remove huggingface mixing

pvnet/models/base_model.py

@@ -141,33 +141,35 @@ def minimize_data_config(input_path, output_path, model):
         yaml.dump(config, outfile, default_flow_style=False)
 
 
-class PVNetModelHubMixin(PyTorchModelHubMixin):
+class PVNetModelHubMixin:
     """
     Implementation of [`PyTorchModelHubMixin`] to provide model Hub upload/download capabilities.
     """
 
     @classmethod
-    @_deprecate_positional_args(version="0.16")
-    def _from_pretrained(
+    def from_pretrained(
         cls,
         *,
         model_id: str,
         revision: str,
-        cache_dir: str,
-        force_download: bool,
-        proxies: Optional[Dict],
-        resume_download: bool,
-        local_files_only: bool,
-        token: Union[str, bool, None],
+        cache_dir: Optional[Union[str, Path]] = None,
+        force_download: bool = False,
+        proxies: Optional[Dict] = None,
+        resume_download: Optional[bool] = None,
+        local_files_only: bool = False,
+        token: Union[str, bool, None] = None,
         map_location: str = "cpu",
         strict: bool = False,
-        **model_kwargs,
     ):
         """Load Pytorch pretrained weights and return the loaded model."""
+
         if os.path.isdir(model_id):
             print("Loading weights from local directory")
             model_file = os.path.join(model_id, PYTORCH_WEIGHTS_NAME)
+            config_file = os.path.join(model_id, CONFIG_NAME)
         else:
+
+            # load model file
             model_file = hf_hub_download(
                 repo_id=model_id,
                 filename=PYTORCH_WEIGHTS_NAME,
@@ -180,11 +182,23 @@ def _from_pretrained(
                 local_files_only=local_files_only,
             )
 
-        if "config" in model_kwargs:
-            logger.debug("Removing config from model_kwargs to avoid conflicts with model init.")
-            model_kwargs.update(model_kwargs.pop("config"))
+            # load config file
+            config_file = hf_hub_download(
+                repo_id=model_id,
+                filename=CONFIG_NAME,
+                revision=revision,
+                cache_dir=cache_dir,
+                force_download=force_download,
+                proxies=proxies,
+                resume_download=resume_download,
+                token=token,
+                local_files_only=local_files_only,
+            )
+
+        with open(config_file, "r", encoding="utf-8") as f:
+            config = json.load(f)
 
-        model = hydra.utils.instantiate(model_kwargs)
+        model = hydra.utils.instantiate(config)
 
         state_dict = torch.load(model_file, map_location=torch.device(map_location))
         model.load_state_dict(state_dict, strict=strict)  # type: ignore

tests/models/multimodal/test_from_pretrained.py

@@ -3,9 +3,9 @@
 
 def test_from_pretrained():
     model_name = "openclimatefix/pvnet_uk_region"
-    model_version = "aa73cdafd1db8df3c8b7f5ecfdb160989e7639ac"
+    model_version = "92266cd9040c590a9e90ee33eafd0e7b92548be8"
 
     _ = BaseModel.from_pretrained(
-        model_name,
+        model_id=model_name,
         revision=model_version,
     )