[Docs Update] AutoPipelineForInpainting.from_pretrained fails to load runwayml/stable-diffusion-inpainting without variant="fp16"

[Player256]

Describe the bug

I was following this part of the docs, the code above configure pipeline parameters. I found a little mistake which lead to the following error log. Adding variant="fp16" resolves the issue.

Reproduction

import PIL
import numpy as np
import torch

from diffusers import AutoPipelineForInpainting
from diffusers.utils import load_image, make_image_grid

device = "cuda"
pipeline = AutoPipelineForInpainting.from_pretrained(
    "runwayml/stable-diffusion-inpainting",
    torch_dtype=torch.float16,
)
pipeline = pipeline.to(device)

img_url = "https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png"
mask_url = "https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo_mask.png"

init_image = load_image(img_url).resize((512, 512))
mask_image = load_image(mask_url).resize((512, 512))

prompt = "Face of a yellow cat, high resolution, sitting on a park bench"
repainted_image = pipeline(prompt=prompt, image=init_image, mask_image=mask_image).images[0]
repainted_image.save("repainted_image.png")

unmasked_unchanged_image = pipeline.image_processor.apply_overlay(mask_image, init_image, repainted_image)
unmasked_unchanged_image.save("force_unmasked_unchanged.png")
make_image_grid([init_image, mask_image, repainted_image, unmasked_unchanged_image], rows=2, cols=2)

Logs

---------------------------------------------------------------------------
OSError                                   Traceback (most recent call last)
Cell In[8], line 9
      6 from diffusers.utils import load_image, make_image_grid
      8 device = "cuda"
----> 9 pipeline = AutoPipelineForInpainting.from_pretrained(
     10     "runwayml/stable-diffusion-inpainting",
     11     torch_dtype=torch.float16,
     12 )
     13 pipeline = pipeline.to(device)
     15 img_url = "https://raw.githubusercontent.com/CompVis/latent-diffusion/main/data/inpainting_examples/overture-creations-5sI6fQgYIuo.png"

File /opt/conda/envs/idm/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py:114, in validate_hf_hub_args.<locals>._inner_fn(*args, **kwargs)
    111 if check_use_auth_token:
    112     kwargs = smoothly_deprecate_use_auth_token(fn_name=fn.__name__, has_token=has_token, kwargs=kwargs)
--> 114 return fn(*args, **kwargs)

File /opt/conda/envs/idm/lib/python3.10/site-packages/diffusers/pipelines/auto_pipeline.py:1058, in AutoPipelineForInpainting.from_pretrained(cls, pretrained_model_or_path, **kwargs)
   1055 inpainting_cls = _get_task_class(AUTO_INPAINT_PIPELINES_MAPPING, orig_class_name)
   1057 kwargs = {**load_config_kwargs, **kwargs}
-> 1058 return inpainting_cls.from_pretrained(pretrained_model_or_path, **kwargs)

File /opt/conda/envs/idm/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py:114, in validate_hf_hub_args.<locals>._inner_fn(*args, **kwargs)
    111 if check_use_auth_token:
    112     kwargs = smoothly_deprecate_use_auth_token(fn_name=fn.__name__, has_token=has_token, kwargs=kwargs)
--> 114 return fn(*args, **kwargs)

File /opt/conda/envs/idm/lib/python3.10/site-packages/diffusers/pipelines/pipeline_utils.py:981, in DiffusionPipeline.from_pretrained(cls, pretrained_model_name_or_path, **kwargs)
    974 else:
    975     # load sub model
    976     sub_model_dtype = (
    977         torch_dtype.get(name, torch_dtype.get("default", torch.float32))
    978         if isinstance(torch_dtype, dict)
    979         else torch_dtype
    980     )
--> 981     loaded_sub_model = load_sub_model(
    982         library_name=library_name,
    983         class_name=class_name,
    984         importable_classes=importable_classes,
    985         pipelines=pipelines,
    986         is_pipeline_module=is_pipeline_module,
    987         pipeline_class=pipeline_class,
    988         torch_dtype=sub_model_dtype,
    989         provider=provider,
    990         sess_options=sess_options,
    991         device_map=current_device_map,
    992         max_memory=max_memory,
    993         offload_folder=offload_folder,
    994         offload_state_dict=offload_state_dict,
    995         model_variants=model_variants,
    996         name=name,
    997         from_flax=from_flax,
    998         variant=variant,
    999         low_cpu_mem_usage=low_cpu_mem_usage,
   1000         cached_folder=cached_folder,
   1001         use_safetensors=use_safetensors,
   1002         dduf_entries=dduf_entries,
   1003         provider_options=provider_options,
   1004     )
   1005     logger.info(
   1006         f"Loaded {name} as {class_name} from `{name}` subfolder of {pretrained_model_name_or_path}."
   1007     )
   1009 init_kwargs[name] = loaded_sub_model  # UNet(...), # DiffusionSchedule(...)

File /opt/conda/envs/idm/lib/python3.10/site-packages/diffusers/pipelines/pipeline_loading_utils.py:777, in load_sub_model(library_name, class_name, importable_classes, pipelines, is_pipeline_module, pipeline_class, torch_dtype, provider, sess_options, device_map, max_memory, offload_folder, offload_state_dict, model_variants, name, from_flax, variant, low_cpu_mem_usage, cached_folder, use_safetensors, dduf_entries, provider_options)
    775     loaded_sub_model = load_method(name, **loading_kwargs)
    776 elif os.path.isdir(os.path.join(cached_folder, name)):
--> 777     loaded_sub_model = load_method(os.path.join(cached_folder, name), **loading_kwargs)
    778 else:
    779     # else load from the root directory
    780     loaded_sub_model = load_method(cached_folder, **loading_kwargs)

File /opt/conda/envs/idm/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py:114, in validate_hf_hub_args.<locals>._inner_fn(*args, **kwargs)
    111 if check_use_auth_token:
    112     kwargs = smoothly_deprecate_use_auth_token(fn_name=fn.__name__, has_token=has_token, kwargs=kwargs)
--> 114 return fn(*args, **kwargs)

File /opt/conda/envs/idm/lib/python3.10/site-packages/diffusers/models/modeling_utils.py:1147, in ModelMixin.from_pretrained(cls, pretrained_model_name_or_path, **kwargs)
   1142             logger.warning(
   1143                 "Defaulting to unsafe serialization. Pass `allow_pickle=False` to raise an error instead."
   1144             )
   1146     if resolved_model_file is None and not is_sharded:
-> 1147         resolved_model_file = _get_model_file(
   1148             pretrained_model_name_or_path,
   1149             weights_name=_add_variant(WEIGHTS_NAME, variant),
   1150             cache_dir=cache_dir,
   1151             force_download=force_download,
   1152             proxies=proxies,
   1153             local_files_only=local_files_only,
   1154             token=token,
   1155             revision=revision,
   1156             subfolder=subfolder,
   1157             user_agent=user_agent,
   1158             commit_hash=commit_hash,
   1159             dduf_entries=dduf_entries,
   1160         )
   1162 if not isinstance(resolved_model_file, list):
   1163     resolved_model_file = [resolved_model_file]

File /opt/conda/envs/idm/lib/python3.10/site-packages/huggingface_hub/utils/_validators.py:114, in validate_hf_hub_args.<locals>._inner_fn(*args, **kwargs)
    111 if check_use_auth_token:
    112     kwargs = smoothly_deprecate_use_auth_token(fn_name=fn.__name__, has_token=has_token, kwargs=kwargs)
--> 114 return fn(*args, **kwargs)

File /opt/conda/envs/idm/lib/python3.10/site-packages/diffusers/utils/hub_utils.py:254, in _get_model_file(pretrained_model_name_or_path, weights_name, subfolder, cache_dir, force_download, proxies, local_files_only, token, user_agent, revision, commit_hash, dduf_entries)
    252         return model_file
    253     else:
--> 254         raise EnvironmentError(
    255             f"Error no file named {weights_name} found in directory {pretrained_model_name_or_path}."
    256         )
    257 else:
    258     # 1. First check if deprecated way of loading from branches is used
    259     if (
    260         revision in DEPRECATED_REVISION_ARGS
    261         and (weights_name == WEIGHTS_NAME or weights_name == SAFETENSORS_WEIGHTS_NAME)
    262         and version.parse(version.parse(__version__).base_version) >= version.parse("0.22.0")
    263     ):

OSError: Error no file named diffusion_pytorch_model.bin found in directory /home/ubuntu/.cache/huggingface/hub/models--runwayml--stable-diffusion-inpainting/snapshots/8a4288a76071f7280aedbdb3253bdb9e9d5d84bb/unet.

System Info

diffusers==0.34.0.dev0

Who can help?

No response