def str_to_bool(value) -> int:
    """
    Converts a string representation of truth to `True` (1) or `False` (0).
    True values are `y`, `yes`, `t`, `true`, `on`, and `1`; False value are `n`, `no`, `f`, `false`, `off`, and `0`;
    """
    value = value.lower()
    if value in ("y", "yes", "t", "true", "on", "1"):
        return 1
    elif value in ("n", "no", "f", "false", "off", "0"):
        return 0
    else:
        raise ValueError(f"invalid truth value {value}")
def get_int_from_env(env_keys, default):
    """Returns the first positive env value found in the `env_keys` list or the default."""
    for e in env_keys:
        val = int(os.environ.get(e, -1))
        if val >= 0:
            return val
    return default
def parse_flag_from_env(key, default=False):
    """Returns truthy value for `key` from the env if available else the default."""
    value = os.environ.get(key, str(default))
    return str_to_bool(value) == 1  # As its name indicates `str_to_bool` actually returns an int...
def parse_choice_from_env(key, default="no"):
    value = os.environ.get(key, str(default))
    return value
def are_libraries_initialized(*library_names: str) -> Dict[str, bool]:
    """
    Checks if any of `library_names` are imported in the environment. Will return results as a `key:bool` pair.
    """
    return [lib_name for lib_name in library_names if lib_name in sys.modules.keys()]
def get_gpu_info():
    """
    Gets GPU count and names using `nvidia-smi` instead of torch to not initialize CUDA.
    Largely based on the `gputil` library.
    """
    if platform.system() == "Windows":
        # If platform is Windows and nvidia-smi can't be found in path
        # try from systemd rive with default installation path
        command = spawn.find_executable("nvidia-smi")
        if command is None:
            command = "%s\\Program Files\\NVIDIA Corporation\\NVSMI\\nvidia-smi.exe" % os.environ["systemdrive"]
    else:
        command = "nvidia-smi"
    # Returns as list of `n` GPUs and their names
    output = subprocess.check_output(
        [command, "--query-gpu=count,name", "--format=csv,noheader"], universal_newlines=True
    )
    output = output.strip()
    gpus = output.split(os.linesep)
    # Get names from output
    gpu_count = len(gpus)
    gpu_names = [gpu.split(",")[1].strip() for gpu in gpus]
    return gpu_names, gpu_count
def check_cuda_p2p_ib_support():
    """
    Checks if the devices being used have issues with P2P and IB communications, namely any consumer GPU hardware after
    the 3090.
    Noteably uses `nvidia-smi` instead of torch to not initialize CUDA.
    """
    try:
        device_names, device_count = get_gpu_info()
        unsupported_devices = {"RTX 3090", "RTX 40"}
        if device_count > 1:
            if any(
                unsupported_device in device_name
                for device_name in device_names
                for unsupported_device in unsupported_devices
            ):
                return False
    except Exception:
        pass
    return True
def check_fp8_capability():
    """
    Checks if all the current GPUs available support FP8.
    Notably must initialize `torch.cuda` to check.
    """
    cuda_device_capacity = torch.cuda.get_device_capability()
    return cuda_device_capacity >= (8, 9)