From ae43c2bc32fbb838bfebeeaf2c2b058ccab5c83c Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@burninator.cs.washington.edu>
Date: Thu, 23 Jun 2016 05:31:14 +0000
Subject: [PATCH] hi

---
 src/network.h |   76 ++++++++++++++++++++++++++-----------
 1 files changed, 53 insertions(+), 23 deletions(-)

diff --git a/src/network.h b/src/network.h
index d2fb346..af64e06 100644
--- a/src/network.h
+++ b/src/network.h
@@ -3,33 +3,43 @@
 #define NETWORK_H
 
 #include "image.h"
+#include "layer.h"
 #include "data.h"
 
 typedef enum {
-    CONVOLUTIONAL,
-    DECONVOLUTIONAL,
-    CONNECTED,
-    MAXPOOL,
-    SOFTMAX,
-    DETECTION,
-    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;
-    int seen;
-    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 inputs;
+    int h, w, c;
+    int max_crop;
+    int min_crop;
 
     #ifdef GPU
     float **input_gpu;
@@ -37,29 +47,47 @@
     #endif
 } network;
 
+typedef struct network_state {
+    float *truth;
+    float *input;
+    float *delta;
+    float *workspace;
+    int train;
+    int index;
+    network net;
+} network_state;
+
 #ifdef GPU
 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);
 #endif
 
+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, int batch);
-void forward_network(network net, float *input, float *truth, int train);
-void backward_network(network net, float *input, float *truth);
+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(network net, data d);
 float train_network_batch(network net, data d, int n);
 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);
+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);
@@ -73,11 +101,13 @@
 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);
-void set_learning_network(network *net, float rate, float momentum, float decay);
 int get_network_input_size(network net);
 float get_network_cost(network net);
 
+int get_network_nuisance(network net);
+int get_network_background(network net);
+
 #endif
 

--
Gitblit v1.10.0