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Convolutional working on GPU

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This commit is contained in:
Joseph Redmon
2014-10-13 00:29:01 -07:00
parent 76ee68f96d
commit 787d534560
21 changed files with 643 additions and 93 deletions
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33
src/convolutional_layer.c
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@@ -195,13 +195,14 @@ void backward_convolutional_layer(convolutional_layer layer, float *delta)
b = layer.delta;
c = layer.col_image;
memset(delta, 0, layer.batch*layer.h*layer.w*layer.c*sizeof(float));
for(i = 0; i < layer.batch; ++i){
gemm(1,0,m,n,k,1,a,m,b,n,0,c,n);
b += k*n;
c += m*n;
}
memset(delta, 0, layer.batch*layer.h*layer.w*layer.c*sizeof(float));
col2im_cpu(layer.col_image, layer.batch, layer.c, layer.h, layer.w, layer.size, layer.stride, layer.pad, delta);
}
}
@@ -361,7 +362,7 @@ void forward_convolutional_layer_gpu(convolutional_layer layer, cl_mem in)
clReleaseMemObject(c);
}
activate_array_ongpu(layer.output_cl, m*n*layer.batch, layer.activation);
cl_read_array(layer.output_cl, layer.output, m*n*layer.batch);
//cl_read_array(layer.output_cl, layer.output, m*n*layer.batch);
}
void backward_convolutional_layer_gpu(convolutional_layer layer, cl_mem delta_cl)
@@ -384,9 +385,7 @@ void backward_convolutional_layer_gpu(convolutional_layer layer, cl_mem delta_cl
clReleaseMemObject(a);
clReleaseMemObject(b);
}
cl_read_array(layer.filter_updates_cl, layer.filter_updates, m*n);
cl_read_array(layer.bias_updates_cl, layer.bias_updates, m);
//cl_read_array(layer.delta_cl, layer.delta, m*k*layer.batch);
if(delta_cl){
m = layer.size*layer.size*layer.c;
@@ -395,17 +394,31 @@ void backward_convolutional_layer_gpu(convolutional_layer layer, cl_mem delta_cl
convolutional_out_width(layer);
for(i = 0; i < layer.batch; ++i){
a = layer.filters_cl;
b = cl_sub_array(layer.delta_cl, i*k*n, k*n);
c = cl_sub_array(layer.col_image_cl, i*m*n, m*n);
cl_mem a = layer.filters_cl;
cl_mem b = cl_sub_array(layer.delta_cl, i*k*n, k*n);
cl_mem c = cl_sub_array(layer.col_image_cl, i*m*n, m*n);
gemm_ongpu(1,0,m,n,k,1,a,m,b,n,0,c,n);
clReleaseMemObject(b);
clReleaseMemObject(c);
}
col2im_gpu(layer.col_image_cl, layer.batch, layer.c, layer.h, layer.w, layer.size, layer.stride, layer.pad, delta_cl);
scal_ongpu(layer.batch*layer.h*layer.w*layer.c,0,delta_cl, 1);
col2im_ongpu(layer.col_image_cl, layer.batch, layer.c, layer.h, layer.w, layer.size, layer.stride, layer.pad, delta_cl);
}
}
void update_convolutional_layer_gpu(convolutional_layer layer)
{
int size = layer.size*layer.size*layer.c*layer.n;
axpy_ongpu(layer.n, layer.learning_rate, layer.bias_updates_cl, 1, layer.biases_cl, 1);
scal_ongpu(layer.n,layer.momentum, layer.bias_updates_cl, 1);
scal_ongpu(size, 1.-layer.learning_rate*layer.decay, layer.filters_cl, 1);
axpy_ongpu(size, layer.learning_rate, layer.filter_updates_cl, 1, layer.filters_cl, 1);
scal_ongpu(size, layer.momentum, layer.filter_updates_cl, 1);
}
#endif