

from __future__ import annotations

from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def 						__lowerCamelCase	(       __snake_case					:		List[str],		__snake_case					:		Optional[int],		__snake_case					:		List[Any] = False	)	->							Dict:






						"""simple docstring"""





						if radian_mode:
												return [magnitude * cos(_A	), magnitude * sin(_A	)]
						return [magnitude * cos(radians(_A	)	), magnitude * sin(radians(_A	)	)]
def 						__lowerCamelCase	(       __snake_case					:		Any,		__snake_case					:		Optional[int],		__snake_case					:		Dict = 10**-1	)	->							Optional[Any]:






						"""simple docstring"""





						A__					:       NDArray[floataa]     =cross(_A,		_A	)
						A__					:       float     =sum(_A	)
						return abs(_A	) < eps


if __name__ == "__main__":
		# Test to check if it works
		__snake_case			:     Tuple										=      array(
		    [
		        polar_force(718.4, 180 - 30),
		        polar_force(879.54, 45),
		        polar_force(100, -90),
		    ]
		)

		__snake_case			:     NDArray[floataa]										=      array([[0, 0], [0, 0], [0, 0]])

		assert in_static_equilibrium(forces, location)

		# Problem 1 in image_data/2D_problems.jpg
		__snake_case			:     List[Any]										=      array(
		    [
		        polar_force(30 * 9.81, 15),
		        polar_force(215, 180 - 45),
		        polar_force(264, 90 - 30),
		    ]
		)

		__snake_case			:     Union[str, Any]										=      array([[0, 0], [0, 0], [0, 0]])

		assert in_static_equilibrium(forces, location)

		# Problem in image_data/2D_problems_1.jpg
		__snake_case			:     Optional[Any]										=      array([[0, -2000], [0, -1200], [0, 1_5600], [0, -1_2400]])

		__snake_case			:     Any										=      array([[0, 0], [6, 0], [10, 0], [12, 0]])

		assert in_static_equilibrium(forces, location)

		import doctest

		doctest.testmod()




'''simple docstring'''



from typing import Dict

from .base import GenericTensor, Pipeline



class lowerCamelCase			(  lowercase_						):



			'''simple docstring'''






			def lowercase__						(				self	:						List[str]		,      lowerCAmelCase_	:						Tuple=None		,      lowerCAmelCase_	:						Dict=None		,      lowerCAmelCase_	:						Any=None		,      **lowerCAmelCase_	:						Union[str, Any]			)      ->		Optional[Any]:





									'''simple docstring'''
									if tokenize_kwargs is None:
															A__					:       List[Any]     ={}

									if truncation is not None:
															if "truncation" in tokenize_kwargs:
																					raise ValueError(
																					    """truncation parameter defined twice (given as keyword argument as well as in tokenize_kwargs)"""			)
															A__					:       str     =truncation

									A__					:       Optional[int]     =tokenize_kwargs

									A__					:       List[Any]     ={}
									if return_tensors is not None:
															A__					:       Any     =return_tensors

									return preprocess_params, {}, postprocess_params


			def lowercase__						(				self	:						int		,      lowerCAmelCase_	:						Union[str, Any]		,      **lowerCAmelCase_	:						Dict			)      ->		Dict[str, GenericTensor]:





									'''simple docstring'''
									A__					:       List[str]     =self.framework
									A__					:       Union[str, Any]     =self.tokenizer(lowerCAmelCase_		,      return_tensors=lowerCAmelCase_		,      **lowerCAmelCase_			)
									return model_inputs


			def lowercase__						(				self	:						Optional[int]		,      lowerCAmelCase_	:						Dict			)      ->		Optional[Any]:





									'''simple docstring'''
									A__					:       Union[str, Any]     =self.model(**lowerCAmelCase_			)
									return model_outputs


			def lowercase__						(				self	:						Tuple		,      lowerCAmelCase_	:						Tuple		,      lowerCAmelCase_	:						Any=False			)      ->		List[Any]:





									'''simple docstring'''
									# [0] is the first available tensor, logits or last_hidden_state.
									if return_tensors:
															return model_outputs[0]
									if self.framework == "pt":
															return model_outputs[0].tolist()
									elif self.framework == "tf":
															return model_outputs[0].numpy().tolist()



			def __call__(				self	:						int		,      *lowerCAmelCase_	:						Any		,      **lowerCAmelCase_	:						Union[str, Any]			)      ->		List[str]:





									'''simple docstring'''
									return super().__call__(*lowerCAmelCase_		,      **lowerCAmelCase_			)

