


"""simple docstring"""


from __future__ import annotations

from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray


def _lowerCamelCase	(		_UpperCamelCase    , _UpperCamelCase    , _UpperCamelCase = False      ):

			'''simple docstring'''




			if radian_mode:
						return [magnitude * cos(lowercase_      ), magnitude * sin(lowercase_      )]
			return [magnitude * cos(radians(lowercase_      )      ), magnitude * sin(radians(lowercase_      )      )]


def _lowerCamelCase	(		_UpperCamelCase    , _UpperCamelCase    , _UpperCamelCase = 10**-1      ):

			'''simple docstring'''




			__lowerCAmelCase				    =			cross(lowercase_    , lowercase_      )
			__lowerCAmelCase				    =			sum(lowercase_      )
			return abs(lowercase_      ) < eps


if __name__ == "__main__":
	# Test to check if it works
	A     :   Optional[Any]			    =			array(
	    [
	        polar_force(718.4, 1_8_0 - 3_0),
	        polar_force(879.54, 4_5),
	        polar_force(1_0_0, -9_0),
	    ]
	)

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

	assert in_static_equilibrium(forces, location)

	# Problem 1 in image_data/2D_problems.jpg
	A     :   Union[str, Any]			    =			array(
	    [
	        polar_force(3_0 * 9.81, 1_5),
	        polar_force(2_1_5, 1_8_0 - 4_5),
	        polar_force(2_6_4, 9_0 - 3_0),
	    ]
	)

	A     :   Dict			    =			array([[0, 0], [0, 0], [0, 0]])

	assert in_static_equilibrium(forces, location)

	# Problem in image_data/2D_problems_1.jpg
	A     :   Dict			    =			array([[0, -2_0_0_0], [0, -1_2_0_0], [0, 1_5_6_0_0], [0, -1_2_4_0_0]])

	A     :   Optional[Any]			    =			array([[0, 0], [6, 0], [1_0, 0], [1_2, 0]])

	assert in_static_equilibrium(forces, location)

	import doctest

	doctest.testmod()










import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging


_lowerCamelCase	:		Any							       =   logging.get_logger(__name__)


class 				UpperCamelCase_    ( UpperCAmelCase__     ):

    '''simple docstring'''






    UpperCAmelCase__							  =      '''encoder-decoder'''
    UpperCAmelCase__							  =      True


    def __init__(			self      :	List[str]					, **UpperCAmelCase__      :	Union[str, Any])						->List[Any]:





           '''simple docstring'''

           super().__init__(**UpperCAmelCase__)
           assert (
               "encoder" in kwargs and "decoder" in kwargs
           ), "Config has to be initialized with encoder and decoder config"
           A__       =    kwargs.pop('''encoder''')
           A__       =    encoder_config.pop('''model_type''')
           A__       =    kwargs.pop('''decoder''')
           A__       =    decoder_config.pop('''model_type''')

           from ..auto.configuration_auto import AutoConfig

           A__       =    AutoConfig.for_model(UpperCAmelCase__					, **UpperCAmelCase__)
           A__       =    AutoConfig.for_model(UpperCAmelCase__					, **UpperCAmelCase__)
           A__       =    True


    @classmethod
    def        SCREAMING_SNAKE_CASE							(			cls      :	Union[str, Any]					, UpperCAmelCase__      :	PretrainedConfig					, UpperCAmelCase__      :	PretrainedConfig					, **UpperCAmelCase__      :	Union[str, Any])						->PretrainedConfig:





           '''simple docstring'''

           logger.info('''Set `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config''')
           A__       =    True
           A__       =    True

           return cls(encoder=encoder_config.to_dict()					, decoder=decoder_config.to_dict()					, **UpperCAmelCase__)





    def        SCREAMING_SNAKE_CASE							(			self      :	str)						->Optional[Any]:





           '''simple docstring'''

           A__       =    copy.deepcopy(self.__dict__)
           A__       =    self.encoder.to_dict()
           A__       =    self.decoder.to_dict()
           A__       =    self.__class__.model_type
           return output


