From 6d56c38e8bcb9041335b03f27c192c24dfaedb1c Mon Sep 17 00:00:00 2001
From: AlexeyAB <alexeyab84@gmail.com>
Date: Wed, 28 Mar 2018 23:39:28 +0000
Subject: [PATCH] Merge branch 'master' of github.com:AlexeyAB/darknet
---
src/network.h | 127 ++++++++++++++++++++++++++++++++---------
1 files changed, 98 insertions(+), 29 deletions(-)
diff --git a/src/network.h b/src/network.h
index 7625904..d7f86c1 100644
--- a/src/network.h
+++ b/src/network.h
@@ -2,59 +2,119 @@
#ifndef NETWORK_H
#define NETWORK_H
-#include "opencl.h"
+#include <stdint.h>
+#include "layer.h"
+
+#ifdef __cplusplus
+extern "C" {
+#endif
+
#include "image.h"
#include "data.h"
+#include "tree.h"
typedef enum {
- CONVOLUTIONAL,
- CONNECTED,
- MAXPOOL,
- SOFTMAX,
- NORMALIZATION,
- DROPOUT,
- FREEWEIGHT,
- CROP,
- COST
-} LAYER_TYPE;
+ CONSTANT, STEP, EXP, POLY, STEPS, SIG, RANDOM
+} learning_rate_policy;
-typedef struct {
+typedef struct network{
+ float *workspace;
int n;
int batch;
- float learning_rate;
+ int *seen;
+ float epoch;
+ int subdivisions;
float momentum;
float decay;
- void **layers;
- LAYER_TYPE *types;
+ layer *layers;
int outputs;
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 h, w, c;
+ int max_crop;
+ int min_crop;
+ float angle;
+ float aspect;
+ float exposure;
+ float saturation;
+ float hue;
+
+ int gpu_index;
+ tree *hierarchy;
#ifdef GPU
- cl_mem *input_cl;
- cl_mem *truth_cl;
+ float **input_gpu;
+ float **truth_gpu;
+ float **input16_gpu;
+ float **output16_gpu;
+ size_t *max_input16_size;
+ size_t *max_output16_size;
+ int wait_stream;
#endif
} network;
+typedef struct network_state {
+ float *truth;
+ float *input;
+ float *delta;
+ float *workspace;
+ int train;
+ int index;
+ network net;
+} network_state;
+
#ifdef GPU
-void forward_network_gpu(network net, cl_mem input, cl_mem truth, int train);
-void backward_network_gpu(network net, cl_mem input);
+float train_networks(network *nets, int n, data d, int interval);
+void sync_nets(network *nets, int n, int interval);
+float train_network_datum_gpu(network net, float *x, float *y);
+float *network_predict_gpu(network net, float *input);
+float * get_network_output_gpu_layer(network net, int i);
+float * get_network_delta_gpu_layer(network net, int i);
+float *get_network_output_gpu(network net);
+void forward_network_gpu(network net, network_state state);
+void backward_network_gpu(network net, network_state state);
void update_network_gpu(network net);
-cl_mem get_network_output_cl_layer(network net, int i);
-cl_mem get_network_delta_cl_layer(network net, int i);
-float train_network_sgd_gpu(network net, data d, int n);
-float train_network_data_gpu(network net, data d, int n);
#endif
-network make_network(int n, int batch);
-void forward_network(network net, float *input, float *truth, int train);
-void backward_network(network net, float *input);
+float get_current_rate(network net);
+int get_current_batch(network net);
+void free_network(network net);
+void compare_networks(network n1, network n2, data d);
+char *get_layer_string(LAYER_TYPE a);
+
+network make_network(int n);
+void forward_network(network net, network_state state);
+void backward_network(network net, network_state state);
void update_network(network net);
-float train_network_sgd(network net, data d, int n);
+
+float train_network(network net, data d);
float train_network_batch(network net, data d, int n);
-void train_network(network net, data d);
+float train_network_sgd(network net, data d, int n);
+float train_network_datum(network net, float *x, float *y);
+
matrix network_predict_data(network net, data test);
float *network_predict(network net, float *input);
float network_accuracy(network net, data d);
+float *network_accuracies(network net, data d, int n);
float network_accuracy_multi(network net, data d, int n);
void top_predictions(network net, int n, int *index);
float *get_network_output(network net);
@@ -68,9 +128,18 @@
int get_predicted_class_network(network net);
void print_network(network net);
void visualize_network(network net);
-int resize_network(network net, int h, int w, int c);
+int resize_network(network *net, int w, int h);
+void set_batch_network(network *net, int b);
int get_network_input_size(network net);
float get_network_cost(network net);
+detection *get_network_boxes(network *net, int w, int h, float thresh, float hier, int *map, int relative, int *num, int letter);
+
+int get_network_nuisance(network net);
+int get_network_background(network net);
+
+#ifdef __cplusplus
+}
+#endif
#endif
--
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