minor fix

bin/yolov2-voc.cfg

@@ -24,7 +24,6 @@ scales=.1,.1
 
 input_calibration = 15.8025, 11.6111, 10.9857, 14.9883, 11.6514, 14.9023, 15.4301, 13.8702, 15.3739, 15.584, 15.3044, 15.4963, 15.4139, 15.398, 15.7311, 15.2932, 15.7355, 15.2879, 5.79389, 15.6349, 15.5533, 15.453, 15.7935, 16
 
-
 [convolutional]
 batch_normalize=1
 filters=32

src/additionally.c

@@ -139,12 +139,14 @@ void binary_align_weights(convolutional_layer *l)
     l->align_bit_weights = calloc(l->align_bit_weights_size, sizeof(char));
 
     size_t i, j;
+
     // align A without transpose
     for (i = 0; i < m; ++i) {
         for (j = 0; j < k; ++j) {
             align_weights[i*new_lda + j] = l->binary_weights[i*k + j];
         }
     }
+
     float_to_bit(align_weights, l->align_bit_weights, align_weights_size);
 
     l->mean_arr = calloc(l->n, sizeof(float));

src/main.c

@@ -272,7 +272,8 @@ int main(int argc, char **argv)
     }
 
 	_mkdir("dbg");
-	m_dbg = 1;
+
+	m_dbg = 0;
 
     if (argc < 2) {
         fprintf(stderr, "usage: %s <function>\n", argv[0]);

src/yolov2_forward_network.c

@@ -1,6 +1,7 @@
 #include "additionally.h"    // some definitions from: im2col.h, blas.h, list.h, utils.h, activations.h, tree.h, layer.h, network.h
 // softmax_layer.h, reorg_layer.h, route_layer.h, region_layer.h, maxpool_layer.h, convolutional_layer.h
 
+
 // binary transpose
 size_t binary_transpose_align_input(int k, int n, float *b, char **t_bit_input, size_t ldb_align, int bit_align)
 {
@@ -30,7 +31,7 @@ void forward_convolutional_layer_cpu(layer l, int layer_id, network_state state)
         if (!l.align_bit_weights)
         {
             binarize_weights(l.weights, l.n, l.c*l.size*l.size, l.binary_weights);
-            //printf("\n binarize_weights l.align_bit_weights = %p \n", l.align_bit_weights);
+            printf("\n binarize_weights l.align_bit_weights = %p \n", l.align_bit_weights);
         }
 
 		binarize_cpu(state.input, l.c*l.h*l.w*l.batch, l.binary_input);
@@ -92,6 +93,7 @@ void forward_convolutional_layer_cpu(layer l, int layer_id, network_state state)
                 }
     }
 
+
     int const out_size = out_h*out_w;
 
     // 2. Batch normalization