Upload utils.py

utils.py

@@ -8,11 +8,35 @@ Date: Feb 26, 2025
 import torch
 import gc
 import os
+import sys
 from PIL import Image, ImageDraw, ImageFont
 
 # Disable HF transfer to avoid download issues
 os.environ["HF_HUB_ENABLE_HF_TRANSFER"] = "0"
 
+# Create a monkey patch for the cached_download function
+# This is needed because newer versions of huggingface_hub 
+# removed cached_download but diffusers still tries to import it
+def apply_huggingface_patch():
+    import importlib
+    import huggingface_hub
+    
+    # Check if cached_download is already available
+    if hasattr(huggingface_hub, 'cached_download'):
+        return  # No need to patch
+    
+    # Create a wrapper around hf_hub_download to mimic the old cached_download
+    def cached_download(*args, **kwargs):
+        # Forward to the new function with appropriate args
+        return huggingface_hub.hf_hub_download(*args, **kwargs)
+    
+    # Add the function to the huggingface_hub module
+    setattr(huggingface_hub, 'cached_download', cached_download)
+    
+    # Make sure diffusers.utils.dynamic_modules_utils sees the patched module
+    if 'diffusers.utils.dynamic_modules_utils' in sys.modules:
+        del sys.modules['diffusers.utils.dynamic_modules_utils']
+
 
 def load_models(device="cuda"):
     """
@@ -20,7 +44,10 @@ def load_models(device="cuda"):
     :param device: (str) Device to load models on ('cuda', 'mps', or 'cpu')
     :return: (tuple) (vae, tokenizer, text_encoder, unet, scheduler, pipe)
     """
-    # Import here to avoid the cached_download issue
+    # Apply the patch before importing diffusers
+    apply_huggingface_patch()
+    
+    # Now we can safely import from diffusers
     from diffusers import AutoencoderKL, LMSDiscreteScheduler, UNet2DConditionModel, StableDiffusionPipeline
     from transformers import CLIPTokenizer, CLIPTextModel