
"""simple docstring"""


import unittest
from pathlib import Path

from transformers import is_vision_available, load_tool
from transformers.testing_utils import get_tests_dir

from .test_tools_common import ToolTesterMixin


if is_vision_available():
							from PIL import Image

class 					A_			(  unittest.TestCase   ,      __SCREAMING_SNAKE_CASE     ):



							"""simple docstring"""






							def    UpperCAmelCase__							(						self						:Union[str, Any] ):





										"""simple docstring"""

										lowerCamelCase__			:  Optional[int]  =load_tool('image-segmentation' )
										self.tool.setup()
										lowerCamelCase__			:  Dict  =load_tool('image-segmentation'  ,							remote=UpperCamelCase__ )





							def    UpperCAmelCase__							(						self						:Optional[Any] ):





										"""simple docstring"""

										lowerCamelCase__			:  Dict  =Image.open(Path(get_tests_dir('fixtures/tests_samples/COCO' ) ) / '000000039769.png' )
										lowerCamelCase__			:  Dict  =self.tool(UpperCamelCase__  ,							'cat' )
										self.assertTrue(isinstance(UpperCamelCase__  ,							Image.Image ) )





							def    UpperCAmelCase__							(						self						:Dict ):





										"""simple docstring"""

										lowerCamelCase__			:  Union[str, Any]  =Image.open(Path(get_tests_dir('fixtures/tests_samples/COCO' ) ) / '000000039769.png' )
										lowerCamelCase__			:  Optional[int]  =self.remote_tool(UpperCamelCase__  ,							'cat' )
										self.assertTrue(isinstance(UpperCamelCase__  ,							Image.Image ) )





							def    UpperCAmelCase__							(						self						:Any ):





										"""simple docstring"""

										lowerCamelCase__			:  str  =Image.open(Path(get_tests_dir('fixtures/tests_samples/COCO' ) ) / '000000039769.png' )
										lowerCamelCase__			:  Dict  =self.tool(image=UpperCamelCase__  ,							label='cat' )
										self.assertTrue(isinstance(UpperCamelCase__  ,							Image.Image ) )





							def    UpperCAmelCase__							(						self						:Dict ):





										"""simple docstring"""

										lowerCamelCase__			:  Dict  =Image.open(Path(get_tests_dir('fixtures/tests_samples/COCO' ) ) / '000000039769.png' )
										lowerCamelCase__			:  Optional[int]  =self.remote_tool(image=UpperCamelCase__  ,							label='cat' )
										self.assertTrue(isinstance(UpperCamelCase__  ,							Image.Image ) )

"""simple docstring"""


from sklearn.neural_network import MLPClassifier

lowerCAmelCase			=		[[0.0, 0.0], [1.0, 1.0], [1.0, 0.0], [0.0, 1.0]]
lowerCAmelCase			=		[0, 1, 0, 0]


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

clf.fit(X, y)


lowerCAmelCase			=		[[0.0, 0.0], [0.0, 1.0], [1.0, 1.0]]
lowerCAmelCase			=		clf.predict(test)






def      lowerCAmelCase_     (	snake_case_	:    Tuple    )     ->List[Any]:
			return list(snake_case_    )


if __name__ == "__main__":
							import doctest

							doctest.testmod()