plugin/caffe/caffe_blob.cc

/*
 * Licensed to the Apache Software Foundation (ASF) under one
 * or more contributor license agreements.  See the NOTICE file
 * distributed with this work for additional information
 * regarding copyright ownership.  The ASF licenses this file
 * to you 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.
 */

/*!
 * Copyright (c) 2016 by Contributors
 * \file caffe_blob.cc
 * \brief Implementations of SetDataGradToBlob given various device/dimension
 * \author Haoran Wang
*/
#include "caffe_blob.h"
namespace mxnet {
namespace op {
namespace caffe {

template<>
void SetDataGradToBlob<mshadow::cpu, float>(caffeMemoryTypes memType,
                            std::vector<::caffe::Blob<float>*>::iterator blob,
                            std::vector<TBlob>::const_iterator itr) {
  float *data_ptr = reinterpret_cast<float*>((*itr).dptr_);
  if (memType == Data)
    (*blob)->set_cpu_data(data_ptr);
  else
    MXCAFFEBLOB(*blob, float)->set_cpu_diff(data_ptr);
}

template<>
void SetDataGradToBlob<mshadow::cpu, double>(caffeMemoryTypes memType,
                            std::vector<::caffe::Blob<double>*>::iterator blob,
                            std::vector<TBlob>::const_iterator itr) {
  double *data_ptr = reinterpret_cast<double*>((*itr).dptr_);
  if (memType == Data)
    (*blob)->set_cpu_data(data_ptr);
  else
    MXCAFFEBLOB(*blob, double)->set_cpu_diff(data_ptr);
}

template<>
void SetDataGradToBlob<mshadow::gpu, float>(caffeMemoryTypes memType,
                            std::vector<::caffe::Blob<float>*>::iterator blob,
                            std::vector<TBlob>::const_iterator itr) {
  float *data_ptr = reinterpret_cast<float*>((*itr).dptr_);
  if (memType == Data)
    (*blob)->set_gpu_data(data_ptr);
  else
    MXCAFFEBLOB(*blob, float)->set_gpu_diff(data_ptr);
}

template<>
void SetDataGradToBlob<mshadow::gpu, double>(caffeMemoryTypes memType,
                            std::vector<::caffe::Blob<double>*>::iterator blob,
                            std::vector<TBlob>::const_iterator itr) {
  double *data_ptr = reinterpret_cast<double*>((*itr).dptr_);
  if (memType == Data)
    (*blob)->set_gpu_data(data_ptr);
  else
    MXCAFFEBLOB(*blob, double)->set_gpu_diff(data_ptr);
}

mxnet::TShape Vector2TShape(const std::vector<int> &vec_int) {
  std::vector<mshadow::index_t> vec;
  for (uint32_t i = 0; i < vec_int.size(); ++i)
    vec.push_back(vec_int[i]);
  // 0-dim represents scalar in caffe
  if (vec_int.size() == 0)
    vec.push_back(1);
  return {vec.begin(), vec.end()};
}

std::vector<int> TShape2Vector(const mxnet::TShape &tshape) {
  std::vector<int> s;
  for (uint32_t i =0 ; i < tshape.ndim(); ++i)
    s.push_back(tshape[i]);
  return s;
}

}  // namespace caffe
}  // namespace op
}  // namespace mxnet