import logging

import warnings

# May help avoid undefined symbol errors https://pytorch.org/cppdocs/notes/faq.html#undefined-symbol-errors-from-pytorch-aten

import torch

# For optimizers and normalization there is no Python fallback.

# Absence of cuda backend is a hard error.

# I would like the errors from importing fused_adam_cuda or fused_layer_norm_cuda

# to be triggered lazily, because if someone has installed with --cpp_ext and --cuda_ext

# so they expect those backends to be available, but for some reason they actually aren't

# available (for example because they built improperly in a way that isn't revealed until

# load time) the error message is timely and visible.

from . import optimizers

from . import normalization

__all__ = ["optimizers", "normalization"]

def check_cudnn_version_and_warn(global_option: str, required_cudnn_version: int) -> bool:

cudnn_available = torch.backends.cudnn.is_available()

cudnn_version = torch.backends.cudnn.version() if cudnn_available else None

if not (cudnn_available and (cudnn_version >= required_cudnn_version)):

warnings.warn(

f"`{global_option}` depends on cuDNN {required_cudnn_version} or later, "

f"but {'cuDNN is not available' if not cudnn_available else cudnn_version}"

)

return False

return True

class DeprecatedFeatureWarning(FutureWarning):

pass

def deprecated_warning(msg: str) -> None:

if (

not torch.distributed.is_available

or not torch.distributed.is_initialized()

or (torch.distributed.is_initialized() and torch.distributed.get_rank() == 0)

):

warnings.warn(msg, DeprecatedFeatureWarning)