




"""simple docstring"""







import operator





def      __snake_case (				_lowercase			,_lowercase = False			,_lowercase = None    ):


    """simple docstring"""







    UpperCamelCase              =	operator.lt if reverse else operator.gt
    UpperCamelCase              =	solution or []

    if not arr:
        return solution

    UpperCamelCase              =	[arr.pop(0    )]
    for i, item in enumerate(_lowercase    ):
        if _operator(_lowercase			,sublist[-1]    ):
            sublist.append(_lowercase    )
            arr.pop(_lowercase    )

    #  merging sublist into solution list
    if not solution:
        solution.extend(_lowercase    )
    else:
        while sublist:
            UpperCamelCase              =	sublist.pop(0    )
            for i, xx in enumerate(_lowercase    ):
                if not _operator(_lowercase			,_lowercase    ):
                    solution.insert(_lowercase			,_lowercase    )
                    break
            else:
                solution.append(_lowercase    )

    strand_sort(_lowercase			,_lowercase			,_lowercase    )
    return solution


if __name__ == "__main__":
  assert strand_sort([4, 3, 5, 1, 2]) == [1, 2, 3, 4, 5]
  assert strand_sort([4, 3, 5, 1, 2], reverse=True) == [5, 4, 3, 2, 1]


from typing import TYPE_CHECKING

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


a_      =     {'configuration_plbart': ['PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PLBartConfig']}

try:
			if not is_sentencepiece_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			a_      =     ['PLBartTokenizer']

try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			a_      =     [
			    'PLBART_PRETRAINED_MODEL_ARCHIVE_LIST',
			    'PLBartForCausalLM',
			    'PLBartForConditionalGeneration',
			    'PLBartForSequenceClassification',
			    'PLBartModel',
			    'PLBartPreTrainedModel',
			]


if TYPE_CHECKING:
			from .configuration_plbart import PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP, PLBartConfig

			try:
						if not is_sentencepiece_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .tokenization_plbart import PLBartTokenizer

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_plbart import (
						    PLBART_PRETRAINED_MODEL_ARCHIVE_LIST,
						    PLBartForCausalLM,
						    PLBartForConditionalGeneration,
						    PLBartForSequenceClassification,
						    PLBartModel,
						    PLBartPreTrainedModel,
						)


else:
			import sys

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