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LSTM, RNN, GRU - use connected_layer that uses cuDNN. Fixed CRNN for conv-layer with cuDNN.

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AlexeyAB
2019-01-28 23:50:51 +03:00
parent 0e1f3eaf35
commit 640bdbc063
13 changed files with 292 additions and 101 deletions
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13
src/crnn_layer.c
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@ -48,18 +48,21 @@ layer make_crnn_layer(int batch, int h, int w, int c, int hidden_filters, int ou
l.input_layer = malloc(sizeof(layer));
fprintf(stderr, "\t\t");
*(l.input_layer) = make_convolutional_layer(batch*steps, h, w, c, hidden_filters, 3, 1, 1, activation, batch_normalize, 0, 0, 0, 0, 0);
*(l.input_layer) = make_convolutional_layer(batch, steps, h, w, c, hidden_filters, 3, 1, 1, activation, batch_normalize, 0, 0, 0, 0, 0);
l.input_layer->batch = batch;
if (l.workspace_size < l.input_layer->workspace_size) l.workspace_size = l.input_layer->workspace_size;
l.self_layer = malloc(sizeof(layer));
fprintf(stderr, "\t\t");
*(l.self_layer) = make_convolutional_layer(batch*steps, h, w, hidden_filters, hidden_filters, 3, 1, 1, activation, batch_normalize, 0, 0, 0, 0, 0);
*(l.self_layer) = make_convolutional_layer(batch, steps, h, w, hidden_filters, hidden_filters, 3, 1, 1, activation, batch_normalize, 0, 0, 0, 0, 0);
l.self_layer->batch = batch;
if (l.workspace_size < l.self_layer->workspace_size) l.workspace_size = l.self_layer->workspace_size;
l.output_layer = malloc(sizeof(layer));
fprintf(stderr, "\t\t");
*(l.output_layer) = make_convolutional_layer(batch*steps, h, w, hidden_filters, output_filters, 3, 1, 1, activation, batch_normalize, 0, 0, 0, 0, 0);
*(l.output_layer) = make_convolutional_layer(batch, steps, h, w, hidden_filters, output_filters, 3, 1, 1, activation, batch_normalize, 0, 0, 0, 0, 0);
l.output_layer->batch = batch;
if (l.workspace_size < l.output_layer->workspace_size) l.workspace_size = l.output_layer->workspace_size;
l.output = l.output_layer->output;
l.delta = l.output_layer->delta;
@ -92,6 +95,7 @@ void forward_crnn_layer(layer l, network_state state)
{
network_state s = {0};
s.train = state.train;
s.workspace = state.workspace;
int i;
layer input_layer = *(l.input_layer);
layer self_layer = *(l.self_layer);
@ -133,6 +137,7 @@ void backward_crnn_layer(layer l, network_state state)
{
network_state s = {0};
s.train = state.train;
s.workspace = state.workspace;
int i;
layer input_layer = *(l.input_layer);
layer self_layer = *(l.self_layer);
@ -206,6 +211,7 @@ void forward_crnn_layer_gpu(layer l, network_state state)
{
network_state s = {0};
s.train = state.train;
s.workspace = state.workspace;
int i;
layer input_layer = *(l.input_layer);
layer self_layer = *(l.self_layer);
@ -247,6 +253,7 @@ void backward_crnn_layer_gpu(layer l, network_state state)
{
network_state s = {0};
s.train = state.train;
s.workspace = state.workspace;
int i;
layer input_layer = *(l.input_layer);
layer self_layer = *(l.self_layer);