






"""simple docstring"""





from math import sqrt

import numpy as np
from sympy import symbols

# Coefficient
# Speed of light (m/s)
UpperCamelCase_	:				int										= 299792458

# Symbols
UpperCamelCase_							,							UpperCamelCase_							,							UpperCamelCase_							,							UpperCamelCase_	:				str										= symbols("""ct x y z""")



def     __lowercase					(    a :				float )					->					float:
      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     __lowercase					(    a :				float )					->					float:
      return 1 / sqrt(1 - beta(a ) ** 2 )



def     __lowercase					(    a :				float )					->					np.ndarray:
      return np.array(
          [
              [gamma(a ), -gamma(a ) * beta(a ), 0, 0],
              [-gamma(a ) * beta(a ), gamma(a ), 0, 0],
              [0, 0, 1, 0],
              [0, 0, 0, 1],
          ] )



def     __lowercase					(    a :				float       ,		a :				np.ndarray | None = None )					->					np.ndarray:
      # Ensure event is not empty
      if event is None:
            __snake_case      :    int  			=np.array([ct, x, y, z] )  # Symbolic four vector
      else:
            event[0] *= c  # x0 is ct (speed of light * time)

      return transformation_matrix(a ) @ event


if __name__ == "__main__":
    import doctest

    doctest.testmod()

    # Example of symbolic vector:
    UpperCamelCase_	:				List[str]										= transform(29979245)
    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}''')










"""simple docstring"""





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


UpperCamelCase_	:				Optional[int]										= logging.get_logger(__name__)

UpperCamelCase_	:				Union[str, Any]										= {"""ctrl""": """https://huggingface.co/ctrl/resolve/main/config.json"""}


class      _lowercase (     lowerCAmelCase						):
      _a   :     str								=   '''ctrl'''
      _a   :     Optional[int]								=   ['''past_key_values''']
      _a   :     List[Any]								=   {
          '''max_position_embeddings''': '''n_positions''',
          '''hidden_size''': '''n_embd''',
          '''num_attention_heads''': '''n_head''',
          '''num_hidden_layers''': '''n_layer''',
      }


      def __init__(    self				:	str							,   a				:	Optional[int]=2_4_6_5_3_4							,   a				:	Optional[int]=2_5_6							,   a				:	Optional[int]=1_2_8_0							,   a				:	Any=8_1_9_2							,   a				:	int=4_8							,   a				:	Optional[Any]=1_6							,   a				:	str=0.1							,   a				:	str=0.1							,   a				:	Any=1e-6							,   a				:	Optional[int]=0.0_2							,   a				:	int=True							,   **a				:	str							,   ):





            """simple docstring"""







            __snake_case      :    Tuple  			=vocab_size
            __snake_case      :    Optional[Any]  			=n_positions
            __snake_case      :    List[Any]  			=n_embd
            __snake_case      :    Any  			=n_layer
            __snake_case      :    Any  			=n_head
            __snake_case      :    str  			=dff
            __snake_case      :    List[str]  			=resid_pdrop
            __snake_case      :    str  			=embd_pdrop
            __snake_case      :    Union[str, Any]  			=layer_norm_epsilon
            __snake_case      :    List[Any]  			=initializer_range

            __snake_case      :    Any  			=use_cache

            super().__init__(**a						)


