text: // Copyright (c) 2018 PaddlePaddle 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 "paddle/fluid/inference/anakin/convert/elementwise.h"
  #include <algorithm>
  #include <string>
  #include <vector>
  
  using anakin::PTuple;
  
  namespace paddle {
  namespace inference {
  namespace anakin {
  
  template <typename TargetT, ::anakin::Precision PrecisionT>
  void ElementwiseAddOpConverter<TargetT, PrecisionT>::operator()(
      const framework::proto::OpDesc &op, const framework::BlockDesc &block_desc,
      const framework::Scope &scope, bool test_mode) {
    framework::OpDesc op_desc(op, nullptr);
    PADDLE_ENFORCE_EQ(op_desc.Input("X").size(), 1);
    PADDLE_ENFORCE_EQ(op_desc.Input("Y").size(), 1);
    PADDLE_ENFORCE_EQ(op_desc.Output("Out").size(), 1);
  
    auto x_name = op_desc.Input("X").front();
    auto y_name = op_desc.Input("Y").front();
    auto out_name = op_desc.Output("Out").front();
    auto op_name = op_desc.Type() + ":" + op_desc.Output("Out").front();
  
    this->engine_->AddOp(op_name, "Eltwise", {x_name, y_name}, {out_name});
    std::string elementwise_type = "Add";
    this->engine_->template AddOpAttr<std::string>(op_name, "type",
                                                   elementwise_type);
    std::vector<float> coeff = {1.0, 1.0};
    this->engine_->template AddOpAttr<PTuple<float>>(op_name, "coeff", coeff);
  }
  
  template <typename TargetT, ::anakin::Precision PrecisionT>
  void ElementwiseMulOpConverter<TargetT, PrecisionT>::operator()(
      const framework::proto::OpDesc &op, const framework::BlockDesc &block_desc,
      const framework::Scope &scope, bool test_mode) {
    framework::OpDesc op_desc(op, nullptr);
    PADDLE_ENFORCE_EQ(op_desc.Input("X").size(), 1);
    PADDLE_ENFORCE_EQ(op_desc.Input("Y").size(), 1);
    PADDLE_ENFORCE_EQ(op_desc.Output("Out").size(), 1);
  
    auto x_name = op_desc.Input("X").front();
    auto y_name = op_desc.Input("Y").front();
    auto out_name = op_desc.Output("Out").front();
    auto op_name = op_desc.Type() + ":" + op_desc.Output("Out").front();
  
    this->engine_->AddOp(op_name, "Eltwise", {x_name, y_name}, {out_name});
    std::string elementwise_type = "Mul";
    this->engine_->template AddOpAttr<std::string>(op_name, "type",
                                                   elementwise_type);
    std::vector<float> coeff = {1.0, 1.0};
    this->engine_->template AddOpAttr<PTuple<float>>(op_name, "coeff", coeff);
  }
  
  }  // namespace anakin
  }  // namespace inference
  }  // namespace paddle
  
  REGISTER_ANAKIN_OP_CONVERTER(elementwise_add, ElementwiseAddOpConverter);
  REGISTER_ANAKIN_OP_CONVERTER(elementwise_mul, ElementwiseMulOpConverter);
  