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hope i didn't break anything

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This commit is contained in:
Joseph Redmon
2016-06-02 15:25:24 -07:00
parent 881d6ee9b6
commit ec3d050a76
17 changed files with 834 additions and 550 deletions
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61
src/convolutional_layer.c
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@ -88,8 +88,8 @@ image get_convolutional_delta(convolutional_layer l)
return float_to_image(w,h,c,l.delta);
}
#ifdef CUDNN
size_t get_workspace_size(layer l){
#ifdef CUDNN
size_t most = 0;
size_t s = 0;
cudnnGetConvolutionForwardWorkspaceSize(cudnn_handle(),
@ -117,8 +117,10 @@ size_t get_workspace_size(layer l){
&s);
if (s > most) most = s;
return most;
#else
return (size_t)l.out_h*l.out_w*l.size*l.size*l.c*sizeof(float);
#endif
}
#endif
convolutional_layer make_convolutional_layer(int batch, int h, int w, int c, int n, int size, int stride, int pad, ACTIVATION activation, int batch_normalize, int binary, int xnor)
{
@ -154,8 +156,6 @@ convolutional_layer make_convolutional_layer(int batch, int h, int w, int c, int
l.outputs = l.out_h * l.out_w * l.out_c;
l.inputs = l.w * l.h * l.c;
l.col_image = calloc(out_h*out_w*size*size*c, sizeof(float));
l.workspace_size = out_h*out_w*size*size*c*sizeof(float);
l.output = calloc(l.batch*out_h * out_w * n, sizeof(float));
l.delta = calloc(l.batch*out_h * out_w * n, sizeof(float));
@ -255,10 +255,9 @@ convolutional_layer make_convolutional_layer(int batch, int h, int w, int c, int
CUDNN_CONVOLUTION_BWD_FILTER_PREFER_FASTEST,
0,
&l.bf_algo);
#endif
#endif
l.workspace_size = get_workspace_size(l);
#endif
#endif
l.activation = activation;
fprintf(stderr, "Convolutional Layer: %d x %d x %d image, %d filters -> %d x %d x %d image\n", h,w,c,n, out_h, out_w, n);
@ -315,8 +314,6 @@ void resize_convolutional_layer(convolutional_layer *l, int w, int h)
l->outputs = l->out_h * l->out_w * l->out_c;
l->inputs = l->w * l->h * l->c;
l->col_image = realloc(l->col_image,
out_h*out_w*l->size*l->size*l->c*sizeof(float));
l->output = realloc(l->output,
l->batch*out_h * out_w * l->n*sizeof(float));
l->delta = realloc(l->delta,
@ -328,7 +325,43 @@ void resize_convolutional_layer(convolutional_layer *l, int w, int h)
l->delta_gpu = cuda_make_array(l->delta, l->batch*out_h*out_w*l->n);
l->output_gpu = cuda_make_array(l->output, l->batch*out_h*out_w*l->n);
#ifdef CUDNN
cudnnSetTensor4dDescriptor(l->dsrcTensorDesc, CUDNN_TENSOR_NCHW, CUDNN_DATA_FLOAT, l->batch, l->c, l->h, l->w);
cudnnSetTensor4dDescriptor(l->ddstTensorDesc, CUDNN_TENSOR_NCHW, CUDNN_DATA_FLOAT, l->batch, l->out_c, l->out_h, l->out_w);
cudnnSetFilter4dDescriptor(l->dfilterDesc, CUDNN_DATA_FLOAT, CUDNN_TENSOR_NCHW, l->n, l->c, l->size, l->size);
cudnnSetTensor4dDescriptor(l->srcTensorDesc, CUDNN_TENSOR_NCHW, CUDNN_DATA_FLOAT, l->batch, l->c, l->h, l->w);
cudnnSetTensor4dDescriptor(l->dstTensorDesc, CUDNN_TENSOR_NCHW, CUDNN_DATA_FLOAT, l->batch, l->out_c, l->out_h, l->out_w);
cudnnSetFilter4dDescriptor(l->filterDesc, CUDNN_DATA_FLOAT, CUDNN_TENSOR_NCHW, l->n, l->c, l->size, l->size);
int padding = l->pad ? l->size/2 : 0;
cudnnSetConvolution2dDescriptor(l->convDesc, padding, padding, l->stride, l->stride, 1, 1, CUDNN_CROSS_CORRELATION);
cudnnGetConvolutionForwardAlgorithm(cudnn_handle(),
l->srcTensorDesc,
l->filterDesc,
l->convDesc,
l->dstTensorDesc,
CUDNN_CONVOLUTION_FWD_PREFER_FASTEST,
0,
&l->fw_algo);
cudnnGetConvolutionBackwardDataAlgorithm(cudnn_handle(),
l->filterDesc,
l->ddstTensorDesc,
l->convDesc,
l->dsrcTensorDesc,
CUDNN_CONVOLUTION_BWD_DATA_PREFER_FASTEST,
0,
&l->bd_algo);
cudnnGetConvolutionBackwardFilterAlgorithm(cudnn_handle(),
l->srcTensorDesc,
l->ddstTensorDesc,
l->convDesc,
l->dfilterDesc,
CUDNN_CONVOLUTION_BWD_FILTER_PREFER_FASTEST,
0,
&l->bf_algo);
#endif
#endif
l->workspace_size = get_workspace_size(*l);
}
void add_bias(float *output, float *biases, int batch, int n, int size)
@ -386,7 +419,7 @@ void forward_convolutional_layer(convolutional_layer l, network_state state)
int n = out_h*out_w;
char *a = l.cfilters;
float *b = l.col_image;
float *b = state.workspace;
float *c = l.output;
for(i = 0; i < l.batch; ++i){
@ -407,7 +440,7 @@ void forward_convolutional_layer(convolutional_layer l, network_state state)
int n = out_h*out_w;
float *a = l.filters;
float *b = l.col_image;
float *b = state.workspace;
float *c = l.output;
for(i = 0; i < l.batch; ++i){
@ -439,7 +472,7 @@ void backward_convolutional_layer(convolutional_layer l, network_state state)
for(i = 0; i < l.batch; ++i){
float *a = l.delta + i*m*k;
float *b = l.col_image;
float *b = state.workspace;
float *c = l.filter_updates;
float *im = state.input+i*l.c*l.h*l.w;
@ -451,11 +484,11 @@ void backward_convolutional_layer(convolutional_layer l, network_state state)
if(state.delta){
a = l.filters;
b = l.delta + i*m*k;
c = l.col_image;
c = state.workspace;
gemm(1,0,n,k,m,1,a,n,b,k,0,c,k);
col2im_cpu(l.col_image, l.c, l.h, l.w, l.size, l.stride, l.pad, state.delta+i*l.c*l.h*l.w);
col2im_cpu(state.workspace, l.c, l.h, l.w, l.size, l.stride, l.pad, state.delta+i*l.c*l.h*l.w);
}
}
}