




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  __lowerCAmelCase							(				unittest.TestCase   ,			__lowerCAmelCase):






       def        SCREAMING_SNAKE_CASE     ( self:       Tuple					):
         lowercase     :List[str]   						=    load_tool("image-segmentation"					)
         self.tool.setup()
         lowercase     :Any   						=    load_tool("image-segmentation"							,       remote=_UpperCamelCase					)






       def        SCREAMING_SNAKE_CASE     ( self:       Any					):
         lowercase     :Optional[Any]   						=    Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"					)					) / "000000039769.png"					)
         lowercase     :List[str]   						=    self.tool(_UpperCamelCase							,       "cat"					)
         self.assertTrue(isinstance(_UpperCamelCase							,       Image.Image					)					)






       def        SCREAMING_SNAKE_CASE     ( self:       int					):
         lowercase     :List[str]   						=    Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"					)					) / "000000039769.png"					)
         lowercase     :List[str]   						=    self.remote_tool(_UpperCamelCase							,       "cat"					)
         self.assertTrue(isinstance(_UpperCamelCase							,       Image.Image					)					)






       def        SCREAMING_SNAKE_CASE     ( self:       Tuple					):
         lowercase     :int   						=    Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"					)					) / "000000039769.png"					)
         lowercase     :Optional[int]   						=    self.tool(image=_UpperCamelCase							,       label="cat"					)
         self.assertTrue(isinstance(_UpperCamelCase							,       Image.Image					)					)






       def        SCREAMING_SNAKE_CASE     ( self:       int					):
         lowercase     :str   						=    Image.open(Path(get_tests_dir("fixtures/tests_samples/COCO"					)					) / "000000039769.png"					)
         lowercase     :Optional[int]   						=    self.remote_tool(image=_UpperCamelCase							,       label="cat"					)
         self.assertTrue(isinstance(_UpperCamelCase							,       Image.Image					)					)




lowerCAmelCase      :				Union[str, Any]     			=1000







def     A__	(       __A						):







    '''simple docstring'''
    return x * x







def     A__	(       __A ,			__A ,			__A ,			__A = 4						):







    '''simple docstring'''
    assert callable(
        __A						), F"""the function(object) passed should be callable your input : {function}"""
    assert isinstance(__A ,			(float, int)						), F"""a should be float or integer your input : {a}"""
    assert isinstance(function(__A						) ,			(float, int)						), (
        "the function should return integer or float return type of your function, "
        F"""{type(__A						)}"""
    )
    assert isinstance(__A ,			(float, int)						), F"""b should be float or integer your input : {b}"""
    assert (
        isinstance(__A ,			__A						) and precision > 0
    ), F"""precision should be positive integer your input : {precision}"""

    # just applying the formula of simpson for approximate integration written in
    # mentioned article in first comment of this file and above this function

    _lowerCamelCase  :		Optional[Any]			    =    (b - a) / N_STEPS
    _lowerCamelCase  :		str			    =    function(__A						) + function(__A						)

    for i in range(1 ,			__A						):
        _lowerCamelCase  :		str			    =    a + h * i
        result += function(__A						) * (4 if i % 2 else 2)

    result *= h / 3
    return round(__A ,			__A						)


if __name__ == "__main__":
    import doctest

    doctest.testmod()




