




'''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,
)


UpperCAmelCase_ 		=      {"configuration_mbart": ["MBART_PRETRAINED_CONFIG_ARCHIVE_MAP", "MBartConfig", "MBartOnnxConfig"]}

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

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

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

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

try:
  if not is_flax_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  UpperCAmelCase_ 		=      [
      "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

  UpperCAmelCase_ 		=      _LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)









'''simple docstring'''


def 						SCREAMING_SNAKE_CASE       (      a_	:							int = 10**12			):
  __a			=					1
  __a			=					0

  __a			=					1
  __a			=					1

  while numerator <= 2 * min_total - 1:
    prev_numerator += 2 * numerator
    numerator += 2 * prev_numerator

    prev_denominator += 2 * denominator
    denominator += 2 * prev_denominator

  return (denominator + 1) // 2


if __name__ == "__main__":
  print(f"""{solution() = }""")



