gather.h

/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.

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 <memory.h>
#include <cstring>

#include "paddle/framework/ddim.h"
#include "paddle/framework/tensor.h"
#include "paddle/platform/place.h"

using paddle::framework::Tensor;
using paddle::framework::DDim;

namespace paddle {
namespace operators {

/* Implementation of CPU copy */
template <typename T>
void CPUGather(const T* params, const int* indices, const int slice_size,
               const int index_size, T* output) {
  const size_t slice_bytes = slice_size * sizeof(T);

  for (size_t i = 0; i < index_size; ++i) {
    int index_ = indices[i];
    // copy src[index_] to output[i]
    memcpy(output + i * slice_size, params + index_ * slice_size, slice_bytes);
  }
}

/* Implementation of GPU copy:
  I suppose the GPUDevice& d, contains gpu_id and thread_id
  d = cuda_stream(gpu_id_, stream_id_);
*/
template <typename T>
void GPUGather(const T* src, const int* index, const int slice_size,
               const int index_size, T* output);

/**
 * Return a new tensor from source tensor, gathered according to index
 * input[src]: type-T source Tensor
 * input[index]: type-int index Tensor (1-D)
 * return: output tensor
 */
template <typename T>
void Gather(const platform::Place& place, const paddle::framework::Tensor* src,
            const paddle::framework::Tensor* index,
            paddle::framework::Tensor* output) {
  // check index of shape 1-D
  PADDLE_ENFORCE(index->dims().size() == 1);
  int index_size = index->dims()[0];

  auto src_dims = src->dims();
  DDim output_dims(src_dims);
  output_dims[0] = index_size;

  // slice size
  int slice_size = 1;
  for (size_t i = 1; i < src_dims.size(); ++i) slice_size *= src_dims[i];

  // Gathering
  if (platform::is_cpu_place(place)) {
    CPUGather<T>(src->data<T>(), index->data<int>(), slice_size, index_size,
                 output->data<T>());
  } else {
    // init for GPU
    // output_arr = output->mutable_data<T>(output_dims, platform::GPUPlace());
    // how to specialize device??
    // GPUGather(
    //    d, src->data(), index->data(), slice_size,
    //    new_tensor->mutable_data());
  }
}

}  // namespace operators
}  // namespace paddle