From a392bbd0c957a00e3782c96e7ced84a29ff9dd88 Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Tue, 15 Mar 2016 05:33:02 +0000
Subject: [PATCH] Play along w/ alphago

---
 src/network.h |  104 ++++++++++++++++++++++++++++++++++++++++++++-------
 1 files changed, 89 insertions(+), 15 deletions(-)

diff --git a/src/network.h b/src/network.h
index 10fa6c5..f4f8b5c 100644
--- a/src/network.h
+++ b/src/network.h
@@ -3,33 +3,107 @@
 #define NETWORK_H
 
 #include "image.h"
+#include "layer.h"
 #include "data.h"
 
 typedef enum {
-    CONVOLUTIONAL,
-    CONNECTED,
-    MAXPOOL
-} LAYER_TYPE;
+    CONSTANT, STEP, EXP, POLY, STEPS, SIG
+} learning_rate_policy;
 
-typedef struct {
+typedef struct network{
     int n;
-    void **layers;
-    LAYER_TYPE *types;
+    int batch;
+    int *seen;
+    float epoch;
+    int subdivisions;
+    float momentum;
+    float decay;
+    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 inputs;
+    int h, w, c;
+    int max_crop;
+
+    #ifdef GPU
+    float **input_gpu;
+    float **truth_gpu;
+    #endif
 } network;
 
+typedef struct network_state {
+    float *truth;
+    float *input;
+    float *delta;
+    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);
-void forward_network(network net, double *input);
-void learn_network(network net, double *input);
-void update_network(network net, double step);
-void train_network_batch(network net, batch b);
-double *get_network_output(network net);
-double *get_network_output_layer(network net, int i);
-double *get_network_delta_layer(network net, int i);
-double *get_network_delta(network net);
+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, 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);
+float *get_network_output_layer(network net, int i);
+float *get_network_delta_layer(network net, int i);
+float *get_network_delta(network net);
 int get_network_output_size_layer(network net, int i);
 int get_network_output_size(network net);
 image get_network_image(network net);
 image get_network_image_layer(network net, int i);
+int get_predicted_class_network(network net);
+void print_network(network net);
+void visualize_network(network net);
+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);
+
+int get_network_nuisance(network net);
+int get_network_background(network net);
 
 #endif
 

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