





"""simple docstring"""



def 		__lowercase     (   snake_case_  :  float						)   ->int:



    '''simple docstring'''







    return 10 - x * x







def 		__lowercase     (   snake_case_  :  float				,snake_case_  :  float						)   ->Tuple:



    '''simple docstring'''







    if equation(__SCREAMING_SNAKE_CASE						) * equation(__SCREAMING_SNAKE_CASE						) >= 0:
        raise ValueError('''Wrong space!'''						)

    __A    :						Any						 =     a
    while (b - a) >= 0.01:
        # Find middle point
        __A    :						Dict						 =     (a + b) / 2
        # Check if middle point is root
        if equation(__SCREAMING_SNAKE_CASE						) == 0.0:
            break
        # Decide the side to repeat the steps
        if equation(__SCREAMING_SNAKE_CASE						) * equation(__SCREAMING_SNAKE_CASE						) < 0:
            __A    :						Optional[Any]						 =     c
        else:
            __A    :						List[Any]						 =     c
    return c


if __name__ == "__main__":
       import doctest

       doctest.testmod()

       print(bisection(-2, 5))
       print(bisection(0, 6))






'''simple docstring'''







from pathlib import Path
from typing import List

from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText


if is_torch_available():
							import torch

if is_vision_available():
							from PIL import Image


_lowercase :  List[str]    							=       ["text", "image", "audio"]
def 					snake_case_		(				__SCREAMING_SNAKE_CASE					: List[str]							):



						"""simple docstring"""





						lowercase_	:     int													=       []

						for input_type in input_types:
												if input_type == "text":
																		inputs.append('''Text input'''							)
												elif input_type == "image":
																		inputs.append(
																		    Image.open(Path(get_tests_dir('''fixtures/tests_samples/COCO'''							)							) / '''000000039769.png'''							).resize((512, 512)							)							)
												elif input_type == "audio":
																		inputs.append(torch.ones(3000							)							)
												elif isinstance(__SCREAMING_SNAKE_CASE      ,      __SCREAMING_SNAKE_CASE							):
																		inputs.append(create_inputs(__SCREAMING_SNAKE_CASE							)							)
												else:
																		raise ValueError(F'''Invalid type requested: {input_type}'''							)

						return inputs
def 					snake_case_		(				__SCREAMING_SNAKE_CASE					: List							):



						"""simple docstring"""





						lowercase_	:     Optional[Any]													=       []

						for output in outputs:
												if isinstance(__SCREAMING_SNAKE_CASE      ,      (str, AgentText)							):
																		output_types.append('''text'''							)
												elif isinstance(__SCREAMING_SNAKE_CASE      ,      (Image.Image, AgentImage)							):
																		output_types.append('''image'''							)
												elif isinstance(__SCREAMING_SNAKE_CASE      ,      (torch.Tensor, AgentAudio)							):
																		output_types.append('''audio'''							)
												else:
																		raise ValueError(F'''Invalid output: {output}'''							)

						return output_types






@is_tool_test
class  lowerCAmelCase__   :






					def 	_snake_case    (   self		):


											"""simple docstring"""





											self.assertTrue(hasattr(self.tool				,							'''inputs'''		)		)
											self.assertTrue(hasattr(self.tool				,							'''outputs'''		)		)

											lowercase_	:     Optional[Any]													=       self.tool.inputs
											for _input in inputs:
																	if isinstance(_input				,							__SCREAMING_SNAKE_CASE		):
																							for __input in _input:
																													self.assertTrue(__input in authorized_types		)
																	else:
																							self.assertTrue(_input in authorized_types		)

											lowercase_	:     int													=       self.tool.outputs
											for _output in outputs:
																	self.assertTrue(_output in authorized_types		)






					def 	_snake_case    (   self		):


											"""simple docstring"""





											lowercase_	:     int													=       create_inputs(self.tool.inputs		)
											lowercase_	:     Tuple													=       self.tool(*__SCREAMING_SNAKE_CASE		)

											# There is a single output
											if len(self.tool.outputs		) == 1:
																	lowercase_	:     Any													=       [outputs]

											self.assertListEqual(output_types(__SCREAMING_SNAKE_CASE		)				,							self.tool.outputs		)






					def 	_snake_case    (   self		):


											"""simple docstring"""





											self.assertTrue(hasattr(self.tool				,							'''description'''		)		)
											self.assertTrue(hasattr(self.tool				,							'''default_checkpoint'''		)		)
											self.assertTrue(self.tool.description.startswith('''This is a tool that'''		)		)






					def 	_snake_case    (   self		):


											"""simple docstring"""





											lowercase_	:     int													=       create_inputs(self.tool.inputs		)
											lowercase_	:     int													=       self.tool(*__SCREAMING_SNAKE_CASE		)

											if not isinstance(__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE		):
																	lowercase_	:     Optional[Any]													=       [outputs]

											self.assertEqual(len(__SCREAMING_SNAKE_CASE		)				,							len(self.tool.outputs		)		)

											for output, output_type in zip(__SCREAMING_SNAKE_CASE				,							self.tool.outputs		):
																	lowercase_	:     Optional[int]													=       AGENT_TYPE_MAPPING[output_type]
																	self.assertTrue(isinstance(__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE		)		)






					def 	_snake_case    (   self		):


											"""simple docstring"""





											lowercase_	:     Dict													=       create_inputs(self.tool.inputs		)

											lowercase_	:     int													=       []

											for _input, input_type in zip(__SCREAMING_SNAKE_CASE				,							self.tool.inputs		):
																	if isinstance(__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE		):
																							_inputs.append([AGENT_TYPE_MAPPING[_input_type](_input		) for _input_type in input_type]		)
																	else:
																							_inputs.append(AGENT_TYPE_MAPPING[input_type](_input		)		)

        # Should not raise an error
											lowercase_	:     Optional[Any]													=       self.tool(*__SCREAMING_SNAKE_CASE		)

											if not isinstance(__SCREAMING_SNAKE_CASE				,							__SCREAMING_SNAKE_CASE		):
																	lowercase_	:     Dict													=       [outputs]

											self.assertEqual(len(__SCREAMING_SNAKE_CASE		)				,							len(self.tool.outputs		)		)



