From dbdd31ee211fe8b1ac7e93ceadf7b34b8d304f34 Mon Sep 17 00:00:00 2001
From: Roland Singer <roland.singer@desertbit.com>
Date: Wed, 22 Aug 2018 11:56:41 +0000
Subject: [PATCH] updated README to include information about learning rate adjustment for multiple GPUs

---
 src/convolutional_layer.h |   22 +++++++++++++++-------
 1 files changed, 15 insertions(+), 7 deletions(-)

diff --git a/src/convolutional_layer.h b/src/convolutional_layer.h
index 436ed7e..8869a3c 100644
--- a/src/convolutional_layer.h
+++ b/src/convolutional_layer.h
@@ -2,7 +2,6 @@
 #define CONVOLUTIONAL_LAYER_H
 
 #include "cuda.h"
-#include "params.h"
 #include "image.h"
 #include "activations.h"
 #include "layer.h"
@@ -20,28 +19,37 @@
 
 void add_bias_gpu(float *output, float *biases, int batch, int n, int size);
 void backward_bias_gpu(float *bias_updates, float *delta, int batch, int n, int size);
+#ifdef CUDNN
+void cudnn_convolutional_setup(layer *l, int cudnn_preference);
+void cuda_convert_f32_to_f16(float* input_f32, size_t size, float *output_f16);
+#endif
 #endif
 
-convolutional_layer make_convolutional_layer(int batch, int h, int w, int c, int n, int size, int stride, int pad, ACTIVATION activation, int batch_normalization);
+convolutional_layer make_convolutional_layer(int batch, int h, int w, int c, int n, int size, int stride, int padding, ACTIVATION activation, int batch_normalize, int binary, int xnor, int adam);
 void denormalize_convolutional_layer(convolutional_layer l);
 void resize_convolutional_layer(convolutional_layer *layer, int w, int h);
 void forward_convolutional_layer(const convolutional_layer layer, network_state state);
 void update_convolutional_layer(convolutional_layer layer, int batch, float learning_rate, float momentum, float decay);
-image *visualize_convolutional_layer(convolutional_layer layer, char *window, image *prev_filters);
+image *visualize_convolutional_layer(convolutional_layer layer, char *window, image *prev_weights);
+void binarize_weights(float *weights, int n, int size, float *binary);
+void swap_binary(convolutional_layer *l);
+void binarize_weights2(float *weights, int n, int size, char *binary, float *scales);
+
+void binary_align_weights(convolutional_layer *l);
 
 void backward_convolutional_layer(convolutional_layer layer, network_state state);
 
-void bias_output(float *output, float *biases, int batch, int n, int size);
+void add_bias(float *output, float *biases, int batch, int n, int size);
 void backward_bias(float *bias_updates, float *delta, int batch, int n, int size);
 
 image get_convolutional_image(convolutional_layer layer);
 image get_convolutional_delta(convolutional_layer layer);
-image get_convolutional_filter(convolutional_layer layer, int i);
+image get_convolutional_weight(convolutional_layer layer, int i);
 
 int convolutional_out_height(convolutional_layer layer);
 int convolutional_out_width(convolutional_layer layer);
-void rescale_filters(convolutional_layer l, float scale, float trans);
-void rgbgr_filters(convolutional_layer l);
+void rescale_weights(convolutional_layer l, float scale, float trans);
+void rgbgr_weights(convolutional_layer l);
 
 #endif
 

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