re-download DAT models if filesize < 200 bytes

probably an LFS pointer

modules/dat_model.py

@@ -51,6 +51,16 @@ def load_model(self, path):
                         model_dir=self.model_download_path,
                         hash_prefix=scaler.sha256,
                     )
+
+                    if os.path.getsize(scaler.local_data_path) < 200:
+                        # Re-download if the file is too small, probably an LFS pointer
+                        scaler.local_data_path = modelloader.load_file_from_url(
+                            scaler.data_path,
+                            model_dir=self.model_download_path,
+                            hash_prefix=scaler.sha256,
+                            re_download=True,
+                        )
+
                 if not os.path.exists(scaler.local_data_path):
                     raise FileNotFoundError(f"DAT data missing: {scaler.local_data_path}")
                 return scaler

modules/modelloader.py

@@ -24,17 +24,22 @@ def load_file_from_url(
     progress: bool = True,
     file_name: str | None = None,
     hash_prefix: str | None = None,
+    re_download: bool = False,
 ) -> str:
     """Download a file from `url` into `model_dir`, using the file present if possible.
-
     Returns the path to the downloaded file.
+
+    file_name: if specified, it will be used as the filename, otherwise the filename will be extracted from the url.
+    hash_prefix: is provided, the hash of the downloaded file will be checked against.
+    re_download: re-download the file even if it already exists.
+
     """
     os.makedirs(model_dir, exist_ok=True)
     if not file_name:
         parts = urlparse(url)
         file_name = os.path.basename(parts.path)
     cached_file = os.path.abspath(os.path.join(model_dir, file_name))
-    if not os.path.exists(cached_file):
+    if re_download or not os.path.exists(cached_file):
         print(f'Downloading: "{url}" to {cached_file}\n')
         from torch.hub import download_url_to_file
         download_url_to_file(url, cached_file, progress=progress, hash_prefix=hash_prefix)