#covfefe

include/darknet.h

@@ -0,0 +1,538 @@
+#ifndef DARKNET_API
+#define DARKNET_API
+#include <stdlib.h>
+
+extern int gpu_index;
+
+#ifdef GPU
+    #define BLOCK 512
+
+    #include "cuda_runtime.h"
+    #include "curand.h"
+    #include "cublas_v2.h"
+
+    #ifdef CUDNN
+    #include "cudnn.h"
+    #endif
+#endif
+
+#ifndef __cplusplus
+    #ifdef OPENCV
+    #include "opencv2/highgui/highgui_c.h"
+    #include "opencv2/imgproc/imgproc_c.h"
+    #include "opencv2/core/version.hpp"
+    #if CV_MAJOR_VERSION == 3
+    #include "opencv2/videoio/videoio_c.h"
+    #endif
+    #endif
+#endif
+
+typedef struct{
+    int *leaf;
+    int n;
+    int *parent;
+    int *child;
+    int *group;
+    char **name;
+
+    int groups;
+    int *group_size;
+    int *group_offset;
+} tree;
+
+typedef enum{
+    LOGISTIC, RELU, RELIE, LINEAR, RAMP, TANH, PLSE, LEAKY, ELU, LOGGY, STAIR, HARDTAN, LHTAN
+}ACTIVATION;
+
+typedef enum {
+    CONVOLUTIONAL,
+    DECONVOLUTIONAL,
+    CONNECTED,
+    MAXPOOL,
+    SOFTMAX,
+    DETECTION,
+    DROPOUT,
+    CROP,
+    ROUTE,
+    COST,
+    NORMALIZATION,
+    AVGPOOL,
+    LOCAL,
+    SHORTCUT,
+    ACTIVE,
+    RNN,
+    GRU,
+    CRNN,
+    BATCHNORM,
+    NETWORK,
+    XNOR,
+    REGION,
+    REORG,
+    BLANK
+} LAYER_TYPE;
+
+typedef enum{
+    SSE, MASKED, L1, SMOOTH
+} COST_TYPE;
+
+struct network;
+typedef struct network network;
+
+struct layer;
+typedef struct layer layer;
+
+struct layer{
+    LAYER_TYPE type;
+    ACTIVATION activation;
+    COST_TYPE cost_type;
+    void (*forward)   (struct layer, struct network);
+    void (*backward)  (struct layer, struct network);
+    void (*update)    (struct layer, int, float, float, float);
+    void (*forward_gpu)   (struct layer, struct network);
+    void (*backward_gpu)  (struct layer, struct network);
+    void (*update_gpu)    (struct layer, int, float, float, float);
+    int batch_normalize;
+    int shortcut;
+    int batch;
+    int forced;
+    int flipped;
+    int inputs;
+    int outputs;
+    int nweights;
+    int nbiases;
+    int extra;
+    int truths;
+    int h,w,c;
+    int out_h, out_w, out_c;
+    int n;
+    int max_boxes;
+    int groups;
+    int size;
+    int side;
+    int stride;
+    int reverse;
+    int flatten;
+    int spatial;
+    int pad;
+    int sqrt;
+    int flip;
+    int index;
+    int binary;
+    int xnor;
+    int steps;
+    int hidden;
+    int truth;
+    float smooth;
+    float dot;
+    float angle;
+    float jitter;
+    float saturation;
+    float exposure;
+    float shift;
+    float ratio;
+    float learning_rate_scale;
+    int softmax;
+    int classes;
+    int coords;
+    int background;
+    int rescore;
+    int objectness;
+    int does_cost;
+    int joint;
+    int noadjust;
+    int reorg;
+    int log;
+
+    int adam;
+    float B1;
+    float B2;
+    float eps;
+    int t;
+
+    float alpha;
+    float beta;
+    float kappa;
+
+    float coord_scale;
+    float object_scale;
+    float noobject_scale;
+    float class_scale;
+    int bias_match;
+    int random;
+    float thresh;
+    int classfix;
+    int absolute;
+
+    int onlyforward;
+    int stopbackward;
+    int dontload;
+    int dontloadscales;
+
+    float temperature;
+    float probability;
+    float scale;
+
+    char  * cweights;
+    int   * indexes;
+    int   * input_layers;
+    int   * input_sizes;
+    int   * map;
+    float * rand;
+    float * cost;
+    float * state;
+    float * prev_state;
+    float * forgot_state;
+    float * forgot_delta;
+    float * state_delta;
+
+    float * concat;
+    float * concat_delta;
+
+    float * binary_weights;
+
+    float * biases;
+    float * bias_updates;
+
+    float * scales;
+    float * scale_updates;
+
+    float * weights;
+    float * weight_updates;
+
+    float * delta;
+    float * output;
+    float * squared;
+    float * norms;
+
+    float * spatial_mean;
+    float * mean;
+    float * variance;
+
+    float * mean_delta;
+    float * variance_delta;
+
+    float * rolling_mean;
+    float * rolling_variance;
+
+    float * x;
+    float * x_norm;
+
+    float * m;
+    float * v;
+    
+    float * bias_m;
+    float * bias_v;
+    float * scale_m;
+    float * scale_v;
+
+    float * z_cpu;
+    float * r_cpu;
+    float * h_cpu;
+
+    float * binary_input;
+
+    struct layer *input_layer;
+    struct layer *self_layer;
+    struct layer *output_layer;
+
+    struct layer *input_gate_layer;
+    struct layer *state_gate_layer;
+    struct layer *input_save_layer;
+    struct layer *state_save_layer;
+    struct layer *input_state_layer;
+    struct layer *state_state_layer;
+
+    struct layer *input_z_layer;
+    struct layer *state_z_layer;
+
+    struct layer *input_r_layer;
+    struct layer *state_r_layer;
+
+    struct layer *input_h_layer;
+    struct layer *state_h_layer;
+
+    tree *softmax_tree;
+
+    size_t workspace_size;
+
+    #ifdef GPU
+    int *indexes_gpu;
+
+    float *z_gpu;
+    float *r_gpu;
+    float *h_gpu;
+
+    float *m_gpu;
+    float *v_gpu;
+    float *bias_m_gpu;
+    float *scale_m_gpu;
+    float *bias_v_gpu;
+    float *scale_v_gpu;
+
+    float * prev_state_gpu;
+    float * forgot_state_gpu;
+    float * forgot_delta_gpu;
+    float * state_gpu;
+    float * state_delta_gpu;
+    float * gate_gpu;
+    float * gate_delta_gpu;
+    float * save_gpu;
+    float * save_delta_gpu;
+    float * concat_gpu;
+    float * concat_delta_gpu;
+
+    float *binary_input_gpu;
+    float *binary_weights_gpu;
+
+    float * mean_gpu;
+    float * variance_gpu;
+
+    float * rolling_mean_gpu;
+    float * rolling_variance_gpu;
+
+    float * variance_delta_gpu;
+    float * mean_delta_gpu;
+
+    float * x_gpu;
+    float * x_norm_gpu;
+    float * weights_gpu;
+    float * weight_updates_gpu;
+
+    float * biases_gpu;
+    float * bias_updates_gpu;
+
+    float * scales_gpu;
+    float * scale_updates_gpu;
+
+    float * output_gpu;
+    float * delta_gpu;
+    float * rand_gpu;
+    float * squared_gpu;
+    float * norms_gpu;
+    #ifdef CUDNN
+    cudnnTensorDescriptor_t srcTensorDesc, dstTensorDesc;
+    cudnnTensorDescriptor_t dsrcTensorDesc, ddstTensorDesc;
+    cudnnTensorDescriptor_t normTensorDesc;
+    cudnnFilterDescriptor_t weightDesc;
+    cudnnFilterDescriptor_t dweightDesc;
+    cudnnConvolutionDescriptor_t convDesc;
+    cudnnConvolutionFwdAlgo_t fw_algo;
+    cudnnConvolutionBwdDataAlgo_t bd_algo;
+    cudnnConvolutionBwdFilterAlgo_t bf_algo;
+    #endif
+    #endif
+};
+
+void free_layer(layer);
+
+typedef enum {
+    CONSTANT, STEP, EXP, POLY, STEPS, SIG, RANDOM
+} learning_rate_policy;
+
+typedef struct network{
+    int n;
+    int batch;
+    int *seen;
+    float epoch;
+    int subdivisions;
+    float momentum;
+    float decay;
+    layer *layers;
+    float *output;
+    learning_rate_policy policy;
+
+    float learning_rate;
+    float gamma;
+    float scale;
+    float power;
+    int time_steps;
+    int step;
+    int max_batches;
+    float *scales;
+    int   *steps;
+    int num_steps;
+    int burn_in;
+
+    int adam;
+    float B1;
+    float B2;
+    float eps;
+
+    int inputs;
+    int outputs;
+    int truths;
+    int notruth;
+    int h, w, c;
+    int max_crop;
+    int min_crop;
+    int center;
+    float angle;
+    float aspect;
+    float exposure;
+    float saturation;
+    float hue;
+
+    int gpu_index;
+    tree *hierarchy;
+
+    float *input;
+    float *truth;
+    float *delta;
+    float *workspace;
+    int train;
+    int index;
+    float *cost;
+
+    #ifdef GPU
+    float *input_gpu;
+    float *truth_gpu;
+    float *delta_gpu;
+    float *output_gpu;
+    #endif
+
+} network;
+
+typedef struct {
+    int w;
+    int h;
+    float scale;
+    float rad;
+    float dx;
+    float dy;
+    float aspect;
+} augment_args;
+
+typedef struct {
+    int h;
+    int w;
+    int c;
+    float *data;
+} image;
+
+typedef struct{
+    float x, y, w, h;
+} box;
+
+typedef struct matrix{
+    int rows, cols;
+    float **vals;
+} matrix;
+
+
+typedef struct{
+    int w, h;
+    matrix X;
+    matrix y;
+    int shallow;
+    int *num_boxes;
+    box **boxes;
+} data;
+
+typedef enum {
+    CLASSIFICATION_DATA, DETECTION_DATA, CAPTCHA_DATA, REGION_DATA, IMAGE_DATA, COMPARE_DATA, WRITING_DATA, SWAG_DATA, TAG_DATA, OLD_CLASSIFICATION_DATA, STUDY_DATA, DET_DATA, SUPER_DATA, LETTERBOX_DATA, REGRESSION_DATA, SEGMENTATION_DATA
+} data_type;
+
+typedef struct load_args{
+    int threads;
+    char **paths;
+    char *path;
+    int n;
+    int m;
+    char **labels;
+    int h;
+    int w;
+    int out_w;
+    int out_h;
+    int nh;
+    int nw;
+    int num_boxes;
+    int min, max, size;
+    int classes;
+    int background;
+    int scale;
+    int center;
+    float jitter;
+    float angle;
+    float aspect;
+    float saturation;
+    float exposure;
+    float hue;
+    data *d;
+    image *im;
+    image *resized;
+    data_type type;
+    tree *hierarchy;
+} load_args;
+
+typedef struct{
+    int id;
+    float x,y,w,h;
+    float left, right, top, bottom;
+} box_label;
+
+
+network load_network(char *cfg, char *weights, int clear);
+load_args get_base_args(network net);
+
+void free_data(data d);
+
+typedef struct node{
+    void *val;
+    struct node *next;
+    struct node *prev;
+} node;
+
+typedef struct list{
+    int size;
+    node *front;
+    node *back;
+} list;
+
+pthread_t load_data(load_args args);
+list *read_data_cfg(char *filename);
+list *read_cfg(char *filename);
+
+
+#include "activation_layer.h"
+#include "activations.h"
+#include "avgpool_layer.h"
+#include "batchnorm_layer.h"
+#include "blas.h"
+#include "box.h"
+#include "classifier.h"
+#include "col2im.h"
+#include "connected_layer.h"
+#include "convolutional_layer.h"
+#include "cost_layer.h"
+#include "crnn_layer.h"
+#include "crop_layer.h"
+#include "cuda.h"
+#include "data.h"
+#include "deconvolutional_layer.h"
+#include "demo.h"
+#include "detection_layer.h"
+#include "dropout_layer.h"
+#include "gemm.h"
+#include "gru_layer.h"
+#include "im2col.h"
+#include "image.h"
+#include "layer.h"
+#include "list.h"
+#include "local_layer.h"
+#include "matrix.h"
+#include "maxpool_layer.h"
+#include "network.h"
+#include "normalization_layer.h"
+#include "option_list.h"
+#include "parser.h"
+#include "region_layer.h"
+#include "reorg_layer.h"
+#include "rnn_layer.h"
+#include "route_layer.h"
+#include "shortcut_layer.h"
+#include "softmax_layer.h"
+#include "stb_image.h"
+#include "stb_image_write.h"
+#include "tree.h"
+#include "utils.h"
+#endif