src/caffe/layers/hdf5_data_layer.cu

   1 // Copyright Sergey Karayev 2014
   2 /*
   3 TODO:
   4 - only load parts of the file, in accordance with a prototxt param "max_mem"
   5 */
   6
   7 #include <stdint.h>
   8 #include <string>
   9 #include <vector>
  10
  11 #include "hdf5.h"
  12 #include "hdf5_hl.h"
  13
  14 #include "caffe/layer.hpp"
  15 #include "caffe/util/io.hpp"
  16 #include "caffe/vision_layers.hpp"
  17
  18 using std::string;
  19
  20 namespace caffe {
  21
  22 template <typename Dtype>
  23 void HDF5DataLayer<Dtype>::Forward_gpu(const vector<Blob<Dtype>*>& bottom,
  24       vector<Blob<Dtype>*>* top) {
  25   const int batchsize = this->layer_param_.batchsize();
  26   const int data_count = (*top)[0]->count() / (*top)[0]->num();
  27   const int label_data_count = (*top)[1]->count() / (*top)[1]->num();
  28
  29   for (int i = 0; i < batchsize; ++i, ++current_row_) {
  30     if (current_row_ == data_dims_[0]) {
  31       current_row_ = 0;
  32     }
  33
  34     CUDA_CHECK(cudaMemcpy(
  35             &(*top)[0]->mutable_gpu_data()[i * data_count],
  36             &(data_.get()[current_row_ * data_count]),
  37             sizeof(Dtype) * data_count,
  38             cudaMemcpyHostToDevice));
  39
  40     CUDA_CHECK(cudaMemcpy(
  41             &(*top)[1]->mutable_gpu_data()[i * label_data_count],
  42             &(label_.get()[current_row_ * label_data_count]),
  43             sizeof(Dtype) * label_data_count,
  44             cudaMemcpyHostToDevice));
  45   }
  46 }
  47
  48 template <typename Dtype>
  49 Dtype HDF5DataLayer<Dtype>::Backward_gpu(const vector<Blob<Dtype>*>& top,
  50       const bool propagate_down, vector<Blob<Dtype>*>* bottom) {
  51   return Dtype(0.);
  52 }
  53
  54 INSTANTIATE_CLASS(HDF5DataLayer);
  55
  56 }  // namespace caffe