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Fixed convolutional-layer when it is used as base for crnn-layer

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This commit is contained in:
AlexeyAB
2019-02-28 20:47:22 +03:00
parent e8c3905e54
commit 9b09abe122
1 changed files with 10 additions and 8 deletions
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18
src/convolutional_layer.c
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@ -348,6 +348,7 @@ convolutional_layer make_convolutional_layer(int batch, int steps, int h, int w,
l.xnor = xnor; l.xnor = xnor;
l.use_bin_output = use_bin_output; l.use_bin_output = use_bin_output;
l.batch = batch; l.batch = batch;
l.steps = steps;
l.stride = stride; l.stride = stride;
l.size = size; l.size = size;
l.pad = padding; l.pad = padding;
@ -544,6 +545,7 @@ void test_convolutional_layer()
void resize_convolutional_layer(convolutional_layer *l, int w, int h) void resize_convolutional_layer(convolutional_layer *l, int w, int h)
{ {
int total_batch = l->batch*l->steps;
int old_w = l->w; int old_w = l->w;
int old_h = l->h; int old_h = l->h;
l->w = w; l->w = w;
@ -557,11 +559,11 @@ void resize_convolutional_layer(convolutional_layer *l, int w, int h)
l->outputs = l->out_h * l->out_w * l->out_c; l->outputs = l->out_h * l->out_w * l->out_c;
l->inputs = l->w * l->h * l->c; l->inputs = l->w * l->h * l->c;
l->output = (float*)realloc(l->output, l->batch * l->outputs * sizeof(float)); l->output = (float*)realloc(l->output, total_batch * l->outputs * sizeof(float));
l->delta = (float*)realloc(l->delta, l->batch * l->outputs * sizeof(float)); l->delta = (float*)realloc(l->delta, total_batch * l->outputs * sizeof(float));
if(l->batch_normalize){ if(l->batch_normalize){
l->x = (float*)realloc(l->x, l->batch * l->outputs * sizeof(float)); l->x = (float*)realloc(l->x, total_batch * l->outputs * sizeof(float));
l->x_norm = (float*)realloc(l->x_norm, l->batch * l->outputs * sizeof(float)); l->x_norm = (float*)realloc(l->x_norm, total_batch * l->outputs * sizeof(float));
} }
if (l->xnor) { if (l->xnor) {
@ -573,15 +575,15 @@ void resize_convolutional_layer(convolutional_layer *l, int w, int h)
cuda_free(l->delta_gpu); cuda_free(l->delta_gpu);
cuda_free(l->output_gpu); cuda_free(l->output_gpu);
l->delta_gpu = cuda_make_array(l->delta, l->batch*l->outputs); l->delta_gpu = cuda_make_array(l->delta, total_batch*l->outputs);
l->output_gpu = cuda_make_array(l->output, l->batch*l->outputs); l->output_gpu = cuda_make_array(l->output, total_batch*l->outputs);
if (l->batch_normalize) { if (l->batch_normalize) {
cuda_free(l->x_gpu); cuda_free(l->x_gpu);
cuda_free(l->x_norm_gpu); cuda_free(l->x_norm_gpu);
l->x_gpu = cuda_make_array(l->output, l->batch*l->outputs); l->x_gpu = cuda_make_array(l->output, total_batch*l->outputs);
l->x_norm_gpu = cuda_make_array(l->output, l->batch*l->outputs); l->x_norm_gpu = cuda_make_array(l->output, total_batch*l->outputs);
} }
if (l->xnor) { if (l->xnor) {