art, cudnn

This commit is contained in:
Joseph Redmon
2016-05-13 11:59:43 -07:00
parent 054e2b1954
commit 13209df7bb
11 changed files with 286 additions and 30 deletions

View File

@ -85,7 +85,6 @@ void forward_convolutional_layer_gpu(convolutional_layer l, network_state state)
if(l.xnor){
binarize_filters_gpu(l.filters_gpu, l.n, l.c*l.size*l.size, l.binary_filters_gpu);
//binarize_gpu(l.filters_gpu, l.n*l.c*l.size*l.size, l.binary_filters_gpu);
swap_binary(&l);
for(i = 0; i < l.batch; ++i){
binarize_input_gpu(state.input + i*l.inputs, l.c, l.h*l.w, l.binary_input_gpu + i*l.inputs);
@ -93,13 +92,31 @@ void forward_convolutional_layer_gpu(convolutional_layer l, network_state state)
state.input = l.binary_input_gpu;
}
#ifdef CUDNN
float one = 1;
cudnnConvolutionForward(cudnn_handle(),
&one,
l.srcTensorDesc,
state.input,
l.filterDesc,
l.filters_gpu,
l.convDesc,
l.fw_algo,
state.workspace,
l.workspace_size,
&one,
l.dstTensorDesc,
l.output_gpu);
#else
for(i = 0; i < l.batch; ++i){
im2col_ongpu(state.input + i*l.c*l.h*l.w, l.c, l.h, l.w, l.size, l.stride, l.pad, l.col_image_gpu);
im2col_ongpu(state.input + i*l.c*l.h*l.w, l.c, l.h, l.w, l.size, l.stride, l.pad, state.workspace);
float * a = l.filters_gpu;
float * b = l.col_image_gpu;
float * b = state.workspace;
float * c = l.output_gpu;
gemm_ongpu(0,0,m,n,k,1.,a,k,b,n,1.,c+i*m*n,n);
}
#endif
if (l.batch_normalize) {
forward_batchnorm_layer_gpu(l, state);
@ -113,7 +130,6 @@ void forward_convolutional_layer_gpu(convolutional_layer l, network_state state)
void backward_convolutional_layer_gpu(convolutional_layer l, network_state state)
{
int i;
int m = l.n;
int n = l.size*l.size*l.c;
int k = convolutional_out_height(l)*
@ -128,26 +144,61 @@ void backward_convolutional_layer_gpu(convolutional_layer l, network_state state
}
if(l.xnor) state.input = l.binary_input_gpu;
#ifdef CUDNN
float one = 1;
cudnnConvolutionBackwardFilter(cudnn_handle(),
&one,
l.srcTensorDesc,
state.input,
l.ddstTensorDesc,
l.delta_gpu,
l.convDesc,
l.bf_algo,
state.workspace,
l.workspace_size,
&one,
l.dfilterDesc,
l.filter_updates_gpu);
if(state.delta){
cudnnConvolutionBackwardData(cudnn_handle(),
&one,
l.filterDesc,
l.filters_gpu,
l.ddstTensorDesc,
l.delta_gpu,
l.convDesc,
l.bd_algo,
state.workspace,
l.workspace_size,
&one,
l.dsrcTensorDesc,
state.delta);
}
#else
int i;
for(i = 0; i < l.batch; ++i){
float * a = l.delta_gpu;
float * b = l.col_image_gpu;
float * b = state.workspace;
float * c = l.filter_updates_gpu;
im2col_ongpu(state.input + i*l.c*l.h*l.w, l.c, l.h, l.w, l.size, l.stride, l.pad, l.col_image_gpu);
im2col_ongpu(state.input + i*l.c*l.h*l.w, l.c, l.h, l.w, l.size, l.stride, l.pad, state.workspace);
gemm_ongpu(0,1,m,n,k,1,a + i*m*k,k,b,k,1,c,n);
if(state.delta){
if(l.binary || l.xnor) swap_binary(&l);
float * a = l.filters_gpu;
float * b = l.delta_gpu;
float * c = l.col_image_gpu;
float * c = state.workspace;
gemm_ongpu(1,0,n,k,m,1,a,n,b + i*k*m,k,0,c,k);
col2im_ongpu(l.col_image_gpu, l.c, l.h, l.w, l.size, l.stride, l.pad, state.delta + i*l.c*l.h*l.w);
col2im_ongpu(state.workspace, l.c, l.h, l.w, l.size, l.stride, l.pad, state.delta + i*l.c*l.h*l.w);
if(l.binary || l.xnor) swap_binary(&l);
}
}
#endif
}
void pull_convolutional_layer(convolutional_layer layer)