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refactoring and added DARK ZONE

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This commit is contained in:
Joseph Redmon
2015-03-11 22:20:15 -07:00
parent f047cfff99
commit dcb000b553
37 changed files with 640 additions and 918 deletions
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19
src/deconvolutional_layer.h
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@ -2,14 +2,11 @@
#define DECONVOLUTIONAL_LAYER_H
#include "cuda.h"
#include "params.h"
#include "image.h"
#include "activations.h"
typedef struct {
float learning_rate;
float momentum;
float decay;
int batch;
int h,w,c;
int n;
@ -41,18 +38,18 @@ typedef struct {
} deconvolutional_layer;
#ifdef GPU
void forward_deconvolutional_layer_gpu(deconvolutional_layer layer, float * in);
void backward_deconvolutional_layer_gpu(deconvolutional_layer layer, float * in, float * delta_gpu);
void update_deconvolutional_layer_gpu(deconvolutional_layer layer);
void forward_deconvolutional_layer_gpu(deconvolutional_layer layer, network_state state);
void backward_deconvolutional_layer_gpu(deconvolutional_layer layer, network_state state);
void update_deconvolutional_layer_gpu(deconvolutional_layer layer, float learning_rate, float momentum, float decay);
void push_deconvolutional_layer(deconvolutional_layer layer);
void pull_deconvolutional_layer(deconvolutional_layer layer);
#endif
deconvolutional_layer *make_deconvolutional_layer(int batch, int h, int w, int c, int n, int size, int stride, ACTIVATION activation, float learning_rate, float momentum, float decay);
deconvolutional_layer *make_deconvolutional_layer(int batch, int h, int w, int c, int n, int size, int stride, ACTIVATION activation);
void resize_deconvolutional_layer(deconvolutional_layer *layer, int h, int w);
void forward_deconvolutional_layer(const deconvolutional_layer layer, float *in);
void update_deconvolutional_layer(deconvolutional_layer layer);
void backward_deconvolutional_layer(deconvolutional_layer layer, float *in, float *delta);
void forward_deconvolutional_layer(const deconvolutional_layer layer, network_state state);
void update_deconvolutional_layer(deconvolutional_layer layer, float learning_rate, float momentum, float decay);
void backward_deconvolutional_layer(deconvolutional_layer layer, network_state state);
image get_deconvolutional_image(deconvolutional_layer layer);
image get_deconvolutional_delta(deconvolutional_layer layer);