Cool_Tools/Retrieval-based-Voice-Conversion-WebUI
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feat: ipynb for v2 (#332)
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{
👷 Use `black[jupyter]` (#847) * 👷 Use black[jupyter] * 👷 Add missing matrix
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"cells": [
update colab notebooks (#1023)
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{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"# [Retrieval-based-Voice-Conversion-WebUI](https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI) Training notebook"
]
},
👷 Use `black[jupyter]` (#847) * 👷 Use black[jupyter] * 👷 Add missing matrix
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{
"attachments": {},
"cell_type": "markdown",
"metadata": {
"id": "ZFFCx5J80SGa"
},
"source": [
"[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/RVC-Project/Retrieval-based-Voice-Conversion-WebUI/blob/main/Retrieval_based_Voice_Conversion_WebUI_v2.ipynb)"
]
feat: ipynb for v2 (#332)
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},
👷 Use `black[jupyter]` (#847) * 👷 Use black[jupyter] * 👷 Add missing matrix
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{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "GmFP6bN9dvOq"
},
"outputs": [],
"source": [
update colab notebooks (#1023)
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"# @title #查看显卡\n",
👷 Use `black[jupyter]` (#847) * 👷 Use black[jupyter] * 👷 Add missing matrix
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"!nvidia-smi"
]
},
update colab notebooks (#1023)
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{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "jwu07JgqoFON"
},
"outputs": [],
"source": [
"# @title 挂载谷歌云盘\n",
"\n",
"from google.colab import drive\n",
"\n",
"drive.mount(\"/content/drive\")"
]
},
👷 Use `black[jupyter]` (#847) * 👷 Use black[jupyter] * 👷 Add missing matrix
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{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "wjddIFr1oS3W"
},
"outputs": [],
"source": [
update colab notebooks (#1023)
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"# @title #安装依赖\n",
👷 Use `black[jupyter]` (#847) * 👷 Use black[jupyter] * 👷 Add missing matrix
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"!apt-get -y install build-essential python3-dev ffmpeg\n",
"!pip3 install --upgrade setuptools wheel\n",
"!pip3 install --upgrade pip\n",
"!pip3 install faiss-cpu==1.7.2 fairseq gradio==3.14.0 ffmpeg ffmpeg-python praat-parselmouth pyworld numpy==1.23.5 numba==0.56.4 librosa==0.9.2"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "ge_97mfpgqTm"
},
"outputs": [],
"source": [
update colab notebooks (#1023)
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"# @title #克隆仓库\n",
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"\n",
"!mkdir Retrieval-based-Voice-Conversion-WebUI\n",
"%cd /content/Retrieval-based-Voice-Conversion-WebUI\n",
"!git init\n",
"!git remote add origin https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI.git\n",
"!git fetch origin cfd984812804ddc9247d65b14c82cd32e56c1133 --depth=1\n",
"!git reset --hard FETCH_HEAD"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "BLDEZADkvlw1"
},
"outputs": [],
"source": [
update colab notebooks (#1023)
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"# @title #更新仓库（一般无需执行）\n",
👷 Use `black[jupyter]` (#847) * 👷 Use black[jupyter] * 👷 Add missing matrix
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"!git pull"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "pqE0PrnuRqI2"
},
"outputs": [],
"source": [
update colab notebooks (#1023)
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"# @title #安装aria2\n",
👷 Use `black[jupyter]` (#847) * 👷 Use black[jupyter] * 👷 Add missing matrix
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"!apt -y install -qq aria2"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "UG3XpUwEomUz"
},
"outputs": [],
"source": [
"# @title 下载底模\n",
"\n",
"# v1\n",
"!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/D32k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o D32k.pth\n",
"!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/D40k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o D40k.pth\n",
"!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/D48k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o D48k.pth\n",
"!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/G32k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o G32k.pth\n",
"!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/G40k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o G40k.pth\n",
"!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/G48k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o G48k.pth\n",
"!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0D32k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o f0D32k.pth\n",
"!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0D40k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o f0D40k.pth\n",
"!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0D48k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o f0D48k.pth\n",
"!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0G32k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o f0G32k.pth\n",
"!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0G40k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o f0G40k.pth\n",
"!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained/f0G48k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained -o f0G48k.pth\n",
"\n",
"# v2\n",
"# !aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/D32k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained_v2 -o D32k.pth\n",
"!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/D40k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained_v2 -o D40k.pth\n",
"# !aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/D48k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained_v2 -o D48k.pth\n",
"# !aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/G32k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained_v2 -o G32k.pth\n",
"!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/G40k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained_v2 -o G40k.pth\n",
"# !aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/G48k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained_v2 -o G48k.pth\n",
"# !aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/f0D32k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained_v2 -o f0D32k.pth\n",
"!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/f0D40k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained_v2 -o f0D40k.pth\n",
"# !aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/f0D48k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained_v2 -o f0D48k.pth\n",
"# !aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/f0G32k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained_v2 -o f0G32k.pth\n",
"!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/f0G40k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained_v2 -o f0G40k.pth\n",
"# !aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/pretrained_v2/f0G48k.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/pretrained_v2 -o f0G48k.pth"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "HugjmZqZRuiF"
},
"outputs": [],
"source": [
update colab notebooks (#1023)
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"# @title #下载人声分离模型\n",
👷 Use `black[jupyter]` (#847) * 👷 Use black[jupyter] * 👷 Add missing matrix
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"!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/HP2-人声vocals+非人声instrumentals.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/uvr5_weights -o HP2-人声vocals+非人声instrumentals.pth\n",
"!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/uvr5_weights/HP5-主旋律人声vocals+其他instrumentals.pth -d /content/Retrieval-based-Voice-Conversion-WebUI/uvr5_weights -o HP5-主旋律人声vocals+其他instrumentals.pth"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "2RCaT9FTR0ej"
},
"outputs": [],
"source": [
update colab notebooks (#1023)
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"# @title #下载hubert_base\n",
👷 Use `black[jupyter]` (#847) * 👷 Use black[jupyter] * 👷 Add missing matrix
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"!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/hubert_base.pt -d /content/Retrieval-based-Voice-Conversion-WebUI -o hubert_base.pt"
]
},
{
"cell_type": "code",
"execution_count": null,
update colab notebooks (#1023)
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"metadata": {},
👷 Use `black[jupyter]` (#847) * 👷 Use black[jupyter] * 👷 Add missing matrix
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"outputs": [],
"source": [
update colab notebooks (#1023)
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"# @title #下载rmvpe模型\n",
"!aria2c --console-log-level=error -c -x 16 -s 16 -k 1M https://huggingface.co/lj1995/VoiceConversionWebUI/resolve/main/rmvpe.pt -d /content/Retrieval-based-Voice-Conversion-WebUI -o rmvpe.pt"
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]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "Mwk7Q0Loqzjx"
},
"outputs": [],
"source": [
update colab notebooks (#1023)
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"# @title #从谷歌云盘加载打包好的数据集到/content/dataset\n",
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"\n",
"# @markdown 数据集位置\n",
"DATASET = (\n",
" \"/content/drive/MyDrive/dataset/lulu20230327_32k.zip\" # @param {type:\"string\"}\n",
")\n",
"\n",
"!mkdir -p /content/dataset\n",
"!unzip -d /content/dataset -B {DATASET}"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "PDlFxWHWEynD"
},
"outputs": [],
"source": [
update colab notebooks (#1023)
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"# @title #重命名数据集中的重名文件\n",
👷 Use `black[jupyter]` (#847) * 👷 Use black[jupyter] * 👷 Add missing matrix
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"!ls -a /content/dataset/\n",
"!rename 's/(\\w+)\\.(\\w+)~(\\d*)/$1_$3.$2/' /content/dataset/*.*~*"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "7vh6vphDwO0b"
},
"outputs": [],
"source": [
update colab notebooks (#1023)
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"# @title #启动webui\n",
👷 Use `black[jupyter]` (#847) * 👷 Use black[jupyter] * 👷 Add missing matrix
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"%cd /content/Retrieval-based-Voice-Conversion-WebUI\n",
"# %load_ext tensorboard\n",
"# %tensorboard --logdir /content/Retrieval-based-Voice-Conversion-WebUI/logs\n",
"!python3 infer-web.py --colab --pycmd python3"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "FgJuNeAwx5Y_"
},
"outputs": [],
"source": [
update colab notebooks (#1023)
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"# @title #手动将训练后的模型文件备份到谷歌云盘\n",
"# @markdown #需要自己查看logs文件夹下模型的文件名，手动修改下方命令末尾的文件名\n",
👷 Use `black[jupyter]` (#847) * 👷 Use black[jupyter] * 👷 Add missing matrix
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"\n",
update colab notebooks (#1023)
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"# @markdown #模型名\n",
👷 Use `black[jupyter]` (#847) * 👷 Use black[jupyter] * 👷 Add missing matrix
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"MODELNAME = \"lulu\" # @param {type:\"string\"}\n",
update colab notebooks (#1023)
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"# @markdown #模型epoch\n",
👷 Use `black[jupyter]` (#847) * 👷 Use black[jupyter] * 👷 Add missing matrix
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"MODELEPOCH = 9600 # @param {type:\"integer\"}\n",
"\n",
"!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth /content/drive/MyDrive/{MODELNAME}_D_{MODELEPOCH}.pth\n",
"!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/D_{MODELEPOCH}.pth /content/drive/MyDrive/{MODELNAME}_G_{MODELEPOCH}.pth\n",
"!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/added_*.index /content/drive/MyDrive/\n",
"!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/total_*.npy /content/drive/MyDrive/\n",
"\n",
"!cp /content/Retrieval-based-Voice-Conversion-WebUI/weights/{MODELNAME}.pth /content/drive/MyDrive/{MODELNAME}{MODELEPOCH}.pth"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "OVQoLQJXS7WX"
},
"outputs": [],
"source": [
"# @title 从谷歌云盘恢复pth\n",
"# @markdown 需要自己查看logs文件夹下模型的文件名，手动修改下方命令末尾的文件名\n",
"\n",
"# @markdown 模型名\n",
"MODELNAME = \"lulu\" # @param {type:\"string\"}\n",
"# @markdown 模型epoch\n",
"MODELEPOCH = 7500 # @param {type:\"integer\"}\n",
"\n",
"!mkdir -p /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}\n",
"\n",
"!cp /content/drive/MyDrive/{MODELNAME}_D_{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth\n",
"!cp /content/drive/MyDrive/{MODELNAME}_G_{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/D_{MODELEPOCH}.pth\n",
"!cp /content/drive/MyDrive/*.index /content/\n",
"!cp /content/drive/MyDrive/*.npy /content/\n",
"!cp /content/drive/MyDrive/{MODELNAME}{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/weights/{MODELNAME}.pth"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "ZKAyuKb9J6dz"
},
"outputs": [],
"source": [
"# @title 手动预处理（不推荐）\n",
"# @markdown 模型名\n",
"MODELNAME = \"lulu\" # @param {type:\"string\"}\n",
"# @markdown 采样率\n",
"BITRATE = 48000 # @param {type:\"integer\"}\n",
"# @markdown 使用的进程数\n",
"THREADCOUNT = 8 # @param {type:\"integer\"}\n",
"\n",
"!python3 trainset_preprocess_pipeline_print.py /content/dataset {BITRATE} {THREADCOUNT} logs/{MODELNAME} True"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "CrxJqzAUKmPJ"
},
"outputs": [],
"source": [
"# @title 手动提取特征（不推荐）\n",
"# @markdown 模型名\n",
"MODELNAME = \"lulu\" # @param {type:\"string\"}\n",
"# @markdown 使用的进程数\n",
"THREADCOUNT = 8 # @param {type:\"integer\"}\n",
"# @markdown 音高提取算法\n",
"ALGO = \"harvest\" # @param {type:\"string\"}\n",
"\n",
"!python3 extract_f0_print.py logs/{MODELNAME} {THREADCOUNT} {ALGO}\n",
"\n",
"!python3 extract_feature_print.py cpu 1 0 0 logs/{MODELNAME}"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "IMLPLKOaKj58"
},
"outputs": [],
"source": [
"# @title 手动训练（不推荐）\n",
"# @markdown 模型名\n",
"MODELNAME = \"lulu\" # @param {type:\"string\"}\n",
"# @markdown 使用的GPU\n",
"USEGPU = \"0\" # @param {type:\"string\"}\n",
"# @markdown 批大小\n",
"BATCHSIZE = 32 # @param {type:\"integer\"}\n",
"# @markdown 停止的epoch\n",
"MODELEPOCH = 3200 # @param {type:\"integer\"}\n",
"# @markdown 保存epoch间隔\n",
"EPOCHSAVE = 100 # @param {type:\"integer\"}\n",
"# @markdown 采样率\n",
"MODELSAMPLE = \"48k\" # @param {type:\"string\"}\n",
"# @markdown 是否缓存训练集\n",
"CACHEDATA = 1 # @param {type:\"integer\"}\n",
"# @markdown 是否仅保存最新的ckpt文件\n",
"ONLYLATEST = 0 # @param {type:\"integer\"}\n",
"\n",
"!python3 train_nsf_sim_cache_sid_load_pretrain.py -e lulu -sr {MODELSAMPLE} -f0 1 -bs {BATCHSIZE} -g {USEGPU} -te {MODELEPOCH} -se {EPOCHSAVE} -pg pretrained/f0G{MODELSAMPLE}.pth -pd pretrained/f0D{MODELSAMPLE}.pth -l {ONLYLATEST} -c {CACHEDATA}"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "haYA81hySuDl"
},
"outputs": [],
"source": [
"# @title 删除其它pth，只留选中的（慎点，仔细看代码）\n",
"# @markdown 模型名\n",
"MODELNAME = \"lulu\" # @param {type:\"string\"}\n",
"# @markdown 选中模型epoch\n",
"MODELEPOCH = 9600 # @param {type:\"integer\"}\n",
"\n",
"!echo \"备份选中的模型。。。\"\n",
"!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth /content/{MODELNAME}_D_{MODELEPOCH}.pth\n",
"!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/D_{MODELEPOCH}.pth /content/{MODELNAME}_G_{MODELEPOCH}.pth\n",
"\n",
"!echo \"正在删除。。。\"\n",
"!ls /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}\n",
"!rm /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/*.pth\n",
"\n",
"!echo \"恢复选中的模型。。。\"\n",
"!mv /content/{MODELNAME}_D_{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth\n",
"!mv /content/{MODELNAME}_G_{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/D_{MODELEPOCH}.pth\n",
"\n",
"!echo \"删除完成\"\n",
"!ls /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"id": "QhSiPTVPoIRh"
},
"outputs": [],
"source": [
"# @title 清除项目下所有文件，只留选中的模型（慎点，仔细看代码）\n",
"# @markdown 模型名\n",
"MODELNAME = \"lulu\" # @param {type:\"string\"}\n",
"# @markdown 选中模型epoch\n",
"MODELEPOCH = 9600 # @param {type:\"integer\"}\n",
"\n",
"!echo \"备份选中的模型。。。\"\n",
"!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth /content/{MODELNAME}_D_{MODELEPOCH}.pth\n",
"!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/D_{MODELEPOCH}.pth /content/{MODELNAME}_G_{MODELEPOCH}.pth\n",
"\n",
"!echo \"正在删除。。。\"\n",
"!ls /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}\n",
"!rm -rf /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/*\n",
"\n",
"!echo \"恢复选中的模型。。。\"\n",
"!mv /content/{MODELNAME}_D_{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth\n",
"!mv /content/{MODELNAME}_G_{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/D_{MODELEPOCH}.pth\n",
"\n",
"!echo \"删除完成\"\n",
"!ls /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}"
]
}
],
"metadata": {
"accelerator": "GPU",
"colab": {
"private_outputs": true,
"provenance": []
},
"gpuClass": "standard",
"kernelspec": {
"display_name": "Python 3",
"name": "python3"
},
"language_info": {
"name": "python"
}
},
"nbformat": 4,
"nbformat_minor": 0
feat: ipynb for v2 (#332)
2023-05-23 06:58:05 +02:00
}
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