SCREAMING_SNAKE_CASE			:						Union[str, Any]				  =		tuple[float, float, float]
SCREAMING_SNAKE_CASE			:						Dict				  =		tuple[float, float, float]



def 	__A		(      _A				,					_A       ):



 """simple docstring"""


 __a							=	end_pointa[0] - end_pointa[0]
 __a							=	end_pointa[1] - end_pointa[1]
 __a							=	end_pointa[2] - end_pointa[2]
 return (x, y, z)



def 	__A		(      _A				,					_A       ):



 """simple docstring"""


 __a							=	ab[1] * ac[2] - ab[2] * ac[1]  # *i
 __a							=	(ab[0] * ac[2] - ab[2] * ac[0]) * -1  # *j
 __a							=	ab[0] * ac[1] - ab[1] * ac[0]  # *k
 return (x, y, z)



def 	__A		(      _A				,					_A       ):



 """simple docstring"""


 return tuple(round(_A				,					_A       ) for x in vector       ) == (0, 0, 0)






def 	__A		(      _A				,					_A				,					_A				,					_A = 10       ):



 """simple docstring"""


 __a							=	create_vector(_A				,					_A       )
 __a							=	create_vector(_A				,					_A       )
 return is_zero_vector(get_ad_vectors_cross(_A				,					_A       )				,					_A       )



from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig


SCREAMING_SNAKE_CASE			:						int				  =		logging.get_logger(__name__)

SCREAMING_SNAKE_CASE			:						Any				  =		"""T5Config"""
class  A_			(							a_			):
  _SCREAMING_SNAKE_CASE     					=      """mt5"""
  _SCREAMING_SNAKE_CASE     					=      MTaConfig
class  A_			(							a_			):
  _SCREAMING_SNAKE_CASE     					=      """mt5"""
  _SCREAMING_SNAKE_CASE     					=      MTaConfig
class  A_			(							a_			):
  _SCREAMING_SNAKE_CASE     					=      """mt5"""
  _SCREAMING_SNAKE_CASE     					=      MTaConfig


