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 | 94 +++++++++++++++++++++++++++++++++++++++--------
1 files changed, 78 insertions(+), 16 deletions(-)
diff --git a/src/network.h b/src/network.h
index c75804d..f4f8b5c 100644
--- a/src/network.h
+++ b/src/network.h
@@ -3,32 +3,89 @@
#define NETWORK_H
#include "image.h"
+#include "layer.h"
#include "data.h"
typedef enum {
- CONVOLUTIONAL,
- CONNECTED,
- MAXPOOL,
- SOFTMAX
-} 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, float *input);
-float backward_network(network net, float *input, float *truth);
-void update_network(network net, float step, float momentum, float decay);
-float train_network_sgd(network net, data d, int n, float step, float momentum,float decay);
-float train_network_batch(network net, data d, int n, float step, float momentum,float decay);
-void train_network(network net, data d, float step, float momentum, float decay);
+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);
@@ -40,8 +97,13 @@
int get_predicted_class_network(network net);
void print_network(network net);
void visualize_network(network net);
-void save_network(network net, char *filename);
-int reset_network_size(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);
+
+int get_network_nuisance(network net);
+int get_network_background(network net);
#endif
--
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