


'''simple docstring'''



__UpperCAmelCase      :Union[str, Any]			    =       "Input must be a string of 8 numbers plus letter"
__UpperCAmelCase      :Tuple			    =       "TRWAGMYFPDXBNJZSQVHLCKE"




def      _a     (						_lowercase :     str  ):





     '''simple docstring'''






     if not isinstance(_lowercase      , _lowercase  ):
          __UpperCAmelCase     :			Dict  							=      F'Expected string as input, found {type(_lowercase  ).__name__}'
          raise TypeError(_lowercase  )

     __UpperCAmelCase     :			Tuple  							=      spanish_id.replace('''-'''      , ''''''  ).upper()
     if len(_lowercase  ) != 9:
          raise ValueError(_lowercase  )

     try:
          __UpperCAmelCase     :			Optional[Any]  							=      int(spanish_id_clean[0:8]  )
          __UpperCAmelCase     :			int  							=      spanish_id_clean[8]
     except ValueError as ex:
          raise ValueError(_lowercase  ) from ex

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

     return letter == LOOKUP_LETTERS[number % 23]


if __name__ == "__main__":
 import doctest

 doctest.testmod()



'''simple docstring'''



from typing import TYPE_CHECKING

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


__UpperCAmelCase      :List[Any]			    =       {
    "configuration_lxmert": ["LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LxmertConfig"],
    "tokenization_lxmert": ["LxmertTokenizer"],
}

try:
      if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase      :List[Any]			    =       ["LxmertTokenizerFast"]

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase      :List[Any]			    =       [
          "LxmertEncoder",
          "LxmertForPreTraining",
          "LxmertForQuestionAnswering",
          "LxmertModel",
          "LxmertPreTrainedModel",
          "LxmertVisualFeatureEncoder",
          "LxmertXLayer",
      ]

try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      __UpperCAmelCase      :List[str]			    =       [
          "TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST",
          "TFLxmertForPreTraining",
          "TFLxmertMainLayer",
          "TFLxmertModel",
          "TFLxmertPreTrainedModel",
          "TFLxmertVisualFeatureEncoder",
      ]


if TYPE_CHECKING:
      from .configuration_lxmert import LXMERT_PRETRAINED_CONFIG_ARCHIVE_MAP, LxmertConfig
      from .tokenization_lxmert import LxmertTokenizer

      try:
            if not is_tokenizers_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_lxmert_fast import LxmertTokenizerFast

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_lxmert import (
                LxmertEncoder,
                LxmertForPreTraining,
                LxmertForQuestionAnswering,
                LxmertModel,
                LxmertPreTrainedModel,
                LxmertVisualFeatureEncoder,
                LxmertXLayer,
            )

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_lxmert import (
                TF_LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                TFLxmertForPreTraining,
                TFLxmertMainLayer,
                TFLxmertModel,
                TFLxmertPreTrainedModel,
                TFLxmertVisualFeatureEncoder,
            )

else:
      import sys

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