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import argparse
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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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self.python_cmd, self.listen_port, self.iscolab, self.noparallel, self.noautoopen = 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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@staticmethod
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def arg_parse() -> tuple:
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exe = sys.executable or "python"
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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=exe, 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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if len(sys.argv) > 1 and sys.argv[0].endswith("colab_kernel_launcher.py"):
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args = parser.parse_known_args(sys.argv[1:])[0]
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else:
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args = parser.parse_args()
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args.port = args.port if 0 <= args.port <= 65535 else 7865
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return args.pycmd, args.port, args.colab, args.noparallel, args.noautoopen
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@staticmethod
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def has_mps() -> bool:
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if not torch.backends.mps.is_available():
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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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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 ("16" in self.gpu_name and "V100" not in self.gpu_name.upper()) or "P40" in self.gpu_name.upper() or "1060" in self.gpu_name or "1070" in self.gpu_name or "1080" in self.gpu_name:
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print("Found GPU", self.gpu_name, ", force to fp32")
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self.is_half = False
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else:
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print("Found GPU", self.gpu_name)
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self.gpu_mem = int(torch.cuda.get_device_properties(i_device).total_memory / 1024 / 1024 / 1024 + 0.4)
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elif self.has_mps():
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print("No supported Nvidia GPU found, use MPS instead")
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self.device = "mps"
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self.is_half = False
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else:
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print("No supported Nvidia GPU found, use CPU instead")
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self.device = "cpu"
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self.is_half = False
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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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x_pad, x_query, x_center, x_max = 3, 10, 60, 65
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else:
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x_pad, x_query, x_center, x_max = 1, 6, 38, 41
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if self.gpu_mem is not None and self.gpu_mem <= 4:
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x_pad, x_query, x_center, x_max = 1, 5, 30, 32
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return x_pad, x_query, x_center, x_max
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if __name__ == "__main__":
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config = Config()
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print(config.__dict__)
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