




from sklearn.neural_network import MLPClassifier

lowercase__   :    int 					=      [[0.0, 0.0], [1.0, 1.0], [1.0, 0.0], [0.0, 1.0]]
lowercase__   :    List[Any] 					=      [0, 1, 0, 0]


lowercase__   :    str 					=      MLPClassifier(
    solver="lbfgs", alpha=1E-5, hidden_layer_sizes=(5, 2), random_state=1
)

clf.fit(X, y)


lowercase__   :    str 					=      [[0.0, 0.0], [0.0, 1.0], [1.0, 1.0]]
lowercase__   :    str 					=      clf.predict(test)

def       SCREAMING_SNAKE_CASE							(     __UpperCamelCase)    ->  Any:
     return list(lowerCAmelCase__)


if __name__ == "__main__":
   import doctest

   doctest.testmod()







import unittest

from transformers.image_processing_utils import get_size_dict




class     a__ (      unittest.TestCase   ):







     def     lowerCAmelCase_       (			self				)						->					Optional[int]:



          '''simple docstring'''



          a											=   {"wrong_key": 224}
          with self.assertRaises(A				):
               get_size_dict(A				)

          a											=   {"height": 224}
          with self.assertRaises(A				):
               get_size_dict(A				)

          a											=   {"width": 224, "shortest_edge": 224}
          with self.assertRaises(A				):
               get_size_dict(A				)

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

          a											=   {"shortest_edge": 224}
          a											=   get_size_dict(A				)
          self.assertEqual(A						,	{"shortest_edge": 224}				)

          a											=   {"longest_edge": 224, "shortest_edge": 224}
          a											=   get_size_dict(A				)
          self.assertEqual(A						,	{"longest_edge": 224, "shortest_edge": 224}				)

          # Test a single int value which  represents (size, size)
          a											=   get_size_dict(224				)
          self.assertEqual(A						,	{"height": 224, "width": 224}				)

          # Test a single int value which represents the shortest edge
          a											=   get_size_dict(224						,	default_to_square=A				)
          self.assertEqual(A						,	{"shortest_edge": 224}				)

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

          # Test a tuple of ints which represents (width, height)
          a											=   get_size_dict((150, 200)						,	height_width_order=A				)
          self.assertEqual(A						,	{"height": 200, "width": 150}				)

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

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

