

'''simple docstring'''
import os
import socket
from contextlib import contextmanager

import torch

from ..commands.config.default import write_basic_config  # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
from .transformer_engine import convert_model
from .versions import is_torch_version


if is_deepspeed_available():
     from deepspeed import DeepSpeedEngine

if is_tpu_available(check_device=False):
     import torch_xla.core.xla_model as xm


def        _lowerCAmelCase					(						_UpperCamelCase						:     Union[str, Any]				)      ->			Dict:
     """simple docstring"""




     if is_torch_version('<'							, '2.0.0'				) or not hasattr(_UpperCamelCase							, '_dynamo'				):
          return False
     return isinstance(_UpperCamelCase							, torch._dynamo.eval_frame.OptimizedModule				)


def        _lowerCAmelCase					(						_UpperCamelCase						:     List[Any]							, _UpperCamelCase						:     bool = True				)      ->			Any:
     """simple docstring"""




     _SCREAMING_SNAKE_CASE							    =(torch.nn.parallel.DistributedDataParallel, torch.nn.DataParallel)

     _SCREAMING_SNAKE_CASE							    =is_compiled_module(_UpperCamelCase				)
     if is_compiled:
          _SCREAMING_SNAKE_CASE							    =model
          _SCREAMING_SNAKE_CASE							    =model._orig_mod

     if is_deepspeed_available():
          options += (DeepSpeedEngine,)

     while isinstance(_UpperCamelCase							, _UpperCamelCase				):
          _SCREAMING_SNAKE_CASE							    =model.module

     if not keep_fpaa_wrapper:
          _SCREAMING_SNAKE_CASE							    =getattr(_UpperCamelCase							, 'forward'				)
          _SCREAMING_SNAKE_CASE							    =model.__dict__.pop('_original_forward'							, _UpperCamelCase				)
          if original_forward is not None:
               while hasattr(_UpperCamelCase							, '__wrapped__'				):
                    _SCREAMING_SNAKE_CASE							    =forward.__wrapped__
                    if forward == original_forward:
                         break
               _SCREAMING_SNAKE_CASE							    =forward
          if getattr(_UpperCamelCase							, '_converted_to_transformer_engine'							, _UpperCamelCase				):
               convert_model(_UpperCamelCase							, to_transformer_engine=_UpperCamelCase				)

     if is_compiled:
          _SCREAMING_SNAKE_CASE							    =model
          _SCREAMING_SNAKE_CASE							    =compiled_model

     return model


def        _lowerCAmelCase					(						)      ->			Optional[Any]:
     """simple docstring"""




     PartialState().wait_for_everyone()


def        _lowerCAmelCase					(						_UpperCamelCase						:     str							, _UpperCamelCase						:     Tuple				)      ->			Any:
     """simple docstring"""




     if PartialState().distributed_type == DistributedType.TPU:
          xm.save(_UpperCamelCase							, _UpperCamelCase				)
     elif PartialState().local_process_index == 0:
          torch.save(_UpperCamelCase							, _UpperCamelCase				)


@contextmanager
def        _lowerCAmelCase					(						**_UpperCamelCase						:     Union[str, Any]				)      ->			int:
     """simple docstring"""




     for key, value in kwargs.items():
          _SCREAMING_SNAKE_CASE							    =str(_UpperCamelCase				)

     yield

     for key in kwargs:
          if key.upper() in os.environ:
               del os.environ[key.upper()]


def        _lowerCAmelCase					(						_UpperCamelCase						:     int				)      ->			Any:
     """simple docstring"""




     if not hasattr(_UpperCamelCase							, '__qualname__'				) and not hasattr(_UpperCamelCase							, '__name__'				):
          _SCREAMING_SNAKE_CASE							    =getattr(_UpperCamelCase							, '__class__'							, _UpperCamelCase				)
     if hasattr(_UpperCamelCase							, '__qualname__'				):
          return obj.__qualname__
     if hasattr(_UpperCamelCase							, '__name__'				):
          return obj.__name__
     return str(_UpperCamelCase				)


def        _lowerCAmelCase					(						_UpperCamelCase						:     List[Any]							, _UpperCamelCase						:     Optional[Any]				)      ->			str:
     """simple docstring"""




     for key, value in source.items():
          if isinstance(_UpperCamelCase							, _UpperCamelCase				):
               _SCREAMING_SNAKE_CASE							    =destination.setdefault(_UpperCamelCase							, {}				)
               merge_dicts(_UpperCamelCase							, _UpperCamelCase				)
          else:
               _SCREAMING_SNAKE_CASE							    =value

     return destination







def        _lowerCAmelCase					(						_UpperCamelCase						:     int = None				)      ->			bool:
     """simple docstring"""




     if port is None:
          _SCREAMING_SNAKE_CASE							    =2_95_00
     with socket.socket(socket.AF_INET							, socket.SOCK_STREAM				) as s:
          return s.connect_ex(('localhost', port)				) == 0



'''simple docstring'''






lowerCAmelCase__											=	'''Input must be a string of 8 numbers plus letter'''
lowerCAmelCase__											=	'''TRWAGMYFPDXBNJZSQVHLCKE'''


def 		_A     (    A__      ):






 """simple docstring"""



 if not isinstance(A__     ,				A__      ):
  __lowercase							  = F"Expected string as input, found {type(A__      ).__name__}"
  raise TypeError(A__      )

 __lowercase							  = spanish_id.replace('''-'''     ,				''''''      ).upper()
 if len(A__      ) != 9:
  raise ValueError(A__      )

 try:
  __lowercase							  = int(spanish_id_clean[0:8]      )
  __lowercase							  = spanish_id_clean[8]
 except ValueError as ex:
  raise ValueError(A__      ) from ex

 if letter.isdigit():
  raise ValueError(A__      )

 return letter == LOOKUP_LETTERS[number % 23]


if __name__ == "__main__":
 import doctest

 doctest.testmod()

