| #include "activation_layer.h" |
| #include "utils.h" |
| #include "cuda_dark.h" |
| #include "blas.h" |
| #include "gemm.h" |
|
|
| #include <math.h> |
| #include <stdio.h> |
| #include <stdlib.h> |
| #include <string.h> |
|
|
| layer make_activation_layer(int batch, int inputs, ACTIVATION activation) |
| { |
| layer l = {0}; |
| l.type = ACTIVE; |
|
|
| l.inputs = inputs; |
| l.outputs = inputs; |
| l.batch=batch; |
|
|
| l.output = calloc(batch*inputs, sizeof(float*)); |
| l.delta = calloc(batch*inputs, sizeof(float*)); |
|
|
| l.forward = forward_activation_layer; |
| l.backward = backward_activation_layer; |
| #ifdef GPU |
| l.forward_gpu = forward_activation_layer_gpu; |
| l.backward_gpu = backward_activation_layer_gpu; |
|
|
| l.output_gpu = cuda_make_array(l.output, inputs*batch); |
| l.delta_gpu = cuda_make_array(l.delta, inputs*batch); |
| #endif |
| l.activation = activation; |
| fprintf(stderr, "Activation Layer: %d inputs\n", inputs); |
| return l; |
| } |
|
|
| void forward_activation_layer(layer l, network net) |
| { |
| copy_cpu(l.outputs*l.batch, net.input, 1, l.output, 1); |
| activate_array(l.output, l.outputs*l.batch, l.activation); |
| } |
|
|
| void backward_activation_layer(layer l, network net) |
| { |
| gradient_array(l.output, l.outputs*l.batch, l.activation, l.delta); |
| copy_cpu(l.outputs*l.batch, l.delta, 1, net.delta, 1); |
| } |
|
|
| #ifdef GPU |
|
|
| void forward_activation_layer_gpu(layer l, network net) |
| { |
| copy_gpu(l.outputs*l.batch, net.input_gpu, 1, l.output_gpu, 1); |
| activate_array_gpu(l.output_gpu, l.outputs*l.batch, l.activation); |
| } |
|
|
| void backward_activation_layer_gpu(layer l, network net) |
| { |
| gradient_array_gpu(l.output_gpu, l.outputs*l.batch, l.activation, l.delta_gpu); |
| copy_gpu(l.outputs*l.batch, l.delta_gpu, 1, net.delta_gpu, 1); |
| } |
| #endif |
|
|