



"""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,
)


A:   List[str]								=		{"configuration_mbart": ["MBART_PRETRAINED_CONFIG_ARCHIVE_MAP", "MBartConfig", "MBartOnnxConfig"]}

try:
      if not is_sentencepiece_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A:   List[Any]								=		["MBartTokenizer"]

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

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A:   List[str]								=		[
          "MBART_PRETRAINED_MODEL_ARCHIVE_LIST",
          "MBartForCausalLM",
          "MBartForConditionalGeneration",
          "MBartForQuestionAnswering",
          "MBartForSequenceClassification",
          "MBartModel",
          "MBartPreTrainedModel",
      ]

try:
      if not is_tf_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A:   Optional[int]								=		[
          "TFMBartForConditionalGeneration",
          "TFMBartModel",
          "TFMBartPreTrainedModel",
      ]

try:
      if not is_flax_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      A:   Optional[int]								=		[
          "FlaxMBartForConditionalGeneration",
          "FlaxMBartForQuestionAnswering",
          "FlaxMBartForSequenceClassification",
          "FlaxMBartModel",
          "FlaxMBartPreTrainedModel",
      ]


if TYPE_CHECKING:
      from .configuration_mbart import MBART_PRETRAINED_CONFIG_ARCHIVE_MAP, MBartConfig, MBartOnnxConfig

      try:
            if not is_sentencepiece_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_mbart import MBartTokenizer

      try:
            if not is_tokenizers_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_mbart_fast import MBartTokenizerFast

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_mbart import (
                MBART_PRETRAINED_MODEL_ARCHIVE_LIST,
                MBartForCausalLM,
                MBartForConditionalGeneration,
                MBartForQuestionAnswering,
                MBartForSequenceClassification,
                MBartModel,
                MBartPreTrainedModel,
            )

      try:
            if not is_tf_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_tf_mbart import TFMBartForConditionalGeneration, TFMBartModel, TFMBartPreTrainedModel

      try:
            if not is_flax_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_flax_mbart import (
                FlaxMBartForConditionalGeneration,
                FlaxMBartForQuestionAnswering,
                FlaxMBartForSequenceClassification,
                FlaxMBartModel,
                FlaxMBartPreTrainedModel,
            )

else:
      import sys

      A:   Tuple								=		_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





"""simple docstring"""
A:   Union[str, Any]								=		{
    0: "0",
    1: "1",
    2: "2",
    3: "3",
    4: "4",
    5: "5",
    6: "6",
    7: "7",
    8: "8",
    9: "9",
    1_0: "a",
    1_1: "b",
    1_2: "c",
    1_3: "d",
    1_4: "e",
    1_5: "f",
}

def       _snake_case						(						UpperCamelCase						:		float						):
 assert type(UpperCamelCase						) in (int, float) and decimal == int(UpperCamelCase						)
 UpperCAmelCase	:					str	=	int(UpperCamelCase						)
 UpperCAmelCase	:					Optional[int]	=	""""""
 UpperCAmelCase	:					List[str]	=	False
 if decimal < 0:
  UpperCAmelCase	:					Any	=	True
  decimal *= -1
 while decimal > 0:
  UpperCAmelCase	,		UpperCAmelCase	:					Dict	=	divmod(UpperCamelCase			,		16						)
  UpperCAmelCase	:					Union[str, Any]	=	values[remainder] + hexadecimal
 UpperCAmelCase	:					int	=	"""0x""" + hexadecimal
 if negative:
  UpperCAmelCase	:					Optional[int]	=	"""-""" + hexadecimal
 return hexadecimal


if __name__ == "__main__":
      import doctest

      doctest.testmod()
