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// Copyright 2014 BVLC and contributors.
#include <vector>
#include "hdf5.h"
#include "hdf5_hl.h"
#include "caffe/blob.hpp"
#include "caffe/common.hpp"
#include "caffe/layer.hpp"
#include "caffe/util/io.hpp"
#include "caffe/vision_layers.hpp"
namespace caffe {
using std::vector;
template <typename Dtype>
Dtype HDF5OutputLayer<Dtype>::Forward_gpu(const vector<Blob<Dtype>*>& bottom,
vector<Blob<Dtype>*>* top) {
CHECK_GE(bottom.size(), 2);
CHECK_EQ(bottom[0]->num(), bottom[1]->num());
data_blob_.Reshape(bottom[0]->num(), bottom[0]->channels(),
bottom[0]->height(), bottom[0]->width());
label_blob_.Reshape(bottom[1]->num(), bottom[1]->channels(),
bottom[1]->height(), bottom[1]->width());
const int data_datum_dim = bottom[0]->count() / bottom[0]->num();
const int label_datum_dim = bottom[1]->count() / bottom[1]->num();
for (int i = 0; i < bottom[0]->num(); ++i) {
CUDA_CHECK(cudaMemcpy(&data_blob_.mutable_cpu_data()[i * data_datum_dim],
&bottom[0]->gpu_data()[i * data_datum_dim],
sizeof(Dtype) * data_datum_dim, cudaMemcpyDeviceToHost));
CUDA_CHECK(cudaMemcpy(&label_blob_.mutable_cpu_data()[i * label_datum_dim],
&bottom[1]->gpu_data()[i * label_datum_dim],
sizeof(Dtype) * label_datum_dim, cudaMemcpyDeviceToHost));
}
SaveBlobs();
return Dtype(0.);
}
template <typename Dtype>
void HDF5OutputLayer<Dtype>::Backward_gpu(const vector<Blob<Dtype>*>& top,
const bool propagate_down, vector<Blob<Dtype>*>* bottom) {
return;
}
INSTANTIATE_CLASS(HDF5OutputLayer);
} // namespace caffe
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