class SCREAMING_SNAKE_CASE_		:







   def __init__(    self	:	Dict							):





    """simple docstring"""


    UpperCamelCase      =			[0, 1]







   def 	lowerCamelCase_  (    self	:	int      ,      lowerCamelCase_	:	int							):





    """simple docstring"""


    if (difference := index - (len(self.sequence							) - 2)) >= 1:
     for _ in range(lowerCamelCase_							):
      self.sequence.append(self.sequence[-1] + self.sequence[-2]							)
    return self.sequence[:index]





def  lowercase(  )		->  None:







 '''simple docstring'''
 print(
     """Fibonacci Series Using Dynamic Programming\n"""       ,				"""Enter the index of the Fibonacci number you want to calculate """       ,				"""in the prompt below. (To exit enter exit or Ctrl-C)\n"""       ,				sep=""""""       ,				)
 UpperCamelCase      =			Fibonacci()

 while True:
  UpperCamelCase      =			input(""">> """					)
  if prompt in {"exit", "quit"}:
   break

  try:
   UpperCamelCase      =			int(UpperCamelCase_					)
  except ValueError:
   print("""Enter a number or 'exit'"""					)
   continue

  print(fibonacci.get(UpperCamelCase_					)					)


if __name__ == "__main__":
     main()

from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_torch_available,
)


_SCREAMING_SNAKE_CASE   		=			{
    """configuration_align""": [
        """ALIGN_PRETRAINED_CONFIG_ARCHIVE_MAP""",
        """AlignConfig""",
        """AlignTextConfig""",
        """AlignVisionConfig""",
    ],
    """processing_align""": ["""AlignProcessor"""],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _SCREAMING_SNAKE_CASE   		=			[
         """ALIGN_PRETRAINED_MODEL_ARCHIVE_LIST""",
         """AlignModel""",
         """AlignPreTrainedModel""",
         """AlignTextModel""",
         """AlignVisionModel""",
     ]

if TYPE_CHECKING:
     from .configuration_align import (
         ALIGN_PRETRAINED_CONFIG_ARCHIVE_MAP,
         AlignConfig,
         AlignTextConfig,
         AlignVisionConfig,
     )
     from .processing_align import AlignProcessor

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_align import (
              ALIGN_PRETRAINED_MODEL_ARCHIVE_LIST,
              AlignModel,
              AlignPreTrainedModel,
              AlignTextModel,
              AlignVisionModel,
          )

else:
     import sys

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