elementwise_op_impl.cu.h

/* Copyright (c) 2021 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. */

#pragma once

#include "paddle/fluid/framework/pten_utils.h"
#include "paddle/fluid/framework/tensor.h"

// only can include the headers in paddle/top/api dirs
#include "paddle/pten/api/lib/utils/tensor_utils.h"
#include "paddle/pten/kernels/gpu/elementwise.h"

namespace paddle {
namespace operators {

using ElementwiseType = pten::ElementwiseType;

template <ElementwiseType ET, typename InT, typename OutT, typename Functor,
          int NumOuts = 1>
void LaunchSameDimsElementwiseCudaKernel(
    const KPDevice &ctx, const std::vector<const framework::Tensor *> &ins,
    std::vector<framework::Tensor *> *outs, Functor func) {
  std::vector<const pten::DenseTensor *> pt_inputs;
  std::vector<pten::DenseTensor *> pt_outputs;
  // TODO(YuanRisheng) *_tmp for cache DenseTensor, because the temporary
  // DenseTensor obj
  // generated by MakePtenDenseTensor can be destroyed when exits loop. *_tmp
  // can be deleted
  // when DenseTensor support copy constructor.
  std::vector<std::unique_ptr<pten::DenseTensor>> pt_inputs_tmp;
  std::vector<std::unique_ptr<pten::DenseTensor>> pt_outputs_tmp;
  for (auto in : ins) {
    pt_inputs_tmp.emplace_back(
        std::move(paddle::experimental::MakePtenDenseTensor(*in)));
  }
  for (auto out : *outs) {
    pt_outputs_tmp.emplace_back(
        std::move(paddle::experimental::MakePtenDenseTensor(*out)));
  }
  for (int i = 0; i < pt_inputs_tmp.size(); i++) {
    pt_inputs.push_back(pt_inputs_tmp[i].get());
  }
  for (int i = 0; i < pt_outputs_tmp.size(); i++) {
    pt_outputs.push_back(pt_outputs_tmp[i].get());
  }
  pten::funcs::LaunchSameDimsElementwiseCudaKernel<ET, InT, OutT, Functor,
                                                   NumOuts>(ctx, pt_inputs,
                                                            &pt_outputs, func);
}

}  // namespace operators
}  // namespace paddle