



'''simple docstring'''


def 				__lowerCamelCase				(   A__    )       ->	str:






   """simple docstring"""
   return "".join([hex(A__    )[2:].zfill(2    ).upper() for byte in list(A__    )]    )







def 				__lowerCamelCase				(   A__    )       ->	bytes:






   """simple docstring"""
   # Check data validity, following RFC3548
   # https://www.ietf.org/rfc/rfc3548.txt
   if (len(A__    ) % 2) != 0:
      raise ValueError(
          'Base16 encoded data is invalid:\nData does not have an even number of hex digits.'    )
   # Check the character set - the standard base16 alphabet
   # is uppercase according to RFC3548 section 6
   if not set(A__    ) <= set('0123456789ABCDEF'    ):
      raise ValueError(
          'Base16 encoded data is invalid:\nData is not uppercase hex or it contains invalid characters.'    )
   # For every two hexadecimal digits (= a byte), turn it into an integer.
   # Then, string the result together into bytes, and return it.
   return bytes(int(data[i] + data[i + 1]    ,						16    ) for i in range(0    ,						len(A__    )    ,						2    )    )


if __name__ == "__main__":
   import doctest

   doctest.testmod()






'''simple docstring'''


from typing import TYPE_CHECKING

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


_lowerCamelCase	:       List[Any]      	=	{
    "configuration_m2m_100": ["M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP", "M2M100Config", "M2M100OnnxConfig"],
    "tokenization_m2m_100": ["M2M100Tokenizer"],
}


try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   _lowerCamelCase	:       int      	=	[
       "M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST",
       "M2M100ForConditionalGeneration",
       "M2M100Model",
       "M2M100PreTrainedModel",
   ]


if TYPE_CHECKING:
   from .configuration_mam_aaa import M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP, MaMaaaConfig, MaMaaaOnnxConfig
   from .tokenization_mam_aaa import MaMaaaTokenizer

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_mam_aaa import (
          M2M_100_PRETRAINED_MODEL_ARCHIVE_LIST,
          MaMaaaForConditionalGeneration,
          MaMaaaModel,
          MaMaaaPreTrainedModel,
      )


else:
   import sys

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

