





import operator






def       _A  (      lowerCamelCase							, lowerCamelCase = False							, lowerCamelCase = None   ):
   a__	:						List[str]      		=  operator.lt if reverse else operator.gt
   a__	:						str      		=  solution or []

   if not arr:
      return solution

   a__	:						Union[str, Any]      		=  [arr.pop(0   )]
   for i, item in enumerate(lowerCamelCase   ):
      if _operator(lowerCamelCase							, sublist[-1]   ):
         sublist.append(lowerCamelCase   )
         arr.pop(lowerCamelCase   )

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

   strand_sort(lowerCamelCase							, lowerCamelCase							, lowerCamelCase   )
   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]








# Copyright 2022 The HuggingFace Team and The OpenBMB Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


SCREAMING_SNAKE_CASE__       :			int			      =						{
    """configuration_cpmant""": ["""CPMANT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CpmAntConfig"""],
    """tokenization_cpmant""": ["""CpmAntTokenizer"""],
}

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  SCREAMING_SNAKE_CASE__       :			List[str]			      =						[
      """CPMANT_PRETRAINED_MODEL_ARCHIVE_LIST""",
      """CpmAntForCausalLM""",
      """CpmAntModel""",
      """CpmAntPreTrainedModel""",
  ]


if TYPE_CHECKING:
  from .configuration_cpmant import CPMANT_PRETRAINED_CONFIG_ARCHIVE_MAP, CpmAntConfig
  from .tokenization_cpmant import CpmAntTokenizer

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_cpmant import (
        CPMANT_PRETRAINED_MODEL_ARCHIVE_LIST,
        CpmAntForCausalLM,
        CpmAntModel,
        CpmAntPreTrainedModel,
    )


else:
  import sys

  SCREAMING_SNAKE_CASE__       :			Union[str, Any]			      =						_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

