

from typing import TYPE_CHECKING

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


__snake_case             =	{
    '''configuration_splinter''': ['''SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''SplinterConfig'''],
    '''tokenization_splinter''': ['''SplinterTokenizer'''],
}

try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __snake_case             =	['''SplinterTokenizerFast''']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __snake_case             =	[
        '''SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''SplinterForQuestionAnswering''',
        '''SplinterForPreTraining''',
        '''SplinterLayer''',
        '''SplinterModel''',
        '''SplinterPreTrainedModel''',
    ]


if TYPE_CHECKING:
    from .configuration_splinter import SPLINTER_PRETRAINED_CONFIG_ARCHIVE_MAP, SplinterConfig
    from .tokenization_splinter import SplinterTokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_splinter_fast import SplinterTokenizerFast

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_splinter import (
            SPLINTER_PRETRAINED_MODEL_ARCHIVE_LIST,
            SplinterForPreTraining,
            SplinterForQuestionAnswering,
            SplinterLayer,
            SplinterModel,
            SplinterPreTrainedModel,
        )


else:
    import sys

    __snake_case             =	_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)






def 		_A		(		_lowercase   )				->   bool:


     """simple docstring"""


     if not isinstance(_lowercase				,     _lowercase   ):
          raise ValueError('Input series is not valid, valid series - [1, 2/3, 2]'   )
     if len(_lowercase   ) == 0:
          raise ValueError('Input list must be a non empty list'   )
     if len(_lowercase   ) == 1 and series[0] != 0:
          return True
     __UpperCamelCase   = []
     __UpperCamelCase   = len(_lowercase   )
     for i in range(0				,     _lowercase   ):
          if series[i] == 0:
               raise ValueError('Input series cannot have 0 as an element'   )
          rec_series.append(1 / series[i]   )
     __UpperCamelCase   = rec_series[1] - rec_series[0]
     for index in range(2				,     _lowercase   ):
          if rec_series[index] - rec_series[index - 1] != common_diff:
               return False
     return True






def 		_A		(		_lowercase   )				->   float:


     """simple docstring"""


     if not isinstance(_lowercase				,     _lowercase   ):
          raise ValueError('Input series is not valid, valid series - [2, 4, 6]'   )
     if len(_lowercase   ) == 0:
          raise ValueError('Input list must be a non empty list'   )
     __UpperCamelCase   = 0
     for val in series:
          answer += 1 / val
     return len(_lowercase   ) / answer


if __name__ == "__main__":
    import doctest

    doctest.testmod()


