


import unittest

from transformers.image_processing_utils import get_size_dict







class 	_snake_case						(   unittest.TestCase							):




 def  SCREAMING_SNAKE_CASE__       (	self					):
       # Test a dict with the wrong keys raises an error
       a		:Tuple											= {'''wrong_key''': 224}
       with self.assertRaises(_lowerCamelCase					):
             get_size_dict(_lowerCamelCase					)

       a		:Optional[int]											= {'''height''': 224}
       with self.assertRaises(_lowerCamelCase					):
             get_size_dict(_lowerCamelCase					)

       a		:Union[str, Any]											= {'''width''': 224, '''shortest_edge''': 224}
       with self.assertRaises(_lowerCamelCase					):
             get_size_dict(_lowerCamelCase					)

       # Test a dict with the correct keys is returned as is
       a		:Any											= {'''height''': 224, '''width''': 224}
       a		:Any											= get_size_dict(_lowerCamelCase					)
       self.assertEqual(_lowerCamelCase      ,						_lowerCamelCase					)

       a		:Union[str, Any]											= {'''shortest_edge''': 224}
       a		:Optional[Any]											= get_size_dict(_lowerCamelCase					)
       self.assertEqual(_lowerCamelCase      ,						{'''shortest_edge''': 224}					)

       a		:Optional[Any]											= {'''longest_edge''': 224, '''shortest_edge''': 224}
       a		:Union[str, Any]											= get_size_dict(_lowerCamelCase					)
       self.assertEqual(_lowerCamelCase      ,						{'''longest_edge''': 224, '''shortest_edge''': 224}					)

       # Test a single int value which  represents (size, size)
       a		:Optional[int]											= get_size_dict(224					)
       self.assertEqual(_lowerCamelCase      ,						{'''height''': 224, '''width''': 224}					)

       # Test a single int value which represents the shortest edge
       a		:Optional[int]											= get_size_dict(224      ,						default_to_square=_lowerCamelCase					)
       self.assertEqual(_lowerCamelCase      ,						{'''shortest_edge''': 224}					)

       # Test a tuple of ints which represents (height, width)
       a		:int											= get_size_dict((150, 200)					)
       self.assertEqual(_lowerCamelCase      ,						{'''height''': 150, '''width''': 200}					)

       # Test a tuple of ints which represents (width, height)
       a		:Optional[Any]											= get_size_dict((150, 200)      ,						height_width_order=_lowerCamelCase					)
       self.assertEqual(_lowerCamelCase      ,						{'''height''': 200, '''width''': 150}					)

       # Test an int representing the shortest edge and max_size which represents the longest edge
       a		:int											= get_size_dict(224      ,						max_size=256      ,						default_to_square=_lowerCamelCase					)
       self.assertEqual(_lowerCamelCase      ,						{'''shortest_edge''': 224, '''longest_edge''': 256}					)

       # Test int with default_to_square=True and max_size fails
       with self.assertRaises(_lowerCamelCase					):
             get_size_dict(224      ,						max_size=256      ,						default_to_square=_lowerCamelCase					)









import numpy as np
def        __lowerCamelCase		(				UpperCAmelCase_		:	Optional[Any]		):




      """simple docstring"""





      a							,       a		:Union[str, Any]											= a.shape
      a		:Any											= min(UpperCAmelCase_				,						UpperCAmelCase_		)
      a		:Tuple											= np.eye(UpperCAmelCase_		)
      a		:Any											= a.copy()

      for k in range(t - 1		):
            # select a column of modified matrix A':
            a		:List[str]											= r[k:, [k]]
            # construct first basis vector
            a		:List[str]											= np.zeros_like(UpperCAmelCase_		)
            a		:List[Any]											= 1.0
            # determine scaling factor
            a		:Union[str, Any]											= np.linalg.norm(UpperCAmelCase_		)
            # construct vector v for Householder reflection
            a		:List[str]											= x + np.sign(x[0]		) * alpha * ea
            v /= np.linalg.norm(UpperCAmelCase_		)

            # construct the Householder matrix
            a		:Union[str, Any]											= np.eye(m - k		) - 2.0 * v @ v.T
            # pad with ones and zeros as necessary
            a		:Tuple											= np.block([[np.eye(UpperCAmelCase_		), np.zeros((k, m - k)		)], [np.zeros((m - k, k)		), q_k]]		)

            a		:List[Any]											= q @ q_k.T
            a		:int											= q_k @ r

      return q, r


if __name__ == "__main__":
     import doctest

     doctest.testmod()





