mirror of
https://github.com/RVC-Project/Retrieval-based-Voice-Conversion-WebUI.git
synced 2025-01-01 12:35:04 +08:00
Update config.py
This commit is contained in:
RVC-Boss
GitHub
parent
69ea94609b
commit
8370356d95
225
config.py
225
config.py
@ -1,109 +1,116 @@
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import argparse
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import glob
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import sys
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import torch
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from multiprocessing import cpu_count
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class Config:
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def __init__(self):
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self.device = "cuda:0"
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self.is_half = True
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self.n_cpu = 0
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self.gpu_name = None
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self.gpu_mem = None
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(
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self.python_cmd,
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self.listen_port,
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self.iscolab,
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self.noparallel,
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self.noautoopen,
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) = self.arg_parse()
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self.x_pad, self.x_query, self.x_center, self.x_max = self.device_config()
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def arg_parse(self) -> tuple:
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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(
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"--pycmd", type=str, default="python", help="Python command"
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)
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parser.add_argument("--colab", action="store_true", help="Launch in colab")
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parser.add_argument(
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"--noparallel", action="store_true", help="Disable parallel processing"
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)
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parser.add_argument(
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"--noautoopen",
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action="store_true",
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help="Do not open in browser automatically",
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)
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cmd_opts = parser.parse_args()
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cmd_opts.port = cmd_opts.port if 0 <= cmd_opts.port <= 65535 else 7865
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return (
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cmd_opts.pycmd,
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cmd_opts.port,
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cmd_opts.colab,
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cmd_opts.noparallel,
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cmd_opts.noautoopen,
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)
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def device_config(self) -> tuple:
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if torch.cuda.is_available():
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i_device = int(self.device.split(":")[-1])
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self.gpu_name = torch.cuda.get_device_name(i_device)
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if (
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"16" in self.gpu_name
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or "P40" in self.gpu_name.upper()
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or "1070" in self.gpu_name
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or "1080" in self.gpu_name
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):
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print("16系显卡强制单精度")
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self.is_half = False
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for config_file in ["32k.json", "40k.json", "48k.json"]:
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with open(f"configs/{config_file}", "r+") as f:
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strr = f.read().replace("true", "false")
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f.write(strr)
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self.gpu_mem = int(
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torch.cuda.get_device_properties(i_device).total_memory
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/ 1024
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/ 1024
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/ 1024
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+ 0.4
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)
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if self.gpu_mem <= 4:
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with open("trainset_preprocess_pipeline_print.py", "r+") as f:
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strr = f.read().replace("3.7", "3.0")
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f.write(strr)
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else:
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self.gpu_name = None
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elif torch.backends.mps.is_available():
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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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self.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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self.device = "cpu"
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if self.n_cpu == 0:
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self.n_cpu = cpu_count()
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if self.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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if self.gpu_name != None and self.gpu_mem <= 4:
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x_pad = 1
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x_query = 5
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x_center = 30
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x_max = 32
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return x_pad, x_query, x_center, x_max
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import argparse
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import glob
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import sys
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import torch
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from multiprocessing import cpu_count
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class Config:
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def __init__(self):
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self.device = "cuda:0"
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self.is_half = True
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self.n_cpu = 0
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self.gpu_name = None
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self.gpu_mem = None
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(
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self.python_cmd,
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self.listen_port,
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self.iscolab,
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self.noparallel,
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self.noautoopen,
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) = self.arg_parse()
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self.x_pad, self.x_query, self.x_center, self.x_max = self.device_config()
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def arg_parse(self) -> tuple:
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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(
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"--pycmd", type=str, default="python", help="Python command"
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)
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parser.add_argument("--colab", action="store_true", help="Launch in colab")
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parser.add_argument(
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"--noparallel", action="store_true", help="Disable parallel processing"
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)
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parser.add_argument(
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"--noautoopen",
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action="store_true",
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help="Do not open in browser automatically",
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)
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cmd_opts = parser.parse_args()
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cmd_opts.port = cmd_opts.port if 0 <= cmd_opts.port <= 65535 else 7865
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return (
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cmd_opts.pycmd,
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cmd_opts.port,
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cmd_opts.colab,
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cmd_opts.noparallel,
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cmd_opts.noautoopen,
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)
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def device_config(self) -> tuple:
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if torch.cuda.is_available():
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i_device = int(self.device.split(":")[-1])
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self.gpu_name = torch.cuda.get_device_name(i_device)
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if (
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("16" in gpu_name and "V100"not in gpu_name.upper())
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or "P40" in self.gpu_name.upper()
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or "1070" in self.gpu_name
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or "1080" in self.gpu_name
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):
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print("16系显卡强制单精度")
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self.is_half = False
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for config_file in ["32k.json", "40k.json", "48k.json"]:
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with open(f"configs/{config_file}", "r") as f:
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strr = f.read().replace("true", "false")
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with open(f"configs/{config_file}", "w") as f:
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f.write(strr)
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with open("trainset_preprocess_pipeline_print.py", "r") as f:
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strr = f.read().replace("3.7", "3.0")
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with open("trainset_preprocess_pipeline_print.py", "w") as f:
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f.write(strr)
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else:
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self.gpu_name = None
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self.gpu_mem = int(
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torch.cuda.get_device_properties(i_device).total_memory
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/ 1024
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/ 1024
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/ 1024
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+ 0.4
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)
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if self.gpu_mem <= 4:
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with open("trainset_preprocess_pipeline_print.py", "r") as f:
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strr = f.read().replace("3.7", "3.0")
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with open("trainset_preprocess_pipeline_print.py", "w") as f:
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f.write(strr)
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elif torch.backends.mps.is_available():
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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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self.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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self.device = "cpu"
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self.is_half = True
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if self.n_cpu == 0:
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self.n_cpu = cpu_count()
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if self.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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if self.gpu_mem != None and self.gpu_mem <= 4:
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x_pad = 1
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x_query = 5
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x_center = 30
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x_max = 32
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return x_pad, x_query, x_center, x_max
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