89 lines
2.5 KiB
Python
89 lines
2.5 KiB
Python
########################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 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
|
||
|
||
if device not in ["cpu", "mps"]:
|
||
gpu_name = torch.cuda.get_device_name(int(device.split(":")[-1]))
|
||
if "16" in gpu_name or "MX" in gpu_name:
|
||
print("16系显卡/MX系显卡强制单精度")
|
||
is_half = False
|
||
|
||
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
|