"""simple docstring"""





def     a_					(				_lowerCAmelCase  :			int = 20					):





       '''simple docstring'''

       try:
              lowercase__      :		Optional[Any]          =     int(_lowerCAmelCase					)
       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.'					)
       lowercase__      :		str          =     0
       while 1:
              i += n * (n - 1)
              lowercase__      :		Union[str, Any]          =     0
              for j in range(2       ,			_lowerCAmelCase					):
                     if i % j != 0:
                            lowercase__      :		List[str]          =     1
                            break
              if nfound == 0:
                     if i == 0:
                            lowercase__      :		str          =     1
                     return i
       return None


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


"""simple docstring"""





from typing import TYPE_CHECKING

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


_UpperCamelCase       :						int     =   {
    "configuration_retribert": ["RETRIBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "RetriBertConfig"],
    "tokenization_retribert": ["RetriBertTokenizer"],
}

try:
       if not is_tokenizers_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _UpperCamelCase       :						Tuple     =   ["RetriBertTokenizerFast"]

try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       _UpperCamelCase       :						int     =   [
           "RETRIBERT_PRETRAINED_MODEL_ARCHIVE_LIST",
           "RetriBertModel",
           "RetriBertPreTrainedModel",
       ]


if TYPE_CHECKING:
       from .configuration_retribert import RETRIBERT_PRETRAINED_CONFIG_ARCHIVE_MAP, RetriBertConfig
       from .tokenization_retribert import RetriBertTokenizer

       try:
              if not is_tokenizers_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .tokenization_retribert_fast import RetriBertTokenizerFast

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_retribert import (
                  RETRIBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                  RetriBertModel,
                  RetriBertPreTrainedModel,
              )

else:
       import sys

       _UpperCamelCase       :						Tuple     =   _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

