






from packaging import version

from .import_utils import is_accelerate_available


if is_accelerate_available():
							import accelerate

def        UpperCAmelCase__		(						lowerCamelCase_       :       int				):
			if not is_accelerate_available():
						return method
			__a						:  Union[str, Any]									=     version.parse(accelerate.__version__				).base_version
			if version.parse(lowerCamelCase_				) < version.parse('0.17.0'				):
						return method

			def wrapper(self       :       str   ,  *lowerCamelCase_       :       List[str]   ,  **lowerCamelCase_       :       Union[str, Any]				):
						if hasattr(self   ,  '_hf_hook'				) and hasattr(self._hf_hook   ,  'pre_forward'				):
									self._hf_hook.pre_forward(self				)
						return method(self   ,  *lowerCamelCase_   ,  **lowerCamelCase_				)

			return wrapper











from math import sqrt

import numpy as np
from sympy import symbols

# Coefficient
# Speed of light (m/s)
_lowerCamelCase      :						str							=  299792458

# Symbols
_lowerCamelCase			,     _lowerCamelCase			,     _lowerCamelCase			,     _lowerCamelCase      :						int							=  symbols("""ct x y z""")







def SCREAMING_SNAKE_CASE							(			lowercase_		)  ->			float:



       """simple docstring"""

       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 SCREAMING_SNAKE_CASE							(			lowercase_		)  ->			float:



       """simple docstring"""

       return 1 / sqrt(1 - beta(lowercase_		) ** 2		)







def SCREAMING_SNAKE_CASE							(			lowercase_		)  ->			np.ndarray:



       """simple docstring"""

       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 SCREAMING_SNAKE_CASE							(			lowercase_					,							lowercase_ = None		)  ->			np.ndarray:



       """simple docstring"""

       if event is None:
              A__ 					=       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:
  _lowerCamelCase      :						Tuple							=  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
  _lowerCamelCase      :						int							=  {ct: c, x: 1, y: 1, z: 1}
  _lowerCamelCase      :						Any							=  [four_vector[i].subs(sub_dict) for i in range(4)]

  print(F'''\n{numerical_vector}''')


