2020-1-capstone-design1 / PET_Project1

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dd2c40c2 1 parent a87016b1

hot fix for reuse

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Showing 1 changed file with 3 additions and 3 deletions
...@@ -1751,7 +1751,7 @@ ...@@ -1751,7 +1751,7 @@
1751 " ### Model definition\n", 1751 " ### Model definition\n",
1752 " yolo_model = yolov3(class_num, anchors, use_label_smooth, use_focal_loss, batch_norm_decay, weight_decay, use_static_shape=False)\n", 1752 " yolo_model = yolov3(class_num, anchors, use_label_smooth, use_focal_loss, batch_norm_decay, weight_decay, use_static_shape=False)\n",
1753 "\n", 1753 "\n",
1754 - " with tf.variable_scope('yolov3', reuse=True):\n", 1754 + " with tf.variable_scope('yolov3', reuse=tf.AUTO_REUSE):\n",
1755 " pred_feature_maps = yolo_model.forward(image, is_training=is_training)\n", 1755 " pred_feature_maps = yolo_model.forward(image, is_training=is_training)\n",
1756 "\n", 1756 "\n",
1757 " loss = yolo_model.compute_loss(pred_feature_maps, y_true)\n", 1757 " loss = yolo_model.compute_loss(pred_feature_maps, y_true)\n",
...@@ -1989,7 +1989,7 @@ ...@@ -1989,7 +1989,7 @@
1989 "\n", 1989 "\n",
1990 " ### Model definition\n", 1990 " ### Model definition\n",
1991 " yolo_model = yolov3(args.class_num, args.anchors)\n", 1991 " yolo_model = yolov3(args.class_num, args.anchors)\n",
1992 - " with tf.variable_scope('yolov3', reuse=True):\n", 1992 + " with tf.variable_scope('yolov3', reuse=tf.AUTO_REUSE):\n",
1993 " pred_feature_maps = yolo_model.forward(image, is_training=is_training)\n", 1993 " pred_feature_maps = yolo_model.forward(image, is_training=is_training)\n",
1994 " loss = yolo_model.compute_loss(pred_feature_maps, y_true)\n", 1994 " loss = yolo_model.compute_loss(pred_feature_maps, y_true)\n",
1995 " y_pred = yolo_model.predict(pred_feature_maps)\n", 1995 " y_pred = yolo_model.predict(pred_feature_maps)\n",
...@@ -2083,7 +2083,7 @@ ...@@ -2083,7 +2083,7 @@
2083 " with tf.Session() as sess:\n", 2083 " with tf.Session() as sess:\n",
2084 " input_data = tf.placeholder(tf.float32, [1, args.new_size[1], args.new_size[0], 3], name='input_data')\n", 2084 " input_data = tf.placeholder(tf.float32, [1, args.new_size[1], args.new_size[0], 3], name='input_data')\n",
2085 " yolo_model = yolov3(args.num_class, args.anchors)\n", 2085 " yolo_model = yolov3(args.num_class, args.anchors)\n",
2086 - " with tf.variable_scope('yolov3', reuse=True):\n", 2086 + " with tf.variable_scope('yolov3', reuse=tf.AUTO_REUSE):\n",
2087 " pred_feature_maps = yolo_model.forward(input_data, False)\n", 2087 " pred_feature_maps = yolo_model.forward(input_data, False)\n",
2088 " pred_boxes, pred_confs, pred_probs = yolo_model.predict(pred_feature_maps)\n", 2088 " pred_boxes, pred_confs, pred_probs = yolo_model.predict(pred_feature_maps)\n",
2089 "\n", 2089 "\n",
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