





'''simple docstring'''

def     __magic_name__							(				__UpperCAmelCase   )    ->       int:

   '''simple docstring'''







   if not isinstance(__lowercase				,						__lowercase   ):
      raise TypeError("""only integers accepted as input"""   )
   else:
      __SCREAMING_SNAKE_CASE   				=							str(abs(__lowercase   )   )
      __SCREAMING_SNAKE_CASE   				=							[list(__lowercase   ) for char in range(len(__lowercase   )   )]
      for index in range(len(__lowercase   )   ):
         num_transpositions[index].pop(__lowercase   )
      return max(
          int("""""".join(list(__lowercase   )   )   ) for transposition in num_transpositions   )


if __name__ == "__main__":
    __import__("doctest").testmod()













from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__a   :							Any						= {
    "configuration_time_series_transformer": [
        "TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
        "TimeSeriesTransformerConfig",
    ],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  __a   :							Dict						= [
      "TIME_SERIES_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST",
      "TimeSeriesTransformerForPrediction",
      "TimeSeriesTransformerModel",
      "TimeSeriesTransformerPreTrainedModel",
  ]


if TYPE_CHECKING:
  from .configuration_time_series_transformer import (
      TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP,
      TimeSeriesTransformerConfig,
  )

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_time_series_transformer import (
        TIME_SERIES_TRANSFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
        TimeSeriesTransformerForPrediction,
        TimeSeriesTransformerModel,
        TimeSeriesTransformerPreTrainedModel,
    )

else:
  import sys

  __a   :							str						= _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)




