from math import sqrt

import numpy as np
from sympy import symbols

# Coefficient
# Speed of light (m/s)
a_							=      299792458

# Symbols
a_							=      symbols("""ct x y z""")




def       __lowerCAmelCase      (						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       __lowerCAmelCase      (						A_   : float					)    ->  float:
  return 1 / sqrt(1 - beta(UpperCAmelCase__					) ** 2					)




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




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

  return transformation_matrix(UpperCAmelCase__					) @ event


if __name__ == "__main__":
   import doctest

   doctest.testmod()

   # Example of symbolic vector:
   a_							=      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
   a_							=      {ct: c, x: 1, y: 1, z: 1}
   a_							=      [four_vector[i].subs(sub_dict) for i in range(4)]

   print(F"\n{numerical_vector}")




from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


a_							=      {
    """configuration_altclip""": [
        """ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """AltCLIPConfig""",
        """AltCLIPTextConfig""",
        """AltCLIPVisionConfig""",
    ],
    """processing_altclip""": ["""AltCLIPProcessor"""],
}

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       a_							=      [
           """ALTCLIP_PRETRAINED_MODEL_ARCHIVE_LIST""",
           """AltCLIPPreTrainedModel""",
           """AltCLIPModel""",
           """AltCLIPTextModel""",
           """AltCLIPVisionModel""",
       ]


if TYPE_CHECKING:
       from .configuration_altclip import (
           ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP,
           AltCLIPConfig,
           AltCLIPTextConfig,
           AltCLIPVisionConfig,
       )
       from .processing_altclip import AltCLIPProcessor

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_altclip import (
                  ALTCLIP_PRETRAINED_MODEL_ARCHIVE_LIST,
                  AltCLIPModel,
                  AltCLIPPreTrainedModel,
                  AltCLIPTextModel,
                  AltCLIPVisionModel,
              )


else:
       import sys

       a_							=      _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)



