quality

Author: SunMarc

setup.py

@@ -101,7 +101,7 @@
     "filelock",
     "flax>=0.4.1",
     "hf-doc-builder>=0.3.0",
-    "huggingface-hub>=0.27.0",
+    "huggingface-hub>=0.26.0",
     "requests-mock==1.10.0",
     "importlib_metadata",
     "invisible-watermark>=0.2.0",

src/diffusers/configuration_utils.py

@@ -24,10 +24,10 @@
 import re
 from collections import OrderedDict
 from pathlib import Path
-from typing import Any, Dict, Tuple, Union, Optional, Dict
+from typing import Any, Dict, Optional, Tuple, Union
 
 import numpy as np
-from huggingface_hub import create_repo, hf_hub_download, DDUFEntry
+from huggingface_hub import DDUFEntry, create_repo, hf_hub_download
 from huggingface_hub.utils import (
     EntryNotFoundError,
     RepositoryNotFoundError,
@@ -560,7 +560,9 @@ def extract_init_dict(cls, config_dict, **kwargs):
         return init_dict, unused_kwargs, hidden_config_dict
 
     @classmethod
-    def _dict_from_json_file(cls, json_file: Union[str, os.PathLike], dduf_entries: Optional[Dict[str, DDUFEntry]] = None):
+    def _dict_from_json_file(
+        cls, json_file: Union[str, os.PathLike], dduf_entries: Optional[Dict[str, DDUFEntry]] = None
+    ):
         if dduf_entries:
             text = dduf_entries[json_file].read_text()
         else:

src/diffusers/dependency_versions_table.py

@@ -9,7 +9,7 @@
     "filelock": "filelock",
     "flax": "flax>=0.4.1",
     "hf-doc-builder": "hf-doc-builder>=0.3.0",
-    "huggingface-hub": "huggingface-hub>=0.27.0",
+    "huggingface-hub": "huggingface-hub>=0.26.0",
     "requests-mock": "requests-mock==1.10.0",
     "importlib_metadata": "importlib_metadata",
     "invisible-watermark": "invisible-watermark>=0.2.0",

src/diffusers/models/model_loading_utils.py

@@ -129,7 +129,11 @@ def _fetch_remapped_cls_from_config(config, old_class):
         return old_class
 
 
-def load_state_dict(checkpoint_file: Union[str, os.PathLike], variant: Optional[str] = None, dduf_entries: Optional[Dict[str, DDUFEntry]]=None):
+def load_state_dict(
+    checkpoint_file: Union[str, os.PathLike],
+    variant: Optional[str] = None,
+    dduf_entries: Optional[Dict[str, DDUFEntry]] = None,
+):
     """
     Reads a checkpoint file, returning properly formatted errors if they arise.
     """

src/diffusers/models/modeling_utils.py

@@ -27,7 +27,7 @@
 
 import safetensors
 import torch
-from huggingface_hub import create_repo, split_torch_state_dict_into_shards
+from huggingface_hub import DDUFEntry, Dict, create_repo, split_torch_state_dict_into_shards
 from huggingface_hub.utils import validate_hf_hub_args
 from torch import Tensor, nn
 

src/diffusers/pipelines/pipeline_utils.py

@@ -28,6 +28,7 @@
 import requests
 import torch
 from huggingface_hub import (
+    DDUFEntry,
     ModelCard,
     create_repo,
     hf_hub_download,
@@ -1313,8 +1314,8 @@ def download(cls, pretrained_model_name, **kwargs) -> Union[str, os.PathLike]:
             not local_files_only
             and dduf_file is not None
             and dduf_file not in (sibling.rfilename for sibling in info.siblings)
-            ):  
-                raise ValueError(f"Requested {dduf_file} file is not available in {pretrained_model_name}.")
+        ):
+            raise ValueError(f"Requested {dduf_file} file is not available in {pretrained_model_name}.")
 
         if not local_files_only and not dduf_file:
             filenames = {sibling.rfilename for sibling in info.siblings}

src/diffusers/pipelines/transformers_loading_utils.py

@@ -20,7 +20,7 @@
 from huggingface_hub import DDUFEntry
 from tqdm import tqdm
 
-from ..utils import is_safetensors_available, is_transformers_version
+from ..utils import is_safetensors_available, is_transformers_available, is_transformers_version
 
 
 if TYPE_CHECKING:
@@ -93,15 +93,16 @@ def load_transformers_model_from_dduf(
 
     with tempfile.TemporaryDirectory() as tmp_dir:
         from transformers import AutoConfig, GenerationConfig
+
         tmp_config_file = os.path.join(tmp_dir, "config.json")
         with open(tmp_config_file, "w") as f:
             f.write(config_file.read_text())
         config = AutoConfig.from_pretrained(tmp_config_file)
         if generation_config is not None:
-            tmp_generation_config_file = os.path.join(tmp_generation_config_file, "generation_config.json")
+            tmp_generation_config_file = os.path.join(tmp_dir, "generation_config.json")
             with open(tmp_generation_config_file, "w") as f:
                 f.write(generation_config.read_text())
-            generation_config = GenerationConfig.from_pretrained(tmp_config_file)
+            generation_config = GenerationConfig.from_pretrained(tmp_generation_config_file)
         state_dict = {}
         with contextlib.ExitStack() as stack:
             for entry in tqdm(weight_files, desc="Loading state_dict"):  # Loop over safetensors files
@@ -112,5 +113,9 @@ def load_transformers_model_from_dduf(
                 # Update the state dictionary with tensors
                 state_dict.update(tensors)
             return cls.from_pretrained(
-                pretrained_model_name_or_path=None, config=config, generation_config=generation_config, state_dict=state_dict, **kwargs
-                )
+                pretrained_model_name_or_path=None,
+                config=config,
+                generation_config=generation_config,
+                state_dict=state_dict,
+                **kwargs,
+            )

src/diffusers/utils/hub_utils.py

@@ -292,7 +292,7 @@ def _get_model_file(
     user_agent: Optional[Union[Dict, str]] = None,
     revision: Optional[str] = None,
     commit_hash: Optional[str] = None,
-    dduf_entries: Optional[Dict[str, DDUFEntry]]=None,
+    dduf_entries: Optional[Dict[str, DDUFEntry]] = None,
 ):
     pretrained_model_name_or_path = str(pretrained_model_name_or_path)