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import gradio as gr
from diffusers import DiffusionPipeline
from huggingface_hub import export_folder_as_dduf, create_repo, upload_file
import tempfile
import torch
import os
_DTYPE_MAP = {"fp32": torch.float32, "fp16": torch.float16, "bf16": torch.bfloat16}
article = """
## DDUF
* [DDUF](https://huggingface.co./docs/diffusers/main/en/using-diffusers/other-formats#dduf)
Currently, we require a `repo_id` to have all the pipeline components in the Diffusers format. Examples include:
[black-forest-labs/FLUX.1-dev](https://huggingface.co./black-forest-labs/FLUX.1-dev), [stabilityai/stable-video-diffusion-img2vid-xt](https://huggingface.co./stabilityai/stable-video-diffusion-img2vid-xt), etc.
Partial components will be supported in the future.
"""
def make_dduf(repo_id: str, destination_repo_id: str, dduf_filename: str, token: str, torch_dtype: str):
return_message = ""
if destination_repo_id == "":
destination_repo_id = repo_id
try:
destination_repo_id = create_repo(repo_id=destination_repo_id, exist_ok=True).repo_id
except Exception as e:
return_message += f"❌ Got the following error while creating the repository: \n{e}"
with tempfile.TemporaryDirectory() as tmpdir:
pipe = DiffusionPipeline.from_pretrained(repo_id, torch_dtype=_DTYPE_MAP[torch_dtype])
if dduf_filename == "":
dduf_filename = f"{pipe.__class__.__name__.lower()}"
if torch_dtype != "fp32":
dduf_filename += f"_{torch_dtype}"
dduf_filename += ".dduf"
dduf_filename = os.path.join(tmpdir, dduf_filename)
pipe.save_pretrained(tmpdir, safe_serialization=True)
try:
export_folder_as_dduf(dduf_filename, folder_path=tmpdir)
except Exception as e:
return_message += f"❌ Got the following error while exporting: \n{e}"
try:
commit_url = upload_file(
repo_id=destination_repo_id,
path_in_repo=dduf_filename.split("/")[-1],
path_or_fileobj=dduf_filename,
token=token,
).commit_url
return_message += f"Success 🔥. Find the DDUF in [this commit]({commit_url})."
except Exception as e:
return_message += f"❌ Got the following error while pushing: \n{e}"
return str(return_message)
demo = gr.Interface(
title="DDUF my repo 🤗",
article=article,
fn=make_dduf,
inputs=[
gr.components.Textbox(lines=1, placeholder="Repo ID which should be DDUF'd."),
gr.components.Textbox(
lines=2,
value=None,
placeholder="Destination Repo ID that should be used to store the resultant DDUF. Leave it if you want to use the `repo_id` here.",
),
gr.components.Textbox(
lines=1,
value=None,
placeholder="Name of the DDUF file. If it's not provided we will infer it based on the pipeline class.",
),
gr.components.Textbox(lines=1, placeholder="HF token. You can obtain it from hf.co/settings/tokens."),
gr.Dropdown(
list(_DTYPE_MAP.keys()),
value="fp32",
multiselect=False,
label="dtype",
info="dtype to load the pipeline in.",
),
],
outputs="markdown",
examples=[
["stabilityai/stable-video-diffusion-img2vid-xt", "sayakpaul/svd-dduf", "svd.dduf", "hf_XXX", "fp32"],
],
allow_flagging="never",
)
if __name__ == "__main__":
demo.launch(debug=True, show_error=True)
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