


from math import sqrt

import numpy as np
from sympy import symbols

# Coefficient
# Speed of light (m/s)
__UpperCamelCase				:  List[str]      					=							2_9979_2458

# Symbols
__UpperCamelCase					,					__UpperCamelCase					,					__UpperCamelCase					,					__UpperCamelCase				:  Union[str, Any]      					=							symbols('ct x y z')
def      snake_case_						( __lowercase       ):
   if velocity > c:
      raise ValueError('''Speed must not exceed light speed 299,792,458 [m/s]!'''       )
   elif velocity < 1:
      # Usually the speed should be much higher than 1 (c order of magnitude)
      raise ValueError('''Speed must be greater than or equal to 1!'''       )

   return velocity / c
def      snake_case_						( __lowercase       ):
   return 1 / sqrt(1 - beta(__lowercase       ) ** 2       )
def      snake_case_						( __lowercase       ):
   return np.array(
       [
           [gamma(__lowercase       ), -gamma(__lowercase       ) * beta(__lowercase       ), 0, 0],
           [-gamma(__lowercase       ) * beta(__lowercase       ), gamma(__lowercase       ), 0, 0],
           [0, 0, 1, 0],
           [0, 0, 0, 1],
       ]       )
def      snake_case_						( __lowercase			,       __lowercase = None       ):
   # Ensure event is not empty
   if event is None:
      UpperCAmelCase_							:      Optional[int]						=   np.array([ct, x, y, z]       )  # Symbolic four vector
   else:
      event[0] *= c  # x0 is ct (speed of light * time)

   return transformation_matrix(__lowercase       ) @ event


if __name__ == "__main__":
       import doctest

       doctest.testmod()

       # Example of symbolic vector:
       __UpperCamelCase				:  List[Any]      					=							transform(2997_9245)
       print('Example of four vector: ')
       print(F'ct\' = {four_vector[0]}')
       print(F'x\' = {four_vector[1]}')
       print(F'y\' = {four_vector[2]}')
       print(F'z\' = {four_vector[3]}')

       # Substitute symbols with numerical values
       __UpperCamelCase				:  Any      					=							{ct: c, x: 1, y: 1, z: 1}
       __UpperCamelCase				:  List[str]      					=							[four_vector[i].subs(sub_dict) for i in range(4)]

       print(F'\n{numerical_vector}')



import copy

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


__UpperCamelCase				:  Tuple      					=							logging.get_logger(__name__)





class  lowerCAmelCase__(    snake_case__						):






    '''simple docstring'''





    A_  :     Union[str, Any]			= 'encoder-decoder'
    A_  :     Optional[int]			= True





    def __init__(	self				:   Dict       ,   **__snake_case				:   Union[str, Any]	):





       '''simple docstring'''
       super().__init__(**__snake_case	)
       assert (
           "encoder" in kwargs and "decoder" in kwargs
       ), "Config has to be initialized with encoder and decoder config"
       UpperCAmelCase_							:      int						=   kwargs.pop('''encoder'''	)
       UpperCAmelCase_							:      List[Any]						=   encoder_config.pop('''model_type'''	)
       UpperCAmelCase_							:      int						=   kwargs.pop('''decoder'''	)
       UpperCAmelCase_							:      Union[str, Any]						=   decoder_config.pop('''model_type'''	)

       from ..auto.configuration_auto import AutoConfig

       UpperCAmelCase_							:      Optional[int]						=   AutoConfig.for_model(__snake_case       ,   **__snake_case	)
       UpperCAmelCase_							:      Any						=   AutoConfig.for_model(__snake_case       ,   **__snake_case	)
       UpperCAmelCase_							:      List[Any]						=   True





    @classmethod
    def 					_lowerCamelCase (	cls				:   Optional[Any]       ,   __snake_case				:   PretrainedConfig       ,   __snake_case				:   PretrainedConfig       ,   **__snake_case				:   Union[str, Any]	):





       '''simple docstring'''
       logger.info('''Set `config.is_decoder=True` and `config.add_cross_attention=True` for decoder_config'''	)
       UpperCAmelCase_							:      Dict						=   True
       UpperCAmelCase_							:      str						=   True

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





    def 					_lowerCamelCase (	self				:   Dict	):





       '''simple docstring'''
       UpperCAmelCase_							:      int						=   copy.deepcopy(self.__dict__	)
       UpperCAmelCase_							:      Tuple						=   self.encoder.to_dict()
       UpperCAmelCase_							:      Tuple						=   self.decoder.to_dict()
       UpperCAmelCase_							:      Tuple						=   self.__class__.model_type
       return output