Merge branch 'master' of https://github.com/tensorflow/models into RTESuperGLUE

official/vision/beta/configs/image_classification_test.py

@@ -26,9 +26,12 @@ from official.vision.beta.configs import image_classification as exp_cfg
 
 class ImageClassificationConfigTest(tf.test.TestCase, parameterized.TestCase):
 
-  @parameterized.parameters(('resnet_imagenet',),
-                            ('revnet_imagenet',),
-                            ('mobilenet_imagenet'),)
+  @parameterized.parameters(
+      ('resnet_imagenet',),
+      ('resnet_rs_imagenet',),
+      ('revnet_imagenet',),
+      ('mobilenet_imagenet'),
+  )
   def test_image_classification_configs(self, config_name):
     config = exp_factory.get_exp_config(config_name)
     self.assertIsInstance(config, cfg.ExperimentConfig)

official/vision/beta/configs/semantic_segmentation.py

@@ -90,6 +90,12 @@ class Losses(hyperparams.Config):
   top_k_percent_pixels: float = 1.0
 
 
+@dataclasses.dataclass
+class Evaluation(hyperparams.Config):
+  report_per_class_iou: bool = True
+  report_train_mean_iou: bool = True  # Turning this off can speed up training.
+
+
 @dataclasses.dataclass
 class SemanticSegmentationTask(cfg.TaskConfig):
   """The model config."""
@@ -97,6 +103,7 @@ class SemanticSegmentationTask(cfg.TaskConfig):
   train_data: DataConfig = DataConfig(is_training=True)
   validation_data: DataConfig = DataConfig(is_training=False)
   losses: Losses = Losses()
+  evaluation: Evaluation = Evaluation()
   train_input_partition_dims: List[int] = dataclasses.field(
       default_factory=list)
   eval_input_partition_dims: List[int] = dataclasses.field(

official/vision/beta/modeling/heads/segmentation_heads.py

@@ -182,6 +182,7 @@ class SegmentationHead(tf.keras.layers.Layer):
 
       x = tf.image.resize(
           x, tf.shape(y)[1:3], method=tf.image.ResizeMethod.BILINEAR)
+      x = tf.cast(x, dtype=y.dtype)
       x = tf.concat([x, y], axis=self._bn_axis)
     elif self._config_dict['feature_fusion'] == 'pyramid_fusion':
       x = nn_layers.pyramid_feature_fusion(decoder_output,