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system

util.system

TIME_FORMAT module-attribute 

TIME_FORMAT = '%Y-%m-%d %H:%M:%S KST'

get_cpu_name 

get_cpu_name() -> str

Get CPU name in string

Returns:

  • str ( str ) –

    CPU name (ex: "AMD EPYC 7502 32-Core Processor")

Source code in SaigeToolkit/util/system.py 
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def get_cpu_name() -> str:
    """Get CPU name in string

    Returns:
        str: CPU name (ex: "AMD EPYC 7502 32-Core Processor")
    """
    return cpuinfo.get_cpu_info()["brand_raw"]

get_torch_device_name 

get_torch_device_name(device: Union[device, str, int]) -> str

Get device name in string

Parameters:

  • device (Union[device, str, int]) –

    torch device

Returns:

  • str ( str ) –

    device name (ex: "A100-PCIE-40GB", "AMD EPYC 7502 32-Core Processor")

Source code in SaigeToolkit/util/system.py 
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def get_torch_device_name(device: Union[torch.device, str, int]) -> str:
    """Get device name in string

    Args:
        device (Union[torch.device, str, int]): torch device

    Returns:
        str: device name (ex: "A100-PCIE-40GB", "AMD EPYC 7502 32-Core Processor")
    """
    device = torch.device(device)
    if device.type == "cpu":
        return get_cpu_name()
    else:
        return torch.cuda.get_device_name(device)

get_system_info 

get_system_info() -> Dict[str, str]
Source code in SaigeToolkit/util/system.py 
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def get_system_info() -> Dict[str, str]:
    return {
        "time": datetime.now(pytz.timezone("Asia/Seoul")).strftime(TIME_FORMAT),
        "pc": platform.node(),
        "os": platform.platform(),
        "python": platform.python_version(),
        "cpu": get_cpu_name(),
    }

get_torch_info 

get_torch_info() -> Dict
Source code in SaigeToolkit/util/system.py 
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def get_torch_info() -> Dict:
    return {
        "torch": torch.__version__,
        "cuda": torch.version.cuda,
        "cudnn": torch.backends.cudnn.version(),
        "torch.backends.cuda.matmul.allow_tf32": torch.backends.cuda.matmul.allow_tf32,
        "torch.backends.cudnn.allow_tf32": torch.backends.cudnn.allow_tf32,
        "torch.backends.cudnn.deterministic": torch.backends.cudnn.deterministic,
        "torch.backends.cudnn.benchmark": torch.backends.cudnn.benchmark,
        "os.environ.NVIDIA_TF32_OVERRIDE": os.environ.get("NVIDIA_TF32_OVERRIDE", None),
    }