
'''simple docstring'''
import numpy as np
from numpy import floataa
from numpy.typing import NDArray







def 							A_  (    __SCREAMING_SNAKE_CASE    :	NDArray[floataa]      ,  __SCREAMING_SNAKE_CASE    :	NDArray[floataa]			)					->							NDArray[floataa]:





  """simple docstring"""

  __A				,       __A		:  List[str]       				=		np.shape(__SCREAMING_SNAKE_CASE			)

  __A		:  NDArray[floataa]       				=		np.zeros((rows, 1)      ,  dtype=__SCREAMING_SNAKE_CASE			)
  for row in reversed(range(__SCREAMING_SNAKE_CASE			)			):
    __A		:  Union[str, Any]       				=		0
    for col in range(row + 1      ,  __SCREAMING_SNAKE_CASE			):
      total += coefficients[row, col] * x[col]

    __A		:  Dict       				=		(vector[row] - total) / coefficients[row, row]

  return x







def 							A_  (    __SCREAMING_SNAKE_CASE    :	NDArray[floataa]      ,  __SCREAMING_SNAKE_CASE    :	NDArray[floataa]			)					->							NDArray[floataa]:





  """simple docstring"""

  __A				,       __A		:  Any       				=		np.shape(__SCREAMING_SNAKE_CASE			)
  if rows != columns:
    return np.array(()      ,  dtype=__SCREAMING_SNAKE_CASE			)

  # augmented matrix
  __A		:  NDArray[floataa]       				=		np.concatenate((coefficients, vector)      ,  axis=1			)
  __A		:  List[Any]       				=		augmented_mat.astype("""float64"""			)

  # scale the matrix leaving it triangular
  for row in range(rows - 1			):
    __A		:  str       				=		augmented_mat[row, row]
    for col in range(row + 1      ,  __SCREAMING_SNAKE_CASE			):
      __A		:  Union[str, Any]       				=		augmented_mat[col, row] / pivot
      augmented_mat[col, :] -= factor * augmented_mat[row, :]

  __A		:  List[str]       				=		retroactive_resolution(
      augmented_mat[:, 0:columns]      ,  augmented_mat[:, columns : columns + 1]			)

  return x


if __name__ == "__main__":
     import doctest

     doctest.testmod()





'''simple docstring'''
import warnings

from ...utils import logging
from .image_processing_vit import ViTImageProcessor


A__ :		Optional[int]					=logging.get_logger(__name__)







class 			__A					(			_SCREAMING_SNAKE_CASE      ):
 def __init__( self      :     Union[str, Any]					, *lowerCamelCase      :     Dict					, **lowerCamelCase      :     Optional[Any]							):



   """simple docstring"""





   warnings.warn(
       """The class ViTFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please"""
       """ use ViTImageProcessor instead."""					, lowerCamelCase					, )
   super().__init__(*lowerCamelCase					, **lowerCamelCase							)



