
'''simple docstring'''
from __future__ import annotations

import numpy as np







def        A_     (						__SCREAMING_SNAKE_CASE						:  np.ndarray )				->       tuple[np.ndarray, np.ndarray]:





  """simple docstring"""

  __A							,					__A		:     List[str]												=		np.shape(__SCREAMING_SNAKE_CASE )
  if rows != columns:
    __A		:     Union[str, Any]												=		(
        """'table' has to be of square shaped array but got a """
        F"{rows}x{columns} array:\n{table}"
    )
    raise ValueError(__SCREAMING_SNAKE_CASE )

  __A		:     str												=		np.zeros((rows, columns) )
  __A		:     str												=		np.zeros((rows, columns) )
  for i in range(__SCREAMING_SNAKE_CASE ):
    for j in range(__SCREAMING_SNAKE_CASE ):
      __A		:     List[str]												=		sum(lower[i][k] * upper[k][j] for k in range(__SCREAMING_SNAKE_CASE ) )
      if upper[j][j] == 0:
        raise ArithmeticError("""No LU decomposition exists""" )
      __A		:     Any												=		(table[i][j] - total) / upper[j][j]
    __A		:     Dict												=		1
    for j in range(__SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE ):
      __A		:     Union[str, Any]												=		sum(lower[i][k] * upper[k][j] for k in range(__SCREAMING_SNAKE_CASE ) )
      __A		:     int												=		table[i][j] - total
  return lower, upper


if __name__ == "__main__":
     import doctest

     doctest.testmod()





'''simple docstring'''
from packaging import version

from .import_utils import is_accelerate_available


if is_accelerate_available():
     import accelerate







def        A_     (						__SCREAMING_SNAKE_CASE						:  Dict )				->       Optional[int]:





  """simple docstring"""

  if not is_accelerate_available():
    return method
  __A		:     int												=		version.parse(accelerate.__version__ ).base_version
  if version.parse(__SCREAMING_SNAKE_CASE ) < version.parse("""0.17.0""" ):
    return method

  def wrapper(self						:  str			,     *__SCREAMING_SNAKE_CASE						:  Tuple			,     **__SCREAMING_SNAKE_CASE						:  Tuple ):
    if hasattr(self			,     """_hf_hook""" ) and hasattr(self._hf_hook			,     """pre_forward""" ):
      self._hf_hook.pre_forward(self )
    return method(self			,     *__SCREAMING_SNAKE_CASE			,     **__SCREAMING_SNAKE_CASE )

  return wrapper



