From 5b6be00d4b1ffd671c20c4c72d2239c924eaa3d4 Mon Sep 17 00:00:00 2001
From: AlexeyAB <alexeyab84@gmail.com>
Date: Thu, 23 Aug 2018 12:28:34 +0000
Subject: [PATCH] Added yolov3-tiny_xnor.cfg
---
src/convolutional_layer.h | 59 +++++++++++++++++++++--------------------------------------
1 files changed, 21 insertions(+), 38 deletions(-)
diff --git a/src/convolutional_layer.h b/src/convolutional_layer.h
index 5cf8adc..8869a3c 100644
--- a/src/convolutional_layer.h
+++ b/src/convolutional_layer.h
@@ -2,41 +2,12 @@
#define CONVOLUTIONAL_LAYER_H
#include "cuda.h"
-#include "params.h"
#include "image.h"
#include "activations.h"
+#include "layer.h"
+#include "network.h"
-typedef struct {
- int batch;
- int h,w,c;
- int n;
- int size;
- int stride;
- int pad;
- float *filters;
- float *filter_updates;
-
- float *biases;
- float *bias_updates;
-
- float *col_image;
- float *delta;
- float *output;
-
- #ifdef GPU
- float * filters_gpu;
- float * filter_updates_gpu;
-
- float * biases_gpu;
- float * bias_updates_gpu;
-
- float * col_image_gpu;
- float * delta_gpu;
- float * output_gpu;
- #endif
-
- ACTIVATION activation;
-} convolutional_layer;
+typedef layer convolutional_layer;
#ifdef GPU
void forward_convolutional_layer_gpu(convolutional_layer layer, network_state state);
@@ -46,27 +17,39 @@
void push_convolutional_layer(convolutional_layer layer);
void pull_convolutional_layer(convolutional_layer layer);
-void bias_output_gpu(float *output, float *biases, int batch, int n, int size);
+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);
-void resize_convolutional_layer(convolutional_layer *layer, int h, int w);
+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_weights(convolutional_layer l, float scale, float trans);
+void rgbgr_weights(convolutional_layer l);
#endif
--
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