darknet/src/convolutional_layer.h

#ifndef CONVOLUTIONAL_LAYER_H
#define CONVOLUTIONAL_LAYER_H

#include "cuda.h"
#include "params.h"
#include "image.h"
#include "activations.h"
#include "layer.h"

typedef layer convolutional_layer;

#ifdef GPU
void forward_convolutional_layer_gpu(convolutional_layer layer, network_state state);
void backward_convolutional_layer_gpu(convolutional_layer layer, network_state state);
void update_convolutional_layer_gpu(convolutional_layer layer, int batch, float learning_rate, float momentum, float decay);

void push_convolutional_layer(convolutional_layer layer);
void pull_convolutional_layer(convolutional_layer layer);

void bias_output_gpu(float *output, float *biases, int batch, int n, int size);
void backward_bias_gpu(float *bias_updates, float *delta, int batch, int n, int size);
#endif

convolutional_layer make_convolutional_layer(int batch, int h, int w, int c, int n, int size, int stride, int pad, ACTIVATION activation);
void resize_convolutional_layer(convolutional_layer *layer, int h, int w);
void forward_convolutional_layer(const convolutional_layer layer, network_state state);
void update_convolutional_layer(convolutional_layer layer, int batch, float learning_rate, float momentum, float decay);
image *visualize_convolutional_layer(convolutional_layer layer, char *window, image *prev_filters);

void backward_convolutional_layer(convolutional_layer layer, network_state state);

void bias_output(float *output, float *biases, int batch, int n, int size);
void backward_bias(float *bias_updates, float *delta, int batch, int n, int size);

image get_convolutional_image(convolutional_layer layer);
image get_convolutional_delta(convolutional_layer layer);
image get_convolutional_filter(convolutional_layer layer, int i);

int convolutional_out_height(convolutional_layer layer);
int convolutional_out_width(convolutional_layer layer);

#endif