CaffeOnACL/src/caffe/layers/deconv_layer.cpp at master · 2php/CaffeOnACL · GitHub

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#include <vector>

#include "caffe/layers/deconv_layer.hpp"

namespace caffe {

template <typename Dtype>

void DeconvolutionLayer<Dtype>::compute_output_shape() {

const int* kernel_shape_data = this->kernel_shape_.cpu_data();

const int* stride_data = this->stride_.cpu_data();

const int* pad_data = this->pad_.cpu_data();

const int* dilation_data = this->dilation_.cpu_data();

this->output_shape_.clear();

for (int i = 0; i < this->num_spatial_axes_; ++i) {

// i + 1 to skip channel axis

const int input_dim = this->input_shape(i + 1);

const int kernel_extent = dilation_data[i] * (kernel_shape_data[i] - 1) + 1;

const int output_dim = stride_data[i] * (input_dim - 1)

+ kernel_extent - 2 * pad_data[i];

this->output_shape_.push_back(output_dim);

}

template <typename Dtype>

void DeconvolutionLayer<Dtype>::Forward_cpu(const vector<Blob<Dtype>*>& bottom,

const vector<Blob<Dtype>*>& top) {

const Dtype* weight = this->blobs_[0]->cpu_data();

for (int i = 0; i < bottom.size(); ++i) {

const Dtype* bottom_data = bottom[i]->cpu_data();

Dtype* top_data = top[i]->mutable_cpu_data();

for (int n = 0; n < this->num_; ++n) {

this->backward_cpu_gemm(bottom_data + n * this->bottom_dim_, weight,

top_data + n * this->top_dim_);

if (this->bias_term_) {

const Dtype* bias = this->blobs_[1]->cpu_data();

this->forward_cpu_bias(top_data + n * this->top_dim_, bias);

}

template <typename Dtype>

void DeconvolutionLayer<Dtype>::Backward_cpu(const vector<Blob<Dtype>*>& top,

const vector<bool>& propagate_down, const vector<Blob<Dtype>*>& bottom) {

const Dtype* weight = this->blobs_[0]->cpu_data();

Dtype* weight_diff = this->blobs_[0]->mutable_cpu_diff();

for (int i = 0; i < top.size(); ++i) {

const Dtype* top_diff = top[i]->cpu_diff();

const Dtype* bottom_data = bottom[i]->cpu_data();

Dtype* bottom_diff = bottom[i]->mutable_cpu_diff();

// Bias gradient, if necessary.

if (this->bias_term_ && this->param_propagate_down_[1]) {

Dtype* bias_diff = this->blobs_[1]->mutable_cpu_diff();

for (int n = 0; n < this->num_; ++n) {

this->backward_cpu_bias(bias_diff, top_diff + n * this->top_dim_);

}

if (this->param_propagate_down_[0] || propagate_down[i]) {

for (int n = 0; n < this->num_; ++n) {

// Gradient w.r.t. weight. Note that we will accumulate diffs.

if (this->param_propagate_down_[0]) {

this->weight_cpu_gemm(top_diff + n * this->top_dim_,

bottom_data + n * this->bottom_dim_, weight_diff);

}

// Gradient w.r.t. bottom data, if necessary, reusing the column buffer

// we might have just computed above.

if (propagate_down[i]) {

this->forward_cpu_gemm(top_diff + n * this->top_dim_, weight,

bottom_diff + n * this->bottom_dim_,

this->param_propagate_down_[0]);

}

#ifdef CPU_ONLY

STUB_GPU(DeconvolutionLayer);

#endif

INSTANTIATE_CLASS(DeconvolutionLayer);

REGISTER_LAYER_CLASS(Deconvolution);

} // namespace caffe

CaffeOnACL/src/caffe/layers/deconv_layer.cpp at master · 2php/CaffeOnACL · GitHub

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