





"""simple docstring"""




class 			_UpperCAmelCase  :



      '''simple docstring'''

      def __init__(					self  ):

        """simple docstring"""

        A_  :	Optional[int]    						=  [0, 1]

      def  lowerCamelCase_      (					self ,				snake_case_  ):

        """simple docstring"""

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





def 						UpperCAmelCase__		(					):






  """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=''			, )
  A_  :	str    						=  Fibonacci()

  while True:
    A_  :	List[Any]    						=  input('>> ' )
    if prompt in {"exit", "quit"}:
      break

    try:
      A_  :	Tuple    						=  int(UpperCamelCase_ )
    except ValueError:
      print('Enter a number or \'exit\'' )
      continue

    print(fibonacci.get(UpperCamelCase_ ) )


if __name__ == "__main__":
   main()






"""simple docstring"""




# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

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


lowerCamelCase_					:						Any      = {
    'configuration_tvlt': ['TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TvltConfig'],
    'feature_extraction_tvlt': ['TvltFeatureExtractor'],
    'processing_tvlt': ['TvltProcessor'],
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase_					:						Union[str, Any]      = [
       'TVLT_PRETRAINED_MODEL_ARCHIVE_LIST',
       'TvltModel',
       'TvltForPreTraining',
       'TvltForAudioVisualClassification',
       'TvltPreTrainedModel',
   ]

try:
   if not is_vision_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   lowerCamelCase_					:						List[Any]      = ['TvltImageProcessor']


if TYPE_CHECKING:
   from .configuration_tvlt import TVLT_PRETRAINED_CONFIG_ARCHIVE_MAP, TvltConfig
   from .processing_tvlt import TvltProcessor
   from .feature_extraction_tvlt import TvltFeatureExtractor

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tvlt import (
          TVLT_PRETRAINED_MODEL_ARCHIVE_LIST,
          TvltForAudioVisualClassification,
          TvltForPreTraining,
          TvltModel,
          TvltPreTrainedModel,
      )

   try:
      if not is_vision_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .image_processing_tvlt import TvltImageProcessor


else:
   import sys

   lowerCamelCase_					:						Optional[int]      = _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)