elementwise.cc

// 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::graph::GraphGlobalMem;
using anakin::AK_FLOAT;
using anakin::saber::Shape;
using anakin::PTuple;

namespace paddle {
namespace inference {
namespace anakin {

template <typename TargetT>
void ElementwiseAddOpConverter<TargetT>::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>
void ElementwiseMulOpConverter<TargetT>::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 = "Prod";
  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

#ifdef PADDLE_WITH_CUDA
REGISTER_CUDA_ANAKIN_OP_CONVERTER(
    elementwise_add, ElementwiseAddOpConverter<::anakin::saber::NV>);
REGISTER_CUDA_ANAKIN_OP_CONVERTER(
    elementwise_mul, ElementwiseMulOpConverter<::anakin::saber::NV>);
#endif
REGISTER_CPU_ANAKIN_OP_CONVERTER(
    elementwise_add, ElementwiseAddOpConverter<::anakin::saber::X86>);
REGISTER_CPU_ANAKIN_OP_CONVERTER(
    elementwise_mul, ElementwiseMulOpConverter<::anakin::saber::X86>);