
"""simple docstring"""






def      lowerCAmelCase__			(		__magic_name__      )						->list[list[int]]:
			__lowercase       =       []
			if len(__snake_case      ) == 1:
						return [nums.copy()]
			for _ in range(len(__snake_case      )      ):
						__lowercase       =       nums.pop(0      )
						__lowercase       =       permute(__snake_case      )
						for perm in permutations:
									perm.append(__snake_case      )
						result.extend(__snake_case      )
						nums.append(__snake_case      )
			return result



def      lowerCAmelCase__			(		__magic_name__      )						->Dict:

			def backtrack(__magic_name__      ):
						if start == len(__snake_case      ) - 1:
									output.append(nums[:]      )
						else:
									for i in range(__snake_case			,   len(__snake_case      )      ):
												__lowercase   ,					__lowercase       =       nums[i], nums[start]
												backtrack(start + 1      )
												__lowercase   ,					__lowercase       =       nums[i], nums[start]  # backtrack

			__lowercase       =       []
			backtrack(0      )
			return output


if __name__ == "__main__":
					import doctest

					# use res to print the data in permute2 function
					_lowercase							=				permutea([1, 2, 3])
					print(res)
					doctest.testmod()






'''simple docstring'''

from typing import TYPE_CHECKING

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


A_     :						Optional[Any]    							={
    '''configuration_squeezebert''': [
        '''SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
        '''SqueezeBertConfig''',
        '''SqueezeBertOnnxConfig''',
    ],
    '''tokenization_squeezebert''': ['''SqueezeBertTokenizer'''],
}

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

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 A_     :						Optional[int]    							=[
     '''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

 A_     :						List[str]    							=_LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





