Update
Browse files- Dockerfile +1 -1
- app.py +5 -7
- requirements.txt +6 -6
Dockerfile
CHANGED
@@ -35,7 +35,7 @@ WORKDIR ${HOME}/app
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RUN curl https://pyenv.run | bash
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ENV PATH=${HOME}/.pyenv/shims:${HOME}/.pyenv/bin:${PATH}
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-
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RUN pyenv install ${PYTHON_VERSION} && \
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pyenv global ${PYTHON_VERSION} && \
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pyenv rehash && \
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RUN curl https://pyenv.run | bash
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ENV PATH=${HOME}/.pyenv/shims:${HOME}/.pyenv/bin:${PATH}
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ARG PYTHON_VERSION=3.10.11
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RUN pyenv install ${PYTHON_VERSION} && \
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pyenv global ${PYTHON_VERSION} && \
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pyenv rehash && \
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app.py
CHANGED
@@ -14,10 +14,10 @@ from app_upload import create_upload_demo
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from inference import InferencePipeline
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from trainer import Trainer
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-
TITLE = '# [Tune-A-Video](https://tuneavideo.github.io/)
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ORIGINAL_SPACE_ID = 'Tune-A-Video-library/Tune-A-Video-Training-UI'
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SPACE_ID = os.getenv('SPACE_ID'
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GPU_DATA = getoutput('nvidia-smi')
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SHARED_UI_WARNING = f'''## Attention - Training doesn't work in this shared UI. You can duplicate and use it with a paid private T4 GPU.
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@@ -39,10 +39,8 @@ You can use "T4 small/medium" to run this demo.
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'''
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HF_TOKEN_NOT_SPECIFIED_WARNING = f'''The environment variable `HF_TOKEN` is not specified. Feel free to specify your Hugging Face token with write permission if you don't want to manually provide it for every run.
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-
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You can check and create your Hugging Face tokens <a href="https://huggingface.co/settings/tokens" target="_blank">here</a>.
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You can specify environment variables in the "Repository secrets" section of the {SETTINGS} tab.
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</center>
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'''
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HF_TOKEN = os.getenv('HF_TOKEN')
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@@ -63,7 +61,7 @@ with gr.Blocks(css='style.css') as demo:
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show_warning(SHARED_UI_WARNING)
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elif not torch.cuda.is_available():
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show_warning(CUDA_NOT_AVAILABLE_WARNING)
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-
elif
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show_warning(INVALID_GPU_WARNING)
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gr.Markdown(TITLE)
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from inference import InferencePipeline
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from trainer import Trainer
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+
TITLE = '# [Tune-A-Video](https://tuneavideo.github.io/)'
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ORIGINAL_SPACE_ID = 'Tune-A-Video-library/Tune-A-Video-Training-UI'
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SPACE_ID = os.getenv('SPACE_ID')
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GPU_DATA = getoutput('nvidia-smi')
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SHARED_UI_WARNING = f'''## Attention - Training doesn't work in this shared UI. You can duplicate and use it with a paid private T4 GPU.
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'''
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HF_TOKEN_NOT_SPECIFIED_WARNING = f'''The environment variable `HF_TOKEN` is not specified. Feel free to specify your Hugging Face token with write permission if you don't want to manually provide it for every run.
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+
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+
You can check and create your Hugging Face tokens <a href="https://huggingface.co/settings/tokens" target="_blank">here</a>. You can specify environment variables in the "Repository secrets" section of the {SETTINGS} tab.
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'''
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HF_TOKEN = os.getenv('HF_TOKEN')
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show_warning(SHARED_UI_WARNING)
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elif not torch.cuda.is_available():
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show_warning(CUDA_NOT_AVAILABLE_WARNING)
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elif 'T4' not in GPU_DATA:
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show_warning(INVALID_GPU_WARNING)
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gr.Markdown(TITLE)
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requirements.txt
CHANGED
@@ -4,16 +4,16 @@ decord==0.6.0
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diffusers[torch]==0.11.1
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einops==0.6.0
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ftfy==6.1.1
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gradio==3.
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huggingface-hub==0.
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imageio==2.
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imageio-ffmpeg==0.4.8
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omegaconf==2.3.0
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Pillow==9.
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python-slugify==
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tensorboard==2.11.2
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torch==1.13.1
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torchvision==0.14.1
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transformers==4.26.0
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triton==2.0.0
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xformers==0.0.16
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diffusers[torch]==0.11.1
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einops==0.6.0
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ftfy==6.1.1
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gradio==3.24.1
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huggingface-hub==0.13.4
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imageio==2.27.0
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imageio-ffmpeg==0.4.8
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omegaconf==2.3.0
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Pillow==9.5.0
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python-slugify==8.0.1
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tensorboard==2.11.2
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torch==1.13.1
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torchvision==0.14.1
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transformers==4.26.0
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triton==2.0.0
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xformers==0.0.16
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