add configuration file and automap to config.json

config.json

@@ -3,6 +3,11 @@
   "architectures": [
     "SamHQModel"
   ],
+  "auto_map": {
+    "AutoConfig": "configuration_sam_hq.SamHQConfig",
+    "AutoModel": "modeling_sam_hq.SamHQModel",
+    "AutoModelForMaskGeneration": "modeling_sam_hq.SamHQModel",
+  },
   "initializer_range": 0.02,
   "mask_decoder_config": {
     "model_type": "",

configuration_sam_hq.py

@@ -0,0 +1,4 @@
+from transformers.models.sam.configuration_sam import SamConfig
+
+class SamHQConfig(SamConfig):
+    model_type = "sam_hq"

modeling_sam_hq_vit_huge.py → modeling_sam_hq.py

@@ -34,7 +34,8 @@ from transformers.utils import (
     add_start_docstrings_to_model_forward,
     logging,
 )
-from transformers.models.sam.configuration_sam import SamConfig, SamMaskDecoderConfig, SamPromptEncoderConfig, SamVisionConfig
+from transformers.models.sam.configuration_sam import SamMaskDecoderConfig, SamPromptEncoderConfig, SamVisionConfig
+from .configuration_sam_hq import SamHQConfig
 
 
 logger = logging.get_logger(__name__)
@@ -1187,10 +1188,6 @@ class SamVisionEncoder(nn.Module):
         )
 
 
-class SamHQConfig(SamConfig):
-    model_type = "sam_hq"
-
-
 class SamHQPreTrainedModel(PreTrainedModel):
     config_class = SamHQConfig
     base_model_prefix = "sam_hq"