Remove comments

official/projects/detr/dataloaders/detr_input.py

@@ -92,7 +92,6 @@ class Parser(parser.Parser):
 
     image_shape = tf.shape(image)[:2]
     boxes = box_ops.denormalize_boxes(boxes, image_shape)
-    gt_boxes = boxes
     short_side = scales[0]
     image, image_info = preprocess_ops.resize_image(
         image,
@@ -126,7 +125,6 @@ class Parser(parser.Parser):
 
   def _parse_eval_data(self, data):
     """Parses data for training and evaluation."""
-    groundtruths = {}
     classes = data['groundtruth_classes']
     boxes = data['groundtruth_boxes']
     is_crowd = data['groundtruth_is_crowd']

official/projects/detr/modeling/detr.py

@@ -114,10 +114,6 @@ class DETR(tf.keras.Model):
     self._dropout_rate = dropout_rate
     if hidden_size % 2 != 0:
       raise ValueError("hidden_size must be a multiple of 2.")
-    # TODO(frederickliu): Consider using the backbone factory.
-    # TODO(frederickliu): Add to factory once we get skeleton code in.
-    #self._backbone = resnet.ResNet(101, bn_trainable=False)
-    # (gunho) use backbone factory
     self._backbone = backbone
 
   def build(self, input_shape=None):