renamed existing config to `panoptic_fpn_coco`

official/vision/beta/projects/panoptic_maskrcnn/configs/panoptic_maskrcnn.py

@@ -144,8 +144,8 @@ class PanopticMaskRCNNTask(maskrcnn.MaskRCNNTask):
   panoptic_quality_evaluator: PanopticQualityEvaluator = PanopticQualityEvaluator()  # pylint: disable=line-too-long
 
 
-@exp_factory.register_config_factory('panoptic_maskrcnn_resnetfpn_coco')
-def panoptic_maskrcnn_resnetfpn_coco() -> cfg.ExperimentConfig:
+@exp_factory.register_config_factory('panoptic_fpn_coco')
+def panoptic_fpn_coco() -> cfg.ExperimentConfig:
   """COCO panoptic segmentation with Panoptic Mask R-CNN."""
   train_batch_size = 64
   eval_batch_size = 8
@@ -180,7 +180,11 @@ def panoptic_maskrcnn_resnetfpn_coco() -> cfg.ExperimentConfig:
               stuff_classes_offset=90,
               segmentation_model=SEGMENTATION_MODEL(
                   num_classes=num_semantic_segmentation_classes,
-                  head=SEGMENTATION_HEAD(level=3))),
+                  head=SEGMENTATION_HEAD(
+                    level=2,
+                    decoder_min_level=2,
+                    decoder_max_level=6,
+                    feature_fusion='panoptic_fpn_fusion'))),
           losses=Losses(l2_weight_decay=0.00004),
           train_data=DataConfig(
               input_path=os.path.join(_COCO_INPUT_PATH_BASE, 'train*'),

official/vision/beta/projects/panoptic_maskrcnn/configs/panoptic_maskrcnn_test.py

@@ -25,7 +25,7 @@ from official.vision.beta.projects.panoptic_maskrcnn.configs import panoptic_mas
 class PanopticMaskRCNNConfigTest(tf.test.TestCase, parameterized.TestCase):
 
   @parameterized.parameters(
-      ('panoptic_maskrcnn_resnetfpn_coco',),
+      ('panoptic_fpn_coco',),
   )
   def test_panoptic_maskrcnn_configs(self, config_name):
     config = exp_factory.get_exp_config(config_name)

official/vision/beta/projects/panoptic_maskrcnn/serving/export_saved_model.py

@@ -47,8 +47,8 @@ from official.vision.beta.serving import export_saved_model_lib
 
 FLAGS = flags.FLAGS
 
-flags.DEFINE_string('experiment', 'panoptic_maskrcnn_resnetfpn_coco',
-                    'experiment type, e.g. panoptic_maskrcnn_resnetfpn_coco')
+flags.DEFINE_string('experiment', 'panoptic_fpn_coco',
+                    'experiment type, e.g. panoptic_fpn_coco')
 flags.DEFINE_string('export_dir', None, 'The export directory.')
 flags.DEFINE_string('checkpoint_path', None, 'Checkpoint path.')
 flags.DEFINE_multi_string(

official/vision/beta/projects/panoptic_maskrcnn/serving/panoptic_segmentation_test.py

@@ -70,9 +70,9 @@ class PanopticSegmentationExportTest(tf.test.TestCase, parameterized.TestCase):
       return [example for b in range(batch_size)]
 
   @parameterized.parameters(
-      ('image_tensor', 'panoptic_maskrcnn_resnetfpn_coco'),
-      ('image_bytes', 'panoptic_maskrcnn_resnetfpn_coco'),
-      ('tf_example', 'panoptic_maskrcnn_resnetfpn_coco'),
+      ('image_tensor', 'panoptic_fpn_coco'),
+      ('image_bytes', 'panoptic_fpn_coco'),
+      ('tf_example', 'panoptic_fpn_coco'),
   )
   def test_export(self, input_type, experiment_name):
     tmp_dir = self.get_temp_dir()
@@ -113,7 +113,7 @@ class PanopticSegmentationExportTest(tf.test.TestCase, parameterized.TestCase):
                         expected_outputs['num_detections'].numpy())
 
   def test_build_model_fail_with_none_batch_size(self):
-    params = exp_factory.get_exp_config('panoptic_maskrcnn_resnetfpn_coco')
+    params = exp_factory.get_exp_config('panoptic_fpn_coco')
     input_specs = tf.keras.layers.InputSpec(shape=[1, 128, 128, 3])
     model = factory.build_panoptic_maskrcnn(
         input_specs=input_specs, model_config=params.task.model)