Update about paperspace
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97
Dockerfile
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97
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# ==================================================================
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# Initial setup
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# ------------------------------------------------------------------
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# Ubuntu 22.04 as base image
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FROM ubuntu:22.04
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# RUN yes| unminimize
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# Set ENV variables
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ENV LANG C.UTF-8
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ENV SHELL=/bin/bash
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ENV DEBIAN_FRONTEND=noninteractive
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ENV APT_INSTALL="apt-get install -y --no-install-recommends"
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ENV PIP_INSTALL="python3 -m pip --no-cache-dir install --upgrade"
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ENV GIT_CLONE="git clone --depth 10"
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# ==================================================================
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# Tools
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# ------------------------------------------------------------------
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RUN apt-get update && \
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$APT_INSTALL \
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sudo \
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build-essential \
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ca-certificates \
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wget \
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curl \
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git \
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zip \
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unzip \
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nano \
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ffmpeg \
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software-properties-common \
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gnupg \
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python3 \
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python3-pip \
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python3-dev
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# ==================================================================
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# Git-lfs
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# ------------------------------------------------------------------
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RUN curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | sudo bash && \
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$APT_INSTALL git-lfs
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# Add symlink so python and python3 commands use same python3.9 executable
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RUN ln -s /usr/bin/python3 /usr/local/bin/python
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# ==================================================================
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# Installing CUDA packages (CUDA Toolkit 12.0 and CUDNN 8.9.7)
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# ------------------------------------------------------------------
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RUN wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-ubuntu2204.pin && \
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mv cuda-ubuntu2204.pin /etc/apt/preferences.d/cuda-repository-pin-600 && \
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wget https://developer.download.nvidia.com/compute/cuda/12.0.0/local_installers/cuda-repo-ubuntu2204-12-0-local_12.0.0-525.60.13-1_amd64.deb && \
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dpkg -i cuda-repo-ubuntu2204-12-0-local_12.0.0-525.60.13-1_amd64.deb && \
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cp /var/cuda-repo-ubuntu2204-12-0-local/cuda-*-keyring.gpg /usr/share/keyrings/ && \
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apt-get update && \
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$APT_INSTALL cuda && \
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rm cuda-repo-ubuntu2204-12-0-local_12.0.0-525.60.13-1_amd64.deb
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# Installing CUDNN
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RUN apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/3bf863cc.pub && \
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add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/ /" && \
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apt-get update && \
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$APT_INSTALL libcudnn8=8.9.7.29-1+cuda12.2 \
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libcudnn8-dev=8.9.7.29-1+cuda12.2
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ENV PATH=$PATH:/usr/local/cuda/bin
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ENV LD_LIBRARY_PATH=/usr/local/cuda/lib64:$LD_LIBRARY_PATH
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# ==================================================================
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# PyTorch
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# ------------------------------------------------------------------
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# Based on https://pytorch.org/get-started/locally/
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RUN $PIP_INSTALL torch==2.1.2 torchvision==0.16.2 torchaudio==2.1.2 --index-url https://download.pytorch.org/whl/cu118
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RUN $PIP_INSTALL jupyterlab
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# Install requirements.txt from the project
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COPY requirements.txt /tmp/requirements.txt
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RUN $PIP_INSTALL -r /tmp/requirements.txt
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RUN rm /tmp/requirements.txt
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# ==================================================================
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# Startup
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# ------------------------------------------------------------------
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EXPOSE 8888 6006
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CMD jupyter lab --allow-root --ip=0.0.0.0 --no-browser --ServerApp.trust_xheaders=True --ServerApp.disable_check_xsrf=False --ServerApp.allow_remote_access=True --ServerApp.allow_origin='*' --ServerApp.allow_credentials=True
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@@ -87,8 +87,9 @@ python train_ms.py [--repo_id <username>/<repo_name>]
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If using JP-Extra model:
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```bash
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python train_ms_jp_extra.py [--repo_id <username>/<repo_name>]
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python train_ms_jp_extra.py [--repo_id <username>/<repo_name>] [--skip_default_style]
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```
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Optional:
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- `--repo_id`: Hugging Face repository ID to upload the trained model to. You should have logged in using `huggingface-cli login` before running this command.
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- `--skip_default_style`: Skip making the default style vector. Use this if you want to resume training (since the default style vector is already made).
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@@ -25,8 +25,8 @@ git clone https://github.com/litagin02/Style-Bert-VITS2.git
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```
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環境構築(デフォルトはPyTorch 1.x系、Python 3.9の模様)
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```bash
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pip install torch==2.1.2 torchvision==0.16.2 torchaudio==2.1.2 --index-url https://download.pytorch.org/whl/cu118
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pip install -r requirements.txt
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cd /storage/sbv2/Style-Bert-VITS2
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pip install torch==2.1.2 torchvision==0.16.2 torchaudio==2.1.2 --index-url https://download.pytorch.org/whl/cu118 && pip install -r requirements.txt
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```
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事前学習済みモデル等のダウンロード、またパスを`/notebooks/`以下のものに設定
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```bash
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@@ -70,3 +70,15 @@ Hugging faceの`username/sbv2-private`というモデルリポジトリに学習
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python train_ms_jp_extra.py --repo_id username/sbv2-private
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```
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(JP-Extraでない場合は`train_ms.py`を使う)
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### 4. 学習再開
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Notebooksの時間制限が切れてから別Notebooksで同じモデルを学習を再開する場合(環境構築は必要)。
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```bash
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huggingface-cli login
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cd /notebooks
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huggingface-cli download username/sbv2-private --include "Data/Foo/*" --local-dir .
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cd /storage/sbv2/Style-Bert-VITS2
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python train_ms_jp_extra.py --repo_id username/sbv2-private --skip_default_style
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```
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前回の設定が残っているので特に前処理等は不要。
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