

'''simple docstring'''



import operator


def       snake_case   (	snake_case      : list					,		snake_case      : bool = False					,		snake_case      : list | None = None			) ->  list:


    """simple docstring"""


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

    if not arr:
        return solution

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

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

    strand_sort(snake_case					,		snake_case					,		snake_case			)
    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]








'''simple docstring'''



from typing import TYPE_CHECKING

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


_UpperCamelCase						:  str							       =				{
    "configuration_gpt_neox_japanese": ["GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoXJapaneseConfig"],
    "tokenization_gpt_neox_japanese": ["GPTNeoXJapaneseTokenizer"],
}

try:
     if not is_torch_available():
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     pass
else:
     _UpperCamelCase						:  Dict							       =				[
         "GPT_NEOX_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST",
         "GPTNeoXJapaneseForCausalLM",
         "GPTNeoXJapaneseLayer",
         "GPTNeoXJapaneseModel",
         "GPTNeoXJapanesePreTrainedModel",
     ]


if TYPE_CHECKING:
     from .configuration_gpt_neox_japanese import GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTNeoXJapaneseConfig
     from .tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer

     try:
          if not is_torch_available():
               raise OptionalDependencyNotAvailable()
     except OptionalDependencyNotAvailable:
          pass
     else:
          from .modeling_gpt_neox_japanese import (
              GPT_NEOX_JAPANESE_PRETRAINED_MODEL_ARCHIVE_LIST,
              GPTNeoXJapaneseForCausalLM,
              GPTNeoXJapaneseLayer,
              GPTNeoXJapaneseModel,
              GPTNeoXJapanesePreTrainedModel,
          )


else:
     import sys

     _UpperCamelCase						:  List[Any]							       =				_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)





