402 lines
19 KiB
Plaintext
402 lines
19 KiB
Plaintext
{
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"cells": [
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{
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"attachments": {},
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"cell_type": "markdown",
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"metadata": {
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"id": "ZFFCx5J80SGa"
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},
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"source": [
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"[![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)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "GmFP6bN9dvOq"
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},
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"outputs": [],
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"source": [
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"#@title 查看显卡\n",
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"!nvidia-smi"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "wjddIFr1oS3W"
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},
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"outputs": [],
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"source": [
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"#@title 安装依赖\n",
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"!apt-get -y install build-essential python3-dev ffmpeg\n",
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"!pip3 install --upgrade setuptools wheel\n",
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"!pip3 install --upgrade pip\n",
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"!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"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "ge_97mfpgqTm"
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},
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"outputs": [],
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"source": [
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"#@title 克隆仓库\n",
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"\n",
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"!mkdir Retrieval-based-Voice-Conversion-WebUI\n",
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"%cd /content/Retrieval-based-Voice-Conversion-WebUI\n",
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"!git init\n",
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"!git remote add origin https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI.git\n",
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"!git fetch origin cfd984812804ddc9247d65b14c82cd32e56c1133 --depth=1 \n",
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"!git reset --hard FETCH_HEAD"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "BLDEZADkvlw1"
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},
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"outputs": [],
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"source": [
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"#@title 更新仓库(一般无需执行)\n",
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"!git pull"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "pqE0PrnuRqI2"
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},
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"outputs": [],
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"source": [
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"#@title 安装aria2\n",
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"!apt -y install -qq aria2"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "UG3XpUwEomUz"
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},
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"outputs": [],
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"source": [
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"#@title 下载底模\n",
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"\n",
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"# v1\n",
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"!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",
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"!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",
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"!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",
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"!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",
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"!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",
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"!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",
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"!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",
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"!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",
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"!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",
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"!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",
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"!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",
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"!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",
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"\n",
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"#v2\n",
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"# !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",
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"!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",
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"# !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",
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"# !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",
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"!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",
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"# !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",
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"# !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",
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"!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",
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"# !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",
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"# !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",
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"!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",
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"# !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"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "HugjmZqZRuiF"
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},
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"outputs": [],
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"source": [
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"#@title 下载人声分离模型\n",
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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",
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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/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"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "2RCaT9FTR0ej"
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},
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"outputs": [],
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"source": [
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"#@title 下载hubert_base\n",
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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"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "jwu07JgqoFON"
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},
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"outputs": [],
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"source": [
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"#@title 挂载谷歌云盘\n",
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"\n",
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"from google.colab import drive\n",
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"drive.mount('/content/drive')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "Mwk7Q0Loqzjx"
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},
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"outputs": [],
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"source": [
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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",
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"#@markdown 数据集位置\n",
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"DATASET = \"/content/drive/MyDrive/dataset/lulu20230327_32k.zip\" #@param {type:\"string\"}\n",
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"\n",
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"!mkdir -p /content/dataset\n",
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"!unzip -d /content/dataset -B {DATASET}"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "PDlFxWHWEynD"
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},
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"outputs": [],
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"source": [
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"#@title 重命名数据集中的重名文件\n",
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"!ls -a /content/dataset/\n",
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"!rename 's/(\\w+)\\.(\\w+)~(\\d*)/$1_$3.$2/' /content/dataset/*.*~*"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "7vh6vphDwO0b"
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},
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"outputs": [],
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"source": [
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"#@title 启动web\n",
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"%cd /content/Retrieval-based-Voice-Conversion-WebUI\n",
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"# %load_ext tensorboard\n",
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"# %tensorboard --logdir /content/Retrieval-based-Voice-Conversion-WebUI/logs\n",
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"!python3 infer-web.py --colab --pycmd python3"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "FgJuNeAwx5Y_"
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},
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"outputs": [],
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"source": [
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"#@title 手动将训练后的模型文件备份到谷歌云盘\n",
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"#@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",
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"\n",
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"#@markdown 模型名\n",
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"MODELNAME = \"lulu\" #@param {type:\"string\"}\n",
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"#@markdown 模型epoch\n",
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"MODELEPOCH = 9600 #@param {type:\"integer\"}\n",
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"\n",
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"!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth /content/drive/MyDrive/{MODELNAME}_D_{MODELEPOCH}.pth\n",
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"!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/D_{MODELEPOCH}.pth /content/drive/MyDrive/{MODELNAME}_G_{MODELEPOCH}.pth\n",
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"!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/added_*.index /content/drive/MyDrive/\n",
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"!cp /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/total_*.npy /content/drive/MyDrive/\n",
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"\n",
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"!cp /content/Retrieval-based-Voice-Conversion-WebUI/weights/{MODELNAME}.pth /content/drive/MyDrive/{MODELNAME}{MODELEPOCH}.pth"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "OVQoLQJXS7WX"
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},
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"outputs": [],
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"source": [
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"#@title 从谷歌云盘恢复pth\n",
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"#@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",
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"\n",
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"#@markdown 模型名\n",
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"MODELNAME = \"lulu\" #@param {type:\"string\"}\n",
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"#@markdown 模型epoch\n",
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"MODELEPOCH = 7500 #@param {type:\"integer\"}\n",
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"\n",
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"!mkdir -p /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}\n",
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"\n",
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"!cp /content/drive/MyDrive/{MODELNAME}_D_{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/G_{MODELEPOCH}.pth\n",
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"!cp /content/drive/MyDrive/{MODELNAME}_G_{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/logs/{MODELNAME}/D_{MODELEPOCH}.pth\n",
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"!cp /content/drive/MyDrive/*.index /content/\n",
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"!cp /content/drive/MyDrive/*.npy /content/\n",
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"!cp /content/drive/MyDrive/{MODELNAME}{MODELEPOCH}.pth /content/Retrieval-based-Voice-Conversion-WebUI/weights/{MODELNAME}.pth"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "ZKAyuKb9J6dz"
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},
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"outputs": [],
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"source": [
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"#@title 手动预处理(不推荐)\n",
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"#@markdown 模型名\n",
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"MODELNAME = \"lulu\" #@param {type:\"string\"}\n",
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"#@markdown 采样率\n",
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"BITRATE = 48000 #@param {type:\"integer\"}\n",
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"#@markdown 使用的进程数\n",
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"THREADCOUNT = 8 #@param {type:\"integer\"}\n",
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"\n",
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"!python3 trainset_preprocess_pipeline_print.py /content/dataset {BITRATE} {THREADCOUNT} logs/{MODELNAME} True\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "CrxJqzAUKmPJ"
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},
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"outputs": [],
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"source": [
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"#@title 手动提取特征(不推荐)\n",
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"#@markdown 模型名\n",
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"MODELNAME = \"lulu\" #@param {type:\"string\"}\n",
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"#@markdown 使用的进程数\n",
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"THREADCOUNT = 8 #@param {type:\"integer\"}\n",
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"#@markdown 音高提取算法\n",
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"ALGO = \"harvest\" #@param {type:\"string\"}\n",
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"\n",
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"!python3 extract_f0_print.py logs/{MODELNAME} {THREADCOUNT} {ALGO}\n",
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"\n",
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"!python3 extract_feature_print.py cpu 1 0 0 logs/{MODELNAME}\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "IMLPLKOaKj58"
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},
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"outputs": [],
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"source": [
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"#@title 手动训练(不推荐)\n",
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"#@markdown 模型名\n",
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"MODELNAME = \"lulu\" #@param {type:\"string\"}\n",
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"#@markdown 使用的GPU\n",
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"USEGPU = \"0\" #@param {type:\"string\"}\n",
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"#@markdown 批大小\n",
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"BATCHSIZE = 32 #@param {type:\"integer\"}\n",
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"#@markdown 停止的epoch\n",
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"MODELEPOCH = 3200 #@param {type:\"integer\"}\n",
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"#@markdown 保存epoch间隔\n",
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"EPOCHSAVE = 100 #@param {type:\"integer\"}\n",
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"#@markdown 采样率\n",
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"MODELSAMPLE = \"48k\" #@param {type:\"string\"}\n",
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"#@markdown 是否缓存训练集\n",
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"CACHEDATA = 1 #@param {type:\"integer\"}\n",
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"#@markdown 是否仅保存最新的ckpt文件\n",
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"ONLYLATEST = 0 #@param {type:\"integer\"}\n",
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"\n",
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"!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}\n"
|
||
]
|
||
},
|
||
{
|
||
"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
|
||
}
|