From 08b757a0bf76efe8c76b453063a1bb19315bcaa6 Mon Sep 17 00:00:00 2001
From: Joseph Redmon <pjreddie@gmail.com>
Date: Wed, 14 Jan 2015 20:18:57 +0000
Subject: [PATCH] Stable, needs to be way faster
---
src/network.h | 62 ++++++++++++++++++++++++-------
1 files changed, 48 insertions(+), 14 deletions(-)
diff --git a/src/network.h b/src/network.h
index 975c3dd..c6c7790 100644
--- a/src/network.h
+++ b/src/network.h
@@ -2,6 +2,7 @@
#ifndef NETWORK_H
#define NETWORK_H
+#include "opencl.h"
#include "image.h"
#include "data.h"
@@ -9,30 +10,58 @@
CONVOLUTIONAL,
CONNECTED,
MAXPOOL,
- SOFTMAX
+ SOFTMAX,
+ NORMALIZATION,
+ DROPOUT,
+ FREEWEIGHT,
+ CROP,
+ COST
} LAYER_TYPE;
typedef struct {
int n;
+ int batch;
+ float learning_rate;
+ float momentum;
+ float decay;
void **layers;
LAYER_TYPE *types;
int outputs;
- double *output;
+ float *output;
+
+ #ifdef GPU
+ cl_mem *input_cl;
+ cl_mem *truth_cl;
+ #endif
} network;
-network make_network(int n);
-void forward_network(network net, double *input);
-void backward_network(network net, double *input, double *truth);
-void update_network(network net, double step, double momentum, double decay);
-double train_network_sgd(network net, data d, int n, double step, double momentum,double decay);
-double train_network_batch(network net, data d, int n, double step, double momentum,double decay);
-void train_network(network net, data d, double step, double momentum, double decay);
+#ifdef GPU
+float train_network_datum_gpu(network net, float *x, float *y);
+float *network_predict_gpu(network net, float *input);
+#endif
+
+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);
+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);
+
matrix network_predict_data(network net, data test);
-double network_accuracy(network net, data d);
-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);
+float *network_predict(network net, float *input);
+float network_accuracy(network net, data d);
+float *network_accuracies(network net, data d);
+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);
@@ -40,6 +69,11 @@
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);
+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);
#endif
--
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