udapte

Author: SunMarc

src/diffusers/pipelines/pipeline_utils.py

@@ -786,7 +786,6 @@ def from_pretrained(cls, pretrained_model_name_or_path: Optional[Union[str, os.P
         # We retrieve the information by matching whether variant model checkpoints exist in the subfolders.
         # Example: `diffusion_pytorch_model.safetensors` -> `diffusion_pytorch_model.fp16.safetensors`
         # with variant being `"fp16"`.
-        # TODO: adapt logic for DDUF files (at the moment, scans the local directory which doesn't make sense in DDUF context)
         model_variants = _identify_model_variants(folder=cached_folder, variant=variant, config=config_dict)
         if len(model_variants) == 0 and variant is not None:
             error_message = f"You are trying to load the model files of the `variant={variant}`, but no such modeling files are available."

src/diffusers/utils/dduf.py

@@ -297,13 +297,13 @@ def _get_model_file(
     pretrained_model_name_or_path = str(pretrained_model_name_or_path)
 
     if dduf_entries:
-        if os.path.join(pretrained_model_name_or_path, weights_name) in dduf_entries:
-            return os.path.join(pretrained_model_name_or_path, weights_name)
+        if "/".join([pretrained_model_name_or_path, weights_name]) in dduf_entries:
+            return "/".join([pretrained_model_name_or_path, weights_name])
         elif (
             subfolder is not None
-            and os.path.join(pretrained_model_name_or_path, subfolder, weights_name) in dduf_entries
+            and "/".join([pretrained_model_name_or_path, subfolder, weights_name]) in dduf_entries
         ):
-            return os.path.join(pretrained_model_name_or_path, weights_name)
+            return "/".join([pretrained_model_name_or_path, subfolder, weights_name])
         else:
             raise EnvironmentError(f"Error no file named {weights_name} found in archive {dduf_entries.keys()}.")
     elif os.path.isfile(pretrained_model_name_or_path):