




def 						SCREAMING_SNAKE_CASE__ (   lowercase					)  ->       list:

   if len(lowercase					) <= 1:
      return [tuple(lowercase					)]

   snake_case				:    Dict           =	[]

   def generate(lowercase						,lowercase					):
      snake_case				:    int           =	[0] * n
      res.append(tuple(lowercase					)					)

      snake_case				:    List[Any]           =	0
      while i < n:
         if c[i] < i:
            if i % 2 == 0:
               snake_case     , snake_case				:    Any           =	arr[i], arr[0]
            else:
               snake_case     , snake_case				:    Optional[Any]           =	arr[i], arr[c[i]]
            res.append(tuple(lowercase					)					)
            c[i] += 1
            snake_case				:    Any           =	0
         else:
            snake_case				:    str           =	0
            i += 1

   generate(len(lowercase					)						,lowercase					)
   return res


if __name__ == "__main__":
       lowerCamelCase	:	List[Any]				=   input('Enter numbers separated by a comma:\n').strip()
       lowerCamelCase	:	Union[str, Any]				=   [int(item) for item in user_input.split(',')]
       print(heaps(arr))











from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


lowerCamelCase	:	List[str]				=   {
    'configuration_swinv2': ['SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Swinv2Config'],
}


try:
       if not is_torch_available():
              raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
       pass
else:
       lowerCamelCase	:	Optional[Any]				=   [
           'SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST',
           'Swinv2ForImageClassification',
           'Swinv2ForMaskedImageModeling',
           'Swinv2Model',
           'Swinv2PreTrainedModel',
       ]


if TYPE_CHECKING:
       from .configuration_swinva import SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP, SwinvaConfig

       try:
              if not is_torch_available():
                     raise OptionalDependencyNotAvailable()
       except OptionalDependencyNotAvailable:
              pass
       else:
              from .modeling_swinva import (
                  SWINV2_PRETRAINED_MODEL_ARCHIVE_LIST,
                  SwinvaForImageClassification,
                  SwinvaForMaskedImageModeling,
                  SwinvaModel,
                  SwinvaPreTrainedModel,
              )


else:
       import sys

       lowerCamelCase	:	Optional[int]				=   _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)





