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"