|
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 |
|
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": |
|
|
|
|
|
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" |
|
|
|
output = subprocess.check_output( |
|
[command, "--query-gpu=count,name", "--format=csv,noheader"], universal_newlines=True |
|
) |
|
output = output.strip() |
|
gpus = output.split(os.linesep) |
|
|
|
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) |
|
|