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|
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|
|
| device = "cuda:0"
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|
|
|
|
| is_half = True
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|
|
|
|
| n_cpu = 0
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|
|
|
|
|
|
|
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|
|
|
|
| import argparse
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|
|
| 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
|
|
|
|
|
| import sys
|
| import torch
|
|
|
|
|
|
|
|
|
| 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:
|
|
|
| x_pad = 3
|
| x_query = 10
|
| x_center = 60
|
| x_max = 65
|
| else:
|
|
|
| x_pad = 1
|
| x_query = 6
|
| x_center = 38
|
| x_max = 41
|
|
|