darknet/src/activation_layer.c
Joseph Redmon 8215a8864d 🔥 🐛 🔥
2017-06-18 13:05:37 -07:00

64 lines
1.7 KiB
C

#include "activation_layer.h"
#include "utils.h"
#include "cuda.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