WIP: v1.5support 1

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wataru 2023-01-31 17:16:45 +09:00
parent 21e7c9389f
commit 2f79283e28
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FROM nvidia/cuda:11.8.0-cudnn8-runtime-ubuntu22.04 as base
ARG DEBIAN_FRONTEND=noninteractive
RUN apt-get -y update && apt-get install -y emacs git curl python3-pip libsndfile1-dev ffmpeg
RUN git clone --depth 1 -b v1.5.0.0_SiFiGAN https://github.com/isletennos/MMVC_Trainer.git
ADD /model/D_v15_best.pth /MMVC_Trainer/fine_model/
ADD /model/G_v15_best.pth /MMVC_Trainer/fine_model/
RUN pip install pydub==0.25.1
RUN pip install tqdm==4.64.1
RUN pip install librosa==0.9.2
RUN pip install torch==1.13.1
RUN pip install torchaudio==0.13.1
RUN pip install psutil==5.9.4
RUN pip install tensorboard==2.11.2
RUN pip install pytz==2022.7.1
RUN pip install pyworld==0.3.2
RUN pip install retry==0.9.2
RUN pip install h5py==3.8.0
RUN pip install matplotlib==3.6.3
ADD /warmup.py /
RUN python3 warmup.py
WORKDIR /MMVC_Trainer/
# python3 normalize.py True
# python3 create_dataset.py -f train_config -s 24000 -m dataset/multi_speaker_correspondence.txt
# tensorboard --logdir logs --port 5000
# python3 train_ms.py -c configs/train_config.json -m 20220306_24000 -fg fine_model/G_v15_best.pth -fd fine_model/D_v15_best.pth
#$ docker run --gpus all --rm -ti -v `pwd`/trainer/dataset:/MMVC_Trainer/dataset -v `pwd`/trainer/configs:/MMVC_Trainer/configs -v `pwd`/trainer/F0:/MMVC_Trainer/F0 -v `pwd`/trainer/cF0:/MMVC_Trainer/cF0 -v `pwd`/trainer/units:/MMVC_Trainer/units -v `pwd`/trainer/logs:/MMVC_Trainer/logs -v `pwd`/trainer/filelists:/MMVC_Trainer/filelists -p 5000:5000 trainer /bin/bash

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MMVC Server
----
# 起動方法
(1) Datasetを`trainer/dataset`におく
```sh
trainer/dataset/
├── 00_myvoice
│   ├── text
│   │   ├── emotion001.txt
│   │   ├── emotion002.txt
...
│   │   └── emotion100.txt
│   └── wav
│   ├── emotion001.wav
│   ├── emotion002.wav
...
│   └── emotion100.wav
├── 1205_zundamon
│   ├── text
│   │   ├── emoNormal_001.txt
│   │   ├── emoNormal_002.txt
...
│   │   └── emoNormal_100.txt
│   └── wav
│   ├── emoNormal_001.wav
│   ├── emoNormal_002.wav
...
│   └── emoNormal_100.wav
├── 344_tsumugi
│   ├── text
│   │   ├── VOICEACTRESS100_001.txt
│   │   ├── VOICEACTRESS100_002.txt
...
│   │   └── emoNormal_100.txt
│   └── wav
│   ├── VOICEACTRESS100_001.wav
│   ├── VOICEACTRESS100_002.wav
...
│   └── emoNormal_100.wav
└── multi_speaker_correspondence.txt
```
(2) start.shをrootにコピー
(3) `bash start.sh`を実行
(4) Docker内で次のコマンドを実行
batch sizeは適宜調整
```sh
$ python3 normalize.py True
$ python3 create_dataset.py -f train_config -s 24000 -m dataset/multi_speaker_correspondence.txt
$ tensorboard --logdir logs --port 5000
$ python3 train_ms.py -c configs/train_config.json -m 20220306_24000 -fg fine_model/G_v15_best.pth -fd fine_model/D_v15_best.pth
```

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docker run --gpus all --rm -ti \
-v `pwd`/trainer/dataset:/MMVC_Trainer/dataset \
-v `pwd`/trainer/configs:/MMVC_Trainer/configs \
-v `pwd`/trainer/F0:/MMVC_Trainer/F0 \
-v `pwd`/trainer/cF0:/MMVC_Trainer/cF0 \
-v `pwd`/trainer/units:/MMVC_Trainer/units \
-v `pwd`/trainer/logs:/MMVC_Trainer/logs \
-v `pwd`/trainer/filelists:/MMVC_Trainer/filelists \
-p 5000:5000 \
trainer /bin/bash

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import torch
hubert = torch.hub.load("bshall/hubert:main", "hubert_soft")

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"scripts": {
"build:docker": "date +%Y%m%d%H%M%S > docker/dummy && DOCKER_BUILDKIT=1 docker build -f docker/Dockerfile docker/ -t voice-changer",
"build:docker:onnx": "DOCKER_BUILDKIT=1 docker build -f docker_onnx/Dockerfile docker/ -t onnx-converter",
"build:docker:trainer": "DOCKER_BUILDKIT=1 docker build -f docker_trainer/Dockerfile docker_trainer/ -t trainer",
"copy:frontend": "docker run -v `pwd`/frontend/dist:/frontend/dist --entrypoint /bin/bash -ti voice-changer -c \"cp -r /voice-changer-internal/frontend/dist/* /frontend/dist\"",
"copy:backend": "docker run -v `pwd`/demo:/demo --entrypoint /bin/bash -ti voice-changer -c \"cp -r /voice-changer-internal/voice-change-service/* /demo/ && rm -rf /demo/MMVC_Trainer/.git && rm -rf /demo/MMVC_Trainer/.gitignore \"",
"create:demo": "run-p copy:frontend copy:backend",

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