add Dockerfile
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FROM jupyter/base-notebook:python-3.9.13
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USER root
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# Install OS dependencies
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RUN apt-get update && apt-get install -y git-core ffmpeg espeak-ng && \
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apt-get clean && \
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rm -rf /var/lib/apt/lists/*
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# Update Conda, create the voicecraft environment, and install dependencies
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RUN conda update -y -n base -c conda-forge conda && \
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conda create -y -n voicecraft python=3.9.16 && \
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conda run -n voicecraft conda install -y -c conda-forge montreal-forced-aligner=2.2.17 openfst=1.8.2 kaldi=5.5.1068 && \
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conda run -n voicecraft pip install torch==2.0.1 && \
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tensorboard==2.16.2 && \
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phonemizer==3.2.1 && \
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torchaudio==2.0.2 && \
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datasets==2.16.0 && \
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torchmetrics==0.11.1 && \
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conda run -n voicecraft pip install -e git+https://github.com/facebookresearch/audiocraft.git@c5157b5bf14bf83449c17ea1eeb66c19fb4bc7f0#egg=audiocraft
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# Install the Jupyter kernel
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RUN conda install -n voicecraft ipykernel --update-deps --force-reinstall -y && \
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conda run -n voicecraft python -m ipykernel install --name=voicecraft
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13
README.md
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README.md
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@ -43,23 +43,26 @@ cd VoiceCraft
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# https://docs.nvidia.com/datacenter/cloud-native/container-toolkit/1.13.5/install-guide.html
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# sudo apt-get install -y nvidia-container-toolkit-base || yay -Syu nvidia-container-toolkit || echo etc...
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# 3. Try to start an existing container otherwise create a new one passing in all GPUs
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# 3. First build the docker image
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docker build --tag "voicecraft" .
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# 4. Try to start an existing container otherwise create a new one passing in all GPUs
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./start-jupyter.sh # linux
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start-jupyter.bat # windows
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# 4. now open a webpage on the host box to the URL shown at the bottom of:
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# 5. now open a webpage on the host box to the URL shown at the bottom of:
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docker logs jupyter
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# 5. optionally look inside from another terminal
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# 6. optionally look inside from another terminal
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docker exec -it jupyter /bin/bash
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export USER=(your_linux_username_used_above)
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export HOME=/home/$USER
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sudo apt-get update
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# 6. confirm video card(s) are visible inside container
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# 7. confirm video card(s) are visible inside container
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nvidia-smi
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# 7. Now in browser, open inference_tts.ipynb and work through one cell at a time
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# 8. Now in browser, open inference_tts.ipynb and work through one cell at a time
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echo GOOD LUCK
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```
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