42 lines
1.8 KiB
Markdown
42 lines
1.8 KiB
Markdown
# Fast Video
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This is currently based on Open-Sora-1.2.0: https://github.com/PKU-YuanGroup/Open-Sora-Plan/tree/294993ca78bf65dec1c3b6fb25541432c545eda9
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## Envrironment
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Change the index-url cuda version according to your system.
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```
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conda create -n fastvideo python=3.10.12
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conda activate fastvideo
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pip3 install torch==2.5.0 torchvision --index-url https://download.pytorch.org/whl/cu121
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pip3 install -U xformers --index-url https://download.pytorch.org/whl/cu121
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cd .. && git clone https://github.com/huggingface/diffusers
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cd diffusers && git checkout mochi && pip install -e . && cd ../FastVideo
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```
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```
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pip install -e . && pip install -e ".[train]"
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apt-get update && apt install screen && pip install watch gpustat
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```
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## Prepare Data & Models
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We've prepared some debug data to facilitate development. To make sure the training pipeline is correct, train on the debug data and make sure the model overfit on it (feed it the same text prompt and see if the output video is the same as the training data)
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```
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python scripts/download_hf.py --repo_id=Stealths-Video/dummyVid --local_dir=data/dummyVid --repo_type=dataset
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python scripts/download_hf.py --repo_id=Stealths-Video/mochi --local_dir=data/mochi --repo_type=model
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python scripts/download_hf.py --repo_id=Stealths-Video/Mochi-Synthetic-Data --local_dir=data/Mochi-Synthetic-Data --repo_type=dataset
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```
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## How to overfit
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```
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bash scripts/overfit.sh
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```
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Make sure to edit data/Mochi-Synthetic-Data/videos2caption.json such that this is only one video in the dataset (you can copy multiple annotations of the same video). Also make sure to edit the prompt in scripts/overfit.shto match the prompt in the training data. I observe the overfitting after 50 steps.
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## TODO
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- [X] Delete all npu related stuff.
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- [ ] Remove inpaint.
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- [ ] Create dummy debug data.
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- [ ] Add Mochi
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- [ ] Add Mochi VAE
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