantized regions.
std::unique_ptr<OperationPass<FuncOp>> CreateCpuKernelFusionPass();
} // namespace xla_hlo
} // namespace mlir
#endif // TENSORFLOW_COMPILER_MLIR_LITE_QUANTIZATION_XLA_PASSES_H_