

def    UpperCamelCase(					lowercase_ = 20							)	->				int:





  '''simple docstring'''





  try:
    snake_case_       						=      int(lowercase_							)
  except (TypeError, ValueError):
    raise TypeError("""Parameter n must be int or castable to int."""							)
  if n <= 0:
    raise ValueError("""Parameter n must be greater than or equal to one."""							)
  snake_case_       						=      0
  while 1:
    i += n * (n - 1)
    snake_case_       						=      0
    for j in range(2			,					lowercase_							):
      if i % j != 0:
        snake_case_       						=      1
        break
    if nfound == 0:
      if i == 0:
        snake_case_       						=      1
      return i
  return None


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


from typing import TYPE_CHECKING

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


lowerCamelCase_    =					{
    '''configuration_mpnet''': ['''MPNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MPNetConfig'''],
    '''tokenization_mpnet''': ['''MPNetTokenizer'''],
}

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

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase_    =					[
        '''MPNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''MPNetForMaskedLM''',
        '''MPNetForMultipleChoice''',
        '''MPNetForQuestionAnswering''',
        '''MPNetForSequenceClassification''',
        '''MPNetForTokenClassification''',
        '''MPNetLayer''',
        '''MPNetModel''',
        '''MPNetPreTrainedModel''',
    ]

try:
    if not is_tf_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    lowerCamelCase_    =					[
        '''TF_MPNET_PRETRAINED_MODEL_ARCHIVE_LIST''',
        '''TFMPNetEmbeddings''',
        '''TFMPNetForMaskedLM''',
        '''TFMPNetForMultipleChoice''',
        '''TFMPNetForQuestionAnswering''',
        '''TFMPNetForSequenceClassification''',
        '''TFMPNetForTokenClassification''',
        '''TFMPNetMainLayer''',
        '''TFMPNetModel''',
        '''TFMPNetPreTrainedModel''',
    ]


if TYPE_CHECKING:
    from .configuration_mpnet import MPNET_PRETRAINED_CONFIG_ARCHIVE_MAP, MPNetConfig
    from .tokenization_mpnet import MPNetTokenizer

    try:
        if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .tokenization_mpnet_fast import MPNetTokenizerFast

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_mpnet import (
            MPNET_PRETRAINED_MODEL_ARCHIVE_LIST,
            MPNetForMaskedLM,
            MPNetForMultipleChoice,
            MPNetForQuestionAnswering,
            MPNetForSequenceClassification,
            MPNetForTokenClassification,
            MPNetLayer,
            MPNetModel,
            MPNetPreTrainedModel,
        )

    try:
        if not is_tf_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_tf_mpnet import (
            TF_MPNET_PRETRAINED_MODEL_ARCHIVE_LIST,
            TFMPNetEmbeddings,
            TFMPNetForMaskedLM,
            TFMPNetForMultipleChoice,
            TFMPNetForQuestionAnswering,
            TFMPNetForSequenceClassification,
            TFMPNetForTokenClassification,
            TFMPNetMainLayer,
            TFMPNetModel,
            TFMPNetPreTrainedModel,
        )

else:
    import sys

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