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#!/usr/bin/env python | |
from __future__ import annotations | |
import os | |
import gradio as gr | |
from constants import MODEL_LIBRARY_ORG_NAME, UploadTarget | |
from uploader import upload | |
from utils import find_exp_dirs | |
def load_local_model_list() -> dict: | |
choices = find_exp_dirs() | |
return gr.update(choices=choices, value=choices[0] if choices else None) | |
def create_upload_demo(disable_run_button: bool = False) -> gr.Blocks: | |
model_dirs = find_exp_dirs() | |
with gr.Blocks() as demo: | |
with gr.Box(): | |
gr.Markdown('Local Models') | |
reload_button = gr.Button('Reload Model List') | |
model_dir = gr.Dropdown( | |
label='Model names', | |
choices=model_dirs, | |
value=model_dirs[0] if model_dirs else None) | |
with gr.Box(): | |
gr.Markdown('Upload Settings') | |
with gr.Row(): | |
use_private_repo = gr.Checkbox(label='Private', value=True) | |
delete_existing_repo = gr.Checkbox( | |
label='Delete existing repo of the same name', value=False) | |
upload_to = gr.Radio(label='Upload to', | |
choices=[_.value for _ in UploadTarget], | |
value=UploadTarget.MODEL_LIBRARY.value) | |
model_name = gr.Textbox(label='Model Name') | |
hf_token = gr.Text(label='Hugging Face Write Token', | |
type='password', | |
visible=os.getenv('HF_TOKEN') is None) | |
upload_button = gr.Button('Upload', interactive=not disable_run_button) | |
gr.Markdown(f''' | |
- You can upload your trained model to your personal profile (i.e. `https://huggingface.co/{{your_username}}/{{model_name}}`) or to the public [Tune-A-Video Library](https://huggingface.co/{MODEL_LIBRARY_ORG_NAME}) (i.e. `https://huggingface.co/{MODEL_LIBRARY_ORG_NAME}/{{model_name}}`). | |
''') | |
with gr.Box(): | |
gr.Markdown('Output message') | |
output_message = gr.Markdown() | |
reload_button.click(fn=load_local_model_list, | |
inputs=None, | |
outputs=model_dir) | |
upload_button.click(fn=upload, | |
inputs=[ | |
model_dir, | |
model_name, | |
upload_to, | |
use_private_repo, | |
delete_existing_repo, | |
hf_token, | |
], | |
outputs=output_message) | |
return demo | |
if __name__ == '__main__': | |
demo = create_upload_demo() | |
demo.queue(api_open=False, max_size=1).launch() | |