






'''simple docstring'''
def 	_a(					UpperCamelCase__			:  Optional[Any]							):




      '''simple docstring'''






      SCREAMING_SNAKE_CASE__       :			List[str]													=len(UpperCamelCase__							)
      while cur > 1:
            # Find the maximum number in arr
            SCREAMING_SNAKE_CASE__       :			Optional[int]													=arr.index(max(arr[0:cur]							)							)
            # Reverse from 0 to mi
            SCREAMING_SNAKE_CASE__       :			Dict													=arr[mi::-1] + arr[mi + 1 : len(UpperCamelCase__							)]
            # Reverse whole list
            SCREAMING_SNAKE_CASE__       :			Tuple													=arr[cur - 1 :: -1] + arr[cur : len(UpperCamelCase__							)]
            cur -= 1
      return arr


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







'''simple docstring'''
from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


a_					=	{
    'configuration_megatron_bert': ['MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegatronBertConfig'],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  a_					=	[
      'MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST',
      'MegatronBertForCausalLM',
      'MegatronBertForMaskedLM',
      'MegatronBertForMultipleChoice',
      'MegatronBertForNextSentencePrediction',
      'MegatronBertForPreTraining',
      'MegatronBertForQuestionAnswering',
      'MegatronBertForSequenceClassification',
      'MegatronBertForTokenClassification',
      'MegatronBertModel',
      'MegatronBertPreTrainedModel',
  ]

if TYPE_CHECKING:
  from .configuration_megatron_bert import MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP, MegatronBertConfig

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_megatron_bert import (
        MEGATRON_BERT_PRETRAINED_MODEL_ARCHIVE_LIST,
        MegatronBertForCausalLM,
        MegatronBertForMaskedLM,
        MegatronBertForMultipleChoice,
        MegatronBertForNextSentencePrediction,
        MegatronBertForPreTraining,
        MegatronBertForQuestionAnswering,
        MegatronBertForSequenceClassification,
        MegatronBertForTokenClassification,
        MegatronBertModel,
        MegatronBertPreTrainedModel,
    )

else:
  import sys

  a_					=	_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)