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Config class (#192)

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* update config.py

* class

* class

* fix
This commit is contained in:
Ftps
2023-04-28 21:43:02 +09:00
committed by GitHub
parent b1134d9f64
commit f391ac1763
3 changed files with 151 additions and 165 deletions
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config.py
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@@ -1,124 +1,108 @@
########################硬件参数########################
# 填写cuda:x, cpu 或 mps, x指代第几张卡，只支持 N卡 / Apple Silicon 加速
device = "cuda:0"
# 9-10-20-30-40系显卡无脑True，不影响质量，>=20显卡开启有加速
is_half = True
# 默认0用上所有线程，写数字限制CPU资源使用
n_cpu = 0
########################硬件参数########################
##################下为参数处理逻辑，勿动##################
########################命令行参数########################
import argparse
parser = argparse.ArgumentParser()
parser.add_argument("--port", type=int, default=7865, help="Listen port")
parser.add_argument("--pycmd", type=str, default="python", help="Python command")
parser.add_argument("--colab", action="store_true", help="Launch in colab")
parser.add_argument(
"--noparallel", action="store_true", help="Disable parallel processing"
)
parser.add_argument(
"--noautoopen", action="store_true", help="Do not open in browser automatically"
)
cmd_opts = parser.parse_args()
python_cmd = cmd_opts.pycmd
listen_port = cmd_opts.port if 0 <= cmd_opts.port <= 65535 else 7865
iscolab = cmd_opts.colab
noparallel = cmd_opts.noparallel
noautoopen = cmd_opts.noautoopen
########################命令行参数########################
import glob
import sys
import torch
# has_mps is only available in nightly pytorch (for now) and MasOS 12.3+.
# check `getattr` and try it for compatibility
def has_mps() -> bool:
if sys.platform != "darwin":
return False
else:
if not getattr(torch, "has_mps", False):
return False
try:
torch.zeros(1).to(torch.device("mps"))
return True
except Exception:
return False
if not torch.cuda.is_available():
if has_mps():
print("没有发现支持的N卡, 使用MPS进行推理")
device = "mps"
else:
print("没有发现支持的N卡, 使用CPU进行推理")
device = "cpu"
is_half = False
gpu_mem = None
if device not in ["cpu", "mps"]:
i_device = int(device.split(":")[-1])
gpu_name = torch.cuda.get_device_name(i_device)
if (
"16" in gpu_name
or "P40" in gpu_name.upper()
or "1070" in gpu_name
or "1080" in gpu_name
):
print("16系显卡强制单精度")
is_half = False
with open("configs/32k.json", "r") as f:
strr = f.read().replace("true", "false")
with open("configs/32k.json", "w") as f:
f.write(strr)
with open("configs/40k.json", "r") as f:
strr = f.read().replace("true", "false")
with open("configs/40k.json", "w") as f:
f.write(strr)
with open("configs/48k.json", "r") as f:
strr = f.read().replace("true", "false")
with open("configs/48k.json", "w") as f:
f.write(strr)
with open("trainset_preprocess_pipeline_print.py", "r") as f:
strr = f.read().replace("3.7", "3.0")
with open("trainset_preprocess_pipeline_print.py", "w") as f:
f.write(strr)
gpu_mem = int(
torch.cuda.get_device_properties(i_device).total_memory / 1024 / 1024 / 1024
+ 0.4
)
if gpu_mem <= 4:
with open("trainset_preprocess_pipeline_print.py", "r") as f:
strr = f.read().replace("3.7", "3.0")
with open("trainset_preprocess_pipeline_print.py", "w") as f:
f.write(strr)
from multiprocessing import cpu_count
if n_cpu == 0:
n_cpu = cpu_count()
if is_half:
# 6G显存配置
x_pad = 3
x_query = 10
x_center = 60
x_max = 65
else:
# 5G显存配置
x_pad = 1
x_query = 6
x_center = 38
x_max = 41
if gpu_mem != None and gpu_mem <= 4:
x_pad = 1
x_query = 5
x_center = 30
x_max = 32
class Config:
def __init__(self):
self.device = "cuda:0"
self.is_half = True
self.n_cpu = 0
self.gpu_name = None
self.gpu_mem = None
(
self.python_cmd,
self.listen_port,
self.iscolab,
self.noparallel,
self.noautoopen,
) = self.arg_parse()
self.x_pad, self.x_query, self.x_center, self.x_max = self.device_config()
def arg_parse(self) -> tuple:
parser = argparse.ArgumentParser()
parser.add_argument("--port", type=int, default=7865, help="Listen port")
parser.add_argument(
"--pycmd", type=str, default="python", help="Python command"
)
parser.add_argument("--colab", action="store_true", help="Launch in colab")
parser.add_argument(
"--noparallel", action="store_true", help="Disable parallel processing"
)
parser.add_argument(
"--noautoopen",
action="store_true",
help="Do not open in browser automatically",
)
cmd_opts = parser.parse_args()
cmd_opts.port = cmd_opts.port if 0 <= cmd_opts.port <= 65535 else 7865
return (
cmd_opts.pycmd,
cmd_opts.port,
cmd_opts.colab,
cmd_opts.noparallel,
cmd_opts.noautoopen,
)
def device_config(self) -> tuple:
if torch.cuda.is_available():
self.gpu_name = torch.cuda.get_device_name(int(self.device.split(":")[-1]))
i_device = int(self.device.split(":")[-1])
self.gpu_name = torch.cuda.get_device_name(i_device)
if (
"16" in self.gpu_name
or "P40" in self.gpu_name.upper()
or "1070" in self.gpu_name
or "1080" in self.gpu_name
):
print("16系显卡强制单精度")
self.is_half = False
for config_file in ["32k.json", "40k.json", "48k.json"]:
with open(f"configs/{config_file}", "a") as f:
strr = f.read().replace("true", "false")
f.write(strr)
self.gpu_mem = int(
torch.cuda.get_device_properties(i_device).total_memory
/ 1024
/ 1024
/ 1024
+ 0.4
)
if self.gpu_mem <= 4:
with open("trainset_preprocess_pipeline_print.py", "a") as f:
strr = f.read().replace("3.7", "3.0")
f.write(strr)
elif torch.backends.mps.is_available():
print("没有发现支持的N卡, 使用MPS进行推理")
self.device = "mps"
else:
print("没有发现支持的N卡, 使用CPU进行推理")
self.device = "cpu"
if self.n_cpu == 0:
self.n_cpu = cpu_count()
if self.is_half:
# 6G显存配置
x_pad = 3
x_query = 10
x_center = 60
x_max = 65
else:
# 5G显存配置
x_pad = 1
x_query = 6
x_center = 38
x_max = 41
if self.gpu_name != None and self.gpu_mem <= 4:
x_pad = 1
x_query = 5
x_center = 30
x_max = 32
return x_pad, x_query, x_center, x_max