voice-changer/trainer/exec.sh

#!/bin/bash

# 参考:https://programwiz.org/2022/03/22/how-to-write-shell-script-for-option-parsing/

set -eu


MODE=$1
PARAMS=${@:2:($#-1)}


echo "------"
echo "$MODE"
echo "PARAMS: $PARAMS"
echo "VERBOSE: $VERBOSE"
echo "------"


# 起動
if [ "${MODE}" = "SOFT_VC" ] ; then
    cd /voice-changer-internal/voice-change-service

    cp -r /resources/* .
    if [[ -e ./setting.json ]]; then
        cp ./setting.json ../frontend/dist/assets/setting.json
    else
        cp ../frontend/dist/assets/setting_softvc.json ../frontend/dist/assets/setting.json
    fi
    if [ "${VERBOSE}" = "on" ]; then
        echo "SOFT_VCを起動します(verbose)"
        python3 SoftVcServerSIO.py $PARAMS 
    else
        echo "SOFT_VCを起動します"
        python3 SoftVcServerSIO.py $PARAMS 2>stderr.txt
    fi
elif [ "${MODE}" = "MMVC" ] ; then
    cd /voice-changer-internal/voice-change-service

    cp -r /resources/* .
    if [[ -e ./setting.json ]]; then
        cp ./setting.json ../frontend/dist/assets/setting.json
    else
        cp ../frontend/dist/assets/setting_mmvc.json ../frontend/dist/assets/setting.json
    fi

    if [ "${VERBOSE}" = "on" ]; then
        echo "MMVCを起動します(verbose)"
        python3 serverSIO.py $PARAMS
    else
        echo "MMVCを起動します"
        python3 serverSIO.py $PARAMS 2>stderr.txt
    fi
elif [ "${MODE}" = "MMVC_TRAIN" ] ; then
    python3 create_dataset_jtalk.py -f train_config -s 24000 -m dataset/multi_speaker_correspondence.txt
    # date_tag=`date +%Y%m%d%H%M%S`
    sed -ie 's/80000/8000/' train_ms.py
    sed -ie "s/\"batch_size\": 10/\"batch_size\": $batch_size/" configs/train_config.json
    sed -ie "s/torch.cuda.device_count()/1/" train_ms.py
    python3 -m tensorboard.main --logdir logs --port 6006 --host 0.0.0.0 &
    python3 train_ms.py $PARAMS
    # if ${resume_flag}; then
    #     echo "トレーニング再開。バッチサイズ: ${batch_size}。"
    #     python3 train_ms.py -c configs/train_config.json -m vc
    # else
    #     echo "トレーニング開始。バッチサイズ: ${batch_size}。"
    #     python3 train_ms.py -c configs/train_config.json -m vc -fg fine_model/G_180000.pth -fd fine_model/D_180000.pth
    # fi
fi





# usage() {
#     echo "
# usage: 
#     For training
#         $0 [-t] [-b batch_size] [-r] 
#             -t: flag for training mode
#             -b: batch_size.
#             -r: flag for resuming training.
#     For changing voice
#         $0 [-v] [-c config] [-m model]
#             -v: flag for voice change mode
#             -c: config
#             -m: model name
#     For help
#         $0 [-h]
#             -h: show this help
# " >&2
# }
# warn () {
#     echo "! ! ! $1 ! ! !"
#     exit 1
# }


# training_flag=false
# batch_size=10
# resume_flag=false

# voice_change_flag=false
# config=
# model=

# escape_flag=false

# # オプション解析
# while getopts tb:rvc:m:hx OPT; do
#     case $OPT in
#     t) 
#         training_flag=true
#         ;;
#     b) 
#         batch_size="$OPTARG"
#         ;;
#     r) 
#         resume_flag=true
#         ;;
#     v) 
#         voice_change_flag=true
#         ;;
#     c) 
#         config="$OPTARG"
#         ;;
#     m) 
#         model="$OPTARG"
#         ;;
#     h | \?) 
#         usage && exit 1
#         ;;
#     x)
#         escape_flag=true
#     esac
# done



# # ## コマンドライン引数から、オプション引数分を削除
# # # shift $((OPTIND - 1))

# # # モード解析
# # if $training_flag && $voice_change_flag; then
# #     warn "-t（トレーニングモード） と -v（ボイチェンモード）は同時に指定できません。"
# #     exit 1
# # elif $training_flag; then
# #     echo "■■■  ト レ ー ニ ン グ モ ー ド   ■■■"
# # elif $voice_change_flag; then
# #     echo "■■■  ボ イ チ ェ ン モ ー ド  ■■■"
# # elif $escape_flag; then
# #     /bin/bash
# # else
# #     warn "-t（トレーニングモード） と -v（ボイチェンモード）のいずれかを指定してください。"
# #     exit 1
# # fi



# if $training_flag; then


#     python3 create_dataset_jtalk.py -f train_config -s 24000 -m dataset/multi_speaker_correspondence.txt
#     # date_tag=`date +%Y%m%d%H%M%S`
#     sed -ie 's/80000/8000/' train_ms.py
#     sed -ie "s/\"batch_size\": 10/\"batch_size\": $batch_size/" configs/train_config.json
#     sed -ie "s/torch.cuda.device_count()/1/" train_ms.py
#     python3 -m tensorboard.main --logdir logs --port 6006 --host 0.0.0.0 &

#     if ${resume_flag}; then
#         echo "トレーニング再開。バッチサイズ: ${batch_size}。"
#         python3 train_ms.py -c configs/train_config.json -m vc
#     else
#         echo "トレーニング開始。バッチサイズ: ${batch_size}。"
#         python3 train_ms.py -c configs/train_config.json -m vc -fg fine_model/G_180000.pth -fd fine_model/D_180000.pth
#     fi
# fi

# if $voice_change_flag; then
#     if [[ -z "$config" ]]; then
#         warn "コンフィグファイル(-c)を指定してください"
#     fi
#     if [[ -z "$model" ]]; then
#         warn "モデルファイル(-m)を指定してください"
#     fi

#     cd /voice-changer-internal/voice-change-service

#     cp -r /resources/* .
#     if [[ -e ./setting.json ]]; then
#         cp ./setting.json ../frontend/dist/assets/setting.json
#     fi
#     echo "-----------!!"
#     echo $config $model
#     echo $model
#     python3 serverSIO.py -p 8080 -c $config -m $model --https True --httpsSelfSigned True
# fi