


from typing import TYPE_CHECKING

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


__UpperCamelCase    :						List[str]     =							{
    'configuration_longformer': [
        'LONGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'LongformerConfig',
        'LongformerOnnxConfig',
    ],
    'tokenization_longformer': ['LongformerTokenizer'],
}

try:
    if not is_tokenizers_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __UpperCamelCase    :						str     =							['LongformerTokenizerFast']

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __UpperCamelCase    :						List[str]     =							[
        'LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
        'LongformerForMaskedLM',
        'LongformerForMultipleChoice',
        'LongformerForQuestionAnswering',
        'LongformerForSequenceClassification',
        'LongformerForTokenClassification',
        'LongformerModel',
        'LongformerPreTrainedModel',
        'LongformerSelfAttention',
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __UpperCamelCase    :						List[Any]     =							[
        'TF_LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
        'TFLongformerForMaskedLM',
        'TFLongformerForMultipleChoice',
        'TFLongformerForQuestionAnswering',
        'TFLongformerForSequenceClassification',
        'TFLongformerForTokenClassification',
        'TFLongformerModel',
        'TFLongformerPreTrainedModel',
        'TFLongformerSelfAttention',
    ]


if TYPE_CHECKING:
    from .configuration_longformer import (
        LONGFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
        LongformerConfig,
        LongformerOnnxConfig,
    )
    from .tokenization_longformer import LongformerTokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_longformer_fast import LongformerTokenizerFast

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_longformer import (
            LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
            LongformerForMaskedLM,
            LongformerForMultipleChoice,
            LongformerForQuestionAnswering,
            LongformerForSequenceClassification,
            LongformerForTokenClassification,
            LongformerModel,
            LongformerPreTrainedModel,
            LongformerSelfAttention,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_longformer import (
            TF_LONGFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFLongformerForMaskedLM,
            TFLongformerForMultipleChoice,
            TFLongformerForQuestionAnswering,
            TFLongformerForSequenceClassification,
            TFLongformerForTokenClassification,
            TFLongformerModel,
            TFLongformerPreTrainedModel,
            TFLongformerSelfAttention,
        )

else:
    import sys

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







def   _UpperCAmelCase       (     UpperCAmelCase      :			int = 4_000_000      ):
      """simple docstring"""




      __lowerCamelCase     :      Union[str, Any]       						=						[0, 1]
      __lowerCamelCase     :      Dict       						=						0
      while fib[i] <= n:
            fib.append(fib[i] + fib[i + 1]      )
            if fib[i + 2] > n:
                  break
            i += 1
      __lowerCamelCase     :      Any       						=						0
      for j in range(len(UpperCAmelCase      ) - 1      ):
            if fib[j] % 2 == 0:
                  total += fib[j]

      return total


if __name__ == "__main__":
    print(F'''{solution() = }''')



