add: utility to format our docs too 📜 (#7314)

* add: utility to format our docs too 📜

* debugging saga

* fix: message

* checking

* should be fixed.

* revert pipeline_fixture

* remove empty line

* make style

* fix: setup.py

* style.

src/diffusers/utils/hub_utils.py

@@ -112,7 +112,8 @@ def load_or_create_model_card(
         repo_id_or_path (`str`):
             The repo id (e.g., "runwayml/stable-diffusion-v1-5") or local path where to look for the model card.
         token (`str`, *optional*):
-            Authentication token. Will default to the stored token. See https://huggingface.co/settings/token for more details.
+            Authentication token. Will default to the stored token. See https://huggingface.co/settings/token for more
+            details.
         is_pipeline (`bool`):
             Boolean to indicate if we're adding tag to a [`DiffusionPipeline`].
         from_training: (`bool`): Boolean flag to denote if the model card is being created from a training script.

src/diffusers/utils/loading_utils.py

@@ -16,8 +16,8 @@ def load_image(
         image (`str` or `PIL.Image.Image`):
             The image to convert to the PIL Image format.
         convert_method (Callable[[PIL.Image.Image], PIL.Image.Image], optional):
-            A conversion method to apply to the image after loading it.
-            When set to `None` the image will be converted "RGB".
+            A conversion method to apply to the image after loading it. When set to `None` the image will be converted
+            "RGB".
 
     Returns:
         `PIL.Image.Image`:

src/diffusers/utils/state_dict_utils.py

@@ -253,8 +253,8 @@ def convert_unet_state_dict_to_peft(state_dict):
 
 def convert_all_state_dict_to_peft(state_dict):
     r"""
-    Attempts to first `convert_state_dict_to_peft`, and if it doesn't detect `lora_linear_layer`
-    for a valid `DIFFUSERS` LoRA for example, attempts to exclusively convert the Unet `convert_unet_state_dict_to_peft`
+    Attempts to first `convert_state_dict_to_peft`, and if it doesn't detect `lora_linear_layer` for a valid
+    `DIFFUSERS` LoRA for example, attempts to exclusively convert the Unet `convert_unet_state_dict_to_peft`
     """
     try:
         peft_dict = convert_state_dict_to_peft(state_dict)

src/diffusers/utils/testing_utils.py

@@ -156,8 +156,8 @@ def get_tests_dir(append_path=None):
 # https://github.com/huggingface/accelerate/pull/1964
 def str_to_bool(value) -> int:
     """
-    Converts a string representation of truth to `True` (1) or `False` (0).
-    True values are `y`, `yes`, `t`, `true`, `on`, and `1`; False value are `n`, `no`, `f`, `false`, `off`, and `0`;
+    Converts a string representation of truth to `True` (1) or `False` (0). True values are `y`, `yes`, `t`, `true`,
+    `on`, and `1`; False value are `n`, `no`, `f`, `false`, `off`, and `0`;
     """
     value = value.lower()
     if value in ("y", "yes", "t", "true", "on", "1"):