

"""simple docstring"""


from typing import TYPE_CHECKING

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


if is_sentencepiece_available():
  from ..ta.tokenization_ta import TaTokenizer
else:
  from ...utils.dummy_sentencepiece_objects import TaTokenizer

a					:int    = TaTokenizer

if is_tokenizers_available():
  from ..ta.tokenization_ta_fast import TaTokenizerFast
else:
  from ...utils.dummy_tokenizers_objects import TaTokenizerFast

a					:List[Any]    = TaTokenizerFast

a					:Dict    = {"configuration_mt5": ["MT5Config", "MT5OnnxConfig"]}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a					:Any    = [
      "MT5EncoderModel",
      "MT5ForConditionalGeneration",
      "MT5ForQuestionAnswering",
      "MT5Model",
      "MT5PreTrainedModel",
      "MT5Stack",
  ]

try:
  if not is_tf_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a					:str    = ["TFMT5EncoderModel", "TFMT5ForConditionalGeneration", "TFMT5Model"]

try:
  if not is_flax_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a					:Optional[int]    = ["FlaxMT5EncoderModel", "FlaxMT5ForConditionalGeneration", "FlaxMT5Model"]


if TYPE_CHECKING:
  from .configuration_mta import MTaConfig, MTaOnnxConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_mta import (
        MTaEncoderModel,
        MTaForConditionalGeneration,
        MTaForQuestionAnswering,
        MTaModel,
        MTaPreTrainedModel,
        MTaStack,
    )

  try:
    if not is_tf_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_tf_mta import TFMTaEncoderModel, TFMTaForConditionalGeneration, TFMTaModel

  try:
    if not is_flax_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_flax_mta import FlaxMTaEncoderModel, FlaxMTaForConditionalGeneration, FlaxMTaModel

else:
  import sys

  a					:Tuple    = _LazyModule(
      __name__,
      globals()["__file__"],
      _import_structure,
      extra_objects={"MT5Tokenizer": MTaTokenizer, "MT5TokenizerFast": MTaTokenizerFast},
      module_spec=__spec__,
  )







"""simple docstring"""


a					:List[str]    = [
    (1_000, "M"),
    (900, "CM"),
    (500, "D"),
    (400, "CD"),
    (100, "C"),
    (90, "XC"),
    (50, "L"),
    (40, "XL"),
    (10, "X"),
    (9, "IX"),
    (5, "V"),
    (4, "IV"),
    (1, "I"),
]




def  _lowercase					(    __lowerCAmelCase							)       ->				int:
      SCREAMING_SNAKE_CASE__   :      Optional[Any]      		=	{"""I""": 1, """V""": 5, """X""": 10, """L""": 50, """C""": 100, """D""": 500, """M""": 1000}
      SCREAMING_SNAKE_CASE__   :      List[Any]      		=	0
      SCREAMING_SNAKE_CASE__   :      List[str]      		=	0
      while place < len(__lowerCAmelCase							):
            if (place + 1 < len(__lowerCAmelCase							)) and (vals[roman[place]] < vals[roman[place + 1]]):
                  total += vals[roman[place + 1]] - vals[roman[place]]
                  place += 2
            else:
                  total += vals[roman[place]]
                  place += 1
      return total




def  _lowercase					(    __lowerCAmelCase							)       ->				str:
      SCREAMING_SNAKE_CASE__   :      Any      		=	[]
      for arabic, roman in ROMAN:
            ((SCREAMING_SNAKE_CASE__)		,		(SCREAMING_SNAKE_CASE__))   :      List[str]      		=	divmod(__lowerCAmelCase  ,					__lowerCAmelCase							)
            result.append(roman * factor							)
            if number == 0:
                  break
      return "".join(__lowerCAmelCase							)


if __name__ == "__main__":
  import doctest

  doctest.testmod()




