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hf_model.py

@@ -23,18 +23,13 @@ from .model import create_model_from_args
 from .input_conditioner import get_default_conditioner, InputConditioner
 
 
-resource_map = {
-    'radio_v1': 'https://huggingface.co/nvidia/RADIO/raw/main/radio_v1.pth.tar'
-}
-
-
 class RADIOConfig(PretrainedConfig):
     """Pretrained Hugging Face configuration for RADIO models."""
 
     def __init__(
         self,
         args: Optional[dict] = None,
-        version: Optional[str]="v1",
+        version: Optional[str] = "v1",
         return_summary: Optional[bool] = True,
         return_spatial_features: Optional[bool] = True,
         **kwargs,
@@ -68,12 +63,12 @@ class RADIOModel(PreTrainedModel):
         if isinstance(y, (list, tuple)):
             summary, all_feat = y
         elif isinstance(self.model, VisionTransformer):
-            patch_gen = getattr(self.model, 'patch_generator', None)
+            patch_gen = getattr(self.model, "patch_generator", None)
             if patch_gen is not None:
-                summary = y[:, :patch_gen.num_cls_tokens].flatten(1)
-                all_feat = y[:, patch_gen.num_skip:]
-            elif self.model.global_pool == 'avg':
-                summary = y[:, self.model.num_prefix_tokens:].mean(dim=1)
+                summary = y[:, : patch_gen.num_cls_tokens].flatten(1)
+                all_feat = y[:, patch_gen.num_skip :]
+            elif self.model.global_pool == "avg":
+                summary = y[:, self.model.num_prefix_tokens :].mean(dim=1)
                 all_feat = y
             else:
                 summary = y[:, 0]