mirror of
https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI.git
synced 2025-01-19 21:00:11 +08:00
33e1a0f1d2
* optimize: 精简未用到的配置项并在特征提取初步引入mps * add cmd argument: --noautoopen * fix: i18n * fix * fix * add genlocale workflow * add unitest * fix * fix * fix
80 lines
2.5 KiB
Python
80 lines
2.5 KiB
Python
########################硬件参数########################
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#填写cuda:x, cpu 或 mps, x指代第几张卡，只支持 N卡 / Apple Silicon 加速
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device = "cuda:0"
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#9-10-20-30-40系显卡无脑True，不影响质量，>=20显卡开启有加速
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is_half = True
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#默认0用上所有线程，写数字限制CPU资源使用
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n_cpu = 0
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########################硬件参数########################
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##################下为参数处理逻辑，勿动##################
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########################命令行参数########################
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import argparse
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parser = argparse.ArgumentParser()
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parser.add_argument("--port", type=int, default=7865, help="Listen port")
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parser.add_argument("--pycmd", type=str, default="python", help="Python command")
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parser.add_argument("--colab", action='store_true', help="Launch in colab")
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parser.add_argument("--noparallel", action='store_true', help="Disable parallel processing")
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parser.add_argument("--noautoopen", action='store_true', help="Do not open in browser automatically")
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cmd_opts = parser.parse_args()
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python_cmd=cmd_opts.pycmd
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listen_port=cmd_opts.port
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iscolab=cmd_opts.colab
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noparallel=cmd_opts.noparallel
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noautoopen=cmd_opts.noautoopen
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########################命令行参数########################
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import sys
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import torch
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# has_mps is only available in nightly pytorch (for now) and MasOS 12.3+.
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# check `getattr` and try it for compatibility
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def has_mps() -> bool:
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if sys.platform != "darwin":
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return False
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else:
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if not getattr(torch, 'has_mps', False): return False
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try:
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torch.zeros(1).to(torch.device("mps"))
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return True
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except Exception:
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return False
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if(not torch.cuda.is_available()):
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if has_mps():
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print("没有发现支持的N卡, 使用MPS进行推理")
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device = "mps"
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else:
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print("没有发现支持的N卡, 使用CPU进行推理")
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device = "cpu"
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is_half = False
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if(device not in ["cpu", "mps"]):
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gpu_name = torch.cuda.get_device_name(int(device.split(":")[-1]))
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if("16" in gpu_name or "MX" in gpu_name):
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print("16系显卡/MX系显卡强制单精度")
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is_half = False
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from multiprocessing import cpu_count
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if(n_cpu==0): n_cpu=cpu_count()
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if(is_half):
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#6G显存配置
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x_pad = 3
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x_query = 10
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x_center = 60
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x_max = 65
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else:
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#5G显存配置
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x_pad = 1
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x_query = 6
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x_center = 38
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x_max = 41
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