| | |
| | | cl_read_array(layer.biases_cl, layer.biases, layer.outputs); |
| | | } |
| | | |
| | | void push_connected_layer(connected_layer layer) |
| | | { |
| | | cl_write_array(layer.weights_cl, layer.weights, layer.inputs*layer.outputs); |
| | | cl_write_array(layer.biases_cl, layer.biases, layer.outputs); |
| | | } |
| | | |
| | | void update_connected_layer_gpu(connected_layer layer) |
| | | { |
| | | axpy_ongpu(layer.outputs, layer.learning_rate, layer.bias_updates_cl, 1, layer.biases_cl, 1); |
| | |
| | | { |
| | | int i; |
| | | for(i = 0; i < layer.batch; ++i){ |
| | | cl_mem sub = cl_sub_array(layer.output_cl, i*layer.outputs, layer.outputs); |
| | | copy_ongpu(layer.outputs, layer.biases_cl, 1, sub, 1); |
| | | clReleaseMemObject(sub); |
| | | copy_ongpu_offset(layer.outputs, layer.biases_cl, 0, 1, layer.output_cl, i*layer.outputs, 1); |
| | | } |
| | | int m = layer.batch; |
| | | int k = layer.inputs; |
| | |
| | | int i; |
| | | gradient_array_ongpu(layer.output_cl, layer.outputs*layer.batch, layer.activation, layer.delta_cl); |
| | | for(i = 0; i < layer.batch; ++i){ |
| | | cl_mem sub = cl_sub_array(layer.delta_cl, i*layer.outputs, layer.outputs); |
| | | axpy_ongpu(layer.outputs, 1, sub, 1, layer.bias_updates_cl, 1); |
| | | clReleaseMemObject(sub); |
| | | axpy_ongpu_offset(layer.outputs, 1, layer.delta_cl, i*layer.outputs, 1, layer.bias_updates_cl, 0, 1); |
| | | } |
| | | int m = layer.inputs; |
| | | int k = layer.batch; |