





from typing import TYPE_CHECKING

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


lowercase_						=	{
    '''configuration_squeezebert''': [
        '''SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''SqueezeBertConfig''',
        '''SqueezeBertOnnxConfig''',
    ],
    '''tokenization_squeezebert''': ['''SqueezeBertTokenizer'''],
}

try:
      if not is_tokenizers_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase_						=	['''SqueezeBertTokenizerFast''']

try:
      if not is_torch_available():
            raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
      pass
else:
      lowercase_						=	[
          '''SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST''',
          '''SqueezeBertForMaskedLM''',
          '''SqueezeBertForMultipleChoice''',
          '''SqueezeBertForQuestionAnswering''',
          '''SqueezeBertForSequenceClassification''',
          '''SqueezeBertForTokenClassification''',
          '''SqueezeBertModel''',
          '''SqueezeBertModule''',
          '''SqueezeBertPreTrainedModel''',
      ]


if TYPE_CHECKING:
      from .configuration_squeezebert import (
          SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
          SqueezeBertConfig,
          SqueezeBertOnnxConfig,
      )
      from .tokenization_squeezebert import SqueezeBertTokenizer

      try:
            if not is_tokenizers_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .tokenization_squeezebert_fast import SqueezeBertTokenizerFast

      try:
            if not is_torch_available():
                  raise OptionalDependencyNotAvailable()
      except OptionalDependencyNotAvailable:
            pass
      else:
            from .modeling_squeezebert import (
                SQUEEZEBERT_PRETRAINED_MODEL_ARCHIVE_LIST,
                SqueezeBertForMaskedLM,
                SqueezeBertForMultipleChoice,
                SqueezeBertForQuestionAnswering,
                SqueezeBertForSequenceClassification,
                SqueezeBertForTokenClassification,
                SqueezeBertModel,
                SqueezeBertModule,
                SqueezeBertPreTrainedModel,
            )

else:
      import sys

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









def     __UpperCamelCase						(_SCREAMING_SNAKE_CASE	)       ->     List[Any]:
  stooge(_SCREAMING_SNAKE_CASE	,		0	,		len(_SCREAMING_SNAKE_CASE	) - 1	)
  return arr




def     __UpperCamelCase						(_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE	)       ->     int:
  if i >= h:
    return

  # If first element is smaller than the last then swap them
  if arr[i] > arr[h]:
    lowercase__    ,					lowercase__			    =						arr[h], arr[i]

  # If there are more than 2 elements in the array
  if h - i + 1 > 2:
    lowercase__			    =						(int)((h - i + 1) / 3	)

    # Recursively sort first 2/3 elements
    stooge(_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE	,		(h - t)	)

    # Recursively sort last 2/3 elements
    stooge(_SCREAMING_SNAKE_CASE	,		i + t	,		(_SCREAMING_SNAKE_CASE)	)

    # Recursively sort first 2/3 elements
    stooge(_SCREAMING_SNAKE_CASE	,		_SCREAMING_SNAKE_CASE	,		(h - t)	)


if __name__ == "__main__":
      lowercase_					     =	input("""Enter numbers separated by a comma:\n""").strip()
      lowercase_					     =	[int(item) for item in user_input.split(""",""")]
      print(stooge_sort(unsorted))


