added config for `PanopticSegmentationGenerator`

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

@@ -20,6 +20,7 @@ from typing import List, Optional
 
 from official.core import config_definitions as cfg
 from official.core import exp_factory
+from official.modeling import hyperparams
 from official.modeling import optimization
 from official.vision.beta.configs import maskrcnn
 from official.vision.beta.configs import semantic_segmentation
@@ -52,6 +53,20 @@ class DataConfig(maskrcnn.DataConfig):
   """Input config for training."""
   parser: Parser = Parser()
 
+
+# @dataclasses.dataclass
+@dataclasses.dataclass
+class PanopticSegmentationGenerator(hyperparams.Config):
+  output_size: List[int] = dataclasses.field(
+      default_factory=list)
+  stuff_classes_offset: int = 0
+  mask_binarize_threshold: float = 0.5
+  score_threshold: float = 0.05
+  things_class_label: int = 1
+  void_class_label: int = 0
+  void_instance_id: int = 0
+
+
 @dataclasses.dataclass
 class PanopticMaskRCNN(maskrcnn.MaskRCNN):
   """Panoptic Mask R-CNN model config."""
@@ -60,6 +75,8 @@ class PanopticMaskRCNN(maskrcnn.MaskRCNN):
   include_mask = True
   shared_backbone: bool = True
   shared_decoder: bool = True
+  panoptic_segmentation_generator: PanopticSegmentationGenerator = \
+      PanopticSegmentationGenerator()
 
 
 @dataclasses.dataclass
@@ -112,8 +129,11 @@ def panoptic_maskrcnn_resnetfpn_coco() -> cfg.ExperimentConfig:
           init_checkpoint_modules=['backbone'],
           model=PanopticMaskRCNN(
               num_classes=91, input_size=[1024, 1024, 3],
+              panoptic_segmentation_generator=PanopticSegmentationGenerator(
+                  output_size=[1024, 1024],
+                  stuff_classes_offset=90),
               segmentation_model=SEGMENTATION_MODEL(
-                  num_classes=91,
+                  num_classes=110,
                   head=SEGMENTATION_HEAD(level=3))),
           losses=Losses(l2_weight_decay=0.00004),
           train_data=DataConfig(