fixed linting errors (#10053)

official/vision/beta/projects/panoptic_maskrcnn/modeling/panoptic_maskrcnn_model.py

@@ -78,7 +78,7 @@ class PanopticMaskRCNNModel(maskrcnn_model.MaskRCNNModel):
         will allow the segmentation head to use a standlone decoder. Setting
         `segmentation_decoder=None` would enable decoder sharing between
         the MaskRCNN model and segmentation head. Decoders can only be shared
-        when `segmentation_backbone` is shared as well. 
+        when `segmentation_backbone` is shared as well.
       segmentation_head: segmentatation head for panoptic task.
       class_agnostic_bbox_pred: if True, perform class agnostic bounding box
         prediction. Needs to be `True` for Cascade RCNN models.
@@ -98,28 +98,28 @@ class PanopticMaskRCNNModel(maskrcnn_model.MaskRCNNModel):
       **kwargs: keyword arguments to be passed.
     """
     super(PanopticMaskRCNNModel, self).__init__(
-      backbone=backbone,
-      decoder=decoder,
-      rpn_head=rpn_head,
-      detection_head=detection_head,
-      roi_generator=roi_generator,
-      roi_sampler=roi_sampler,
-      roi_aligner=roi_aligner,
-      detection_generator=detection_generator,
-      mask_head=mask_head,
-      mask_sampler=mask_sampler,
-      mask_roi_aligner=mask_roi_aligner,
-      class_agnostic_bbox_pred=class_agnostic_bbox_pred,
-      cascade_class_ensemble=cascade_class_ensemble,
-      min_level=min_level,
-      max_level=max_level,
-      num_scales=num_scales,
-      aspect_ratios=aspect_ratios,
-      anchor_size=anchor_size,
-      **kwargs)
+        backbone=backbone,
+        decoder=decoder,
+        rpn_head=rpn_head,
+        detection_head=detection_head,
+        roi_generator=roi_generator,
+        roi_sampler=roi_sampler,
+        roi_aligner=roi_aligner,
+        detection_generator=detection_generator,
+        mask_head=mask_head,
+        mask_sampler=mask_sampler,
+        mask_roi_aligner=mask_roi_aligner,
+        class_agnostic_bbox_pred=class_agnostic_bbox_pred,
+        cascade_class_ensemble=cascade_class_ensemble,
+        min_level=min_level,
+        max_level=max_level,
+        num_scales=num_scales,
+        aspect_ratios=aspect_ratios,
+        anchor_size=anchor_size,
+        **kwargs)
 
     self._config_dict.update({
-        'segmentation_backbone':segmentation_backbone,
+        'segmentation_backbone': segmentation_backbone,
         'segmentation_decoder': segmentation_decoder,
         'segmentation_head': segmentation_head
         })
@@ -129,7 +129,8 @@ class PanopticMaskRCNNModel(maskrcnn_model.MaskRCNNModel):
           '`mask_head` needs to be provided for Panoptic Mask R-CNN.')
     if segmentation_backbone is not None and segmentation_decoder is None:
       raise ValueError(
-          '`segmentation_decoder` needs to be provided for Panoptic Mask R-CNN if `backbone` is not shared.'
+          '`segmentation_decoder` needs to be provided for Panoptic Mask R-CNN'\
+            'if `backbone` is not shared.'
       )
 
     self.segmentation_backbone = segmentation_backbone
@@ -270,18 +271,18 @@ class PanopticMaskRCNNModel(maskrcnn_model.MaskRCNNModel):
 
     if self.segmentation_backbone is not None:
       backbone_features = self.segmentation_backbone(
-        images,
-        training=training)
+          images,
+          training=training)
 
     if self.segmentation_decoder is not None:
       decoder_features = self.segmentation_decoder(
+          backbone_features,
+          training=training)
+
+    segmentation_outputs = self.segmentation_head(
         backbone_features,
+        decoder_features,
         training=training)
-    
-    segmentation_outputs = self.segmentation_head(
-      backbone_features,
-      decoder_features,
-      training=training)
 
     model_outputs.update({
         'segmentation_outputs': segmentation_outputs,

official/vision/beta/projects/panoptic_maskrcnn/modeling/panoptic_maskrcnn_model_test.py

@@ -23,7 +23,8 @@ import tensorflow as tf
 
 from tensorflow.python.distribute import combinations
 from tensorflow.python.distribute import strategy_combinations
-from official.vision.beta.projects.panoptic_maskrcnn.modeling import panoptic_maskrcnn_model
+from official.vision.beta.projects.panoptic_maskrcnn.modeling import \
+    panoptic_maskrcnn_model
 from official.vision.beta.modeling.backbones import resnet
 from official.vision.beta.modeling.decoders import fpn
 from official.vision.beta.modeling.decoders import aspp
@@ -111,14 +112,14 @@ class PanopticMaskRCNNModelTest(parameterized.TestCase, tf.test.TestCase):
     if not shared_decoder:
       level = aspp_decoder_level
       segmentation_decoder = aspp.ASPP(
-        level=level, dilation_rates=aspp_dilation_rates)
+          level=level, dilation_rates=aspp_dilation_rates)
     else:
       level = fpn_decoder_level
       segmentation_decoder = None
     segmentation_head = segmentation_heads.SegmentationHead(
-      num_classes=2,  # stuff and common class for things,
-      level=level,
-      num_convs=2)
+        num_classes=2,  # stuff and common class for things,
+        level=level,
+        num_convs=2)
 
     model = panoptic_maskrcnn_model.PanopticMaskRCNNModel(
         backbone,
@@ -316,9 +317,8 @@ class PanopticMaskRCNNModelTest(parameterized.TestCase, tf.test.TestCase):
       self.assertIn('detection_masks', results)
       self.assertIn('segmentation_outputs', results)
       self.assertAllEqual(
-          [2,
-            image_size[0] // (2**level),
-            image_size[1] // (2**level), 2],
+          [2, image_size[0] // (2**level),
+           image_size[1] // (2**level), 2],
           results['segmentation_outputs'].numpy().shape)
 
   @combinations.generate(