김성주

hot fix for reuse

......@@ -1751,7 +1751,7 @@
" ### Model definition\n",
" yolo_model = yolov3(class_num, anchors, use_label_smooth, use_focal_loss, batch_norm_decay, weight_decay, use_static_shape=False)\n",
"\n",
" with tf.variable_scope('yolov3', reuse=True):\n",
" with tf.variable_scope('yolov3', reuse=tf.AUTO_REUSE):\n",
" pred_feature_maps = yolo_model.forward(image, is_training=is_training)\n",
"\n",
" loss = yolo_model.compute_loss(pred_feature_maps, y_true)\n",
......@@ -1989,7 +1989,7 @@
"\n",
" ### Model definition\n",
" yolo_model = yolov3(args.class_num, args.anchors)\n",
" with tf.variable_scope('yolov3', reuse=True):\n",
" with tf.variable_scope('yolov3', reuse=tf.AUTO_REUSE):\n",
" pred_feature_maps = yolo_model.forward(image, is_training=is_training)\n",
" loss = yolo_model.compute_loss(pred_feature_maps, y_true)\n",
" y_pred = yolo_model.predict(pred_feature_maps)\n",
......@@ -2083,7 +2083,7 @@
" with tf.Session() as sess:\n",
" input_data = tf.placeholder(tf.float32, [1, args.new_size[1], args.new_size[0], 3], name='input_data')\n",
" yolo_model = yolov3(args.num_class, args.anchors)\n",
" with tf.variable_scope('yolov3', reuse=True):\n",
" with tf.variable_scope('yolov3', reuse=tf.AUTO_REUSE):\n",
" pred_feature_maps = yolo_model.forward(input_data, False)\n",
" pred_boxes, pred_confs, pred_probs = yolo_model.predict(pred_feature_maps)\n",
"\n",
......