


'''simple docstring'''






a_   :      Optional[int]				    =      "Input must be a string of 8 numbers plus letter"
a_   :      List[Any]				    =      "TRWAGMYFPDXBNJZSQVHLCKE"






def 		_A			(lowerCAmelCase__					:str						)				->					bool:




     '''simple docstring'''



     if not isinstance(lowerCAmelCase__			,  lowerCAmelCase__						):
          _a      =							f'Expected string as input, found {type(lowerCAmelCase__						).__name__}'
          raise TypeError(lowerCAmelCase__						)

     _a      =							spanish_id.replace('-'			,  ''						).upper()
     if len(lowerCAmelCase__						) != 9:
          raise ValueError(lowerCAmelCase__						)

     try:
          _a      =							int(spanish_id_clean[0:8]						)
          _a      =							spanish_id_clean[8]
     except ValueError as ex:
          raise ValueError(lowerCAmelCase__						) from ex

     if letter.isdigit():
          raise ValueError(lowerCAmelCase__						)

     return letter == LOOKUP_LETTERS[number % 23]


if __name__ == "__main__":
     import doctest

     doctest.testmod()





'''simple docstring'''






from typing import TYPE_CHECKING

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


a_   :      int				    =      {
    "configuration_gpt_neox_japanese": ["GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoXJapaneseConfig"],
    "tokenization_gpt_neox_japanese": ["GPTNeoXJapaneseTokenizer"],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 a_   :      List[str]				    =      [
     "GPT_NEOX_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST",
     "GPTNeoXJapaneseForCausalLM",
     "GPTNeoXJapaneseLayer",
     "GPTNeoXJapaneseModel",
     "GPTNeoXJapanesePreTrainedModel",
 ]


if TYPE_CHECKING:
 from .configuration_gpt_neox_japanese import GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXJapaneseConfig
 from .tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_gpt_neox_japanese import (
      GPT_NEOX_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST,
      GPTNeoXJapaneseForCausalLM,
      GPTNeoXJapaneseLayer,
      GPTNeoXJapaneseModel,
      GPTNeoXJapanesePreTrainedModel,
  )


else:
 import sys

 a_   :      int				    =      _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)

