


import numpy as np
from numpy import floataa
from numpy.typing import NDArray






def 				UpperCamelCase      (			__magic_name__  :							Dict					,					__magic_name__  :							int  )     ->						NDArray[floataa]:
		"""simple docstring"""




		lowercase__    ,			lowercase__      =	np.shape(__magic_name__  )

		lowercase__      =	np.zeros((rows, 1)					,					dtype=__magic_name__  )
		for row in reversed(range(__magic_name__  )  ):
				lowercase__      =	0
				for col in range(row + 1					,					__magic_name__  ):
						total += coefficients[row, col] * x[col]

				lowercase__      =	(vector[row] - total) / coefficients[row, row]

		return x






def 				UpperCamelCase      (			__magic_name__  :							int					,					__magic_name__  :							List[Any]  )     ->						NDArray[floataa]:
		"""simple docstring"""




		lowercase__    ,			lowercase__      =	np.shape(__magic_name__  )
		if rows != columns:
				return np.array(()					,					dtype=__magic_name__  )

		# augmented matrix
		lowercase__      =	np.concatenate((coefficients, vector)					,					axis=1  )
		lowercase__      =	augmented_mat.astype("""float64"""  )

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

		lowercase__      =	retroactive_resolution(
		    augmented_mat[:, 0:columns]					,					augmented_mat[:, columns : columns + 1]  )

		return x


if __name__ == "__main__":
	import doctest

	doctest.testmod()





import warnings

from ...utils import logging
from .image_processing_mobilenet_va import MobileNetVaImageProcessor


A :	Optional[Any]												=     logging.get_logger(__name__)



class 							A					( UpperCAmelCase__							):
					'''simple docstring'''






					def __init__(self					:		Optional[int]   ,      *_UpperCAmelCase					:		Union[str, Any]   ,      **_UpperCAmelCase					:		Any	)		->     None:




							"""simple docstring"""


							warnings.warn(
							    """The class MobileNetV1FeatureExtractor is deprecated and will be removed in version 5 of Transformers."""
							    """ Please use MobileNetV1ImageProcessor instead."""   ,      _UpperCAmelCase   ,      )
							super().__init__(*_UpperCAmelCase   ,      **_UpperCAmelCase	)

