darknet/src/layer.h
2015-07-13 23:25:08 -07:00

104 lines
1.6 KiB
C

#ifndef BASE_LAYER_H
#define BASE_LAYER_H
#include "activations.h"
typedef enum {
CONVOLUTIONAL,
DECONVOLUTIONAL,
CONNECTED,
MAXPOOL,
SOFTMAX,
DETECTION,
DROPOUT,
CROP,
ROUTE,
COST,
NORMALIZATION,
AVGPOOL
} LAYER_TYPE;
typedef enum{
SSE, MASKED
} COST_TYPE;
typedef struct {
LAYER_TYPE type;
ACTIVATION activation;
COST_TYPE cost_type;
int batch;
int inputs;
int outputs;
int h,w,c;
int out_h, out_w, out_c;
int n;
int groups;
int size;
int stride;
int pad;
int crop_width;
int crop_height;
int flip;
float angle;
float saturation;
float exposure;
int classes;
int coords;
int background;
int rescore;
int objectness;
int does_cost;
int joint;
int noadjust;
float alpha;
float beta;
float kappa;
int dontload;
float probability;
float scale;
int *indexes;
float *rand;
float *cost;
float *filters;
float *filter_updates;
float *biases;
float *bias_updates;
float *weights;
float *weight_updates;
float *col_image;
int * input_layers;
int * input_sizes;
float * delta;
float * output;
float * squared;
float * norms;
#ifdef GPU
int *indexes_gpu;
float * filters_gpu;
float * filter_updates_gpu;
float * col_image_gpu;
float * weights_gpu;
float * biases_gpu;
float * weight_updates_gpu;
float * bias_updates_gpu;
float * output_gpu;
float * delta_gpu;
float * rand_gpu;
float * squared_gpu;
float * norms_gpu;
#endif
} layer;
#endif