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