def    __lowercase     (						lowerCamelCase					:     list	):

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

 UpperCamelCase_					:						Union[str, Any] =					[]

 def generate(lowerCamelCase					:     int  ,  lowerCamelCase					:     list	):
  if k == 1:
   res.append(tuple(arr[:]	)	)
   return

  generate(k - 1  ,  lowerCamelCase	)

  for i in range(k - 1	):
   if k % 2 == 0:  # k is even
    UpperCamelCase_, UpperCamelCase_					:						Union[str, Any] =					arr[k - 1], arr[i]
   else:  # k is odd
    UpperCamelCase_, UpperCamelCase_					:						Any =					arr[k - 1], arr[0]
   generate(k - 1  ,  lowerCamelCase	)

 generate(len(lowerCamelCase	)  ,  lowerCamelCase	)
 return res


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




from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_tf_available,
    is_torch_available,
    is_vision_available,
)


a_    					=       {
    'configuration_efficientformer': [
        'EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
        'EfficientFormerConfig',
    ]
}

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

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   a_    					=       [
       'EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
       'EfficientFormerForImageClassification',
       'EfficientFormerForImageClassificationWithTeacher',
       'EfficientFormerModel',
       'EfficientFormerPreTrainedModel',
   ]

try:
   if not is_tf_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   a_    					=       [
       'TF_EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST',
       'TFEfficientFormerForImageClassification',
       'TFEfficientFormerForImageClassificationWithTeacher',
       'TFEfficientFormerModel',
       'TFEfficientFormerPreTrainedModel',
   ]

if TYPE_CHECKING:
   from .configuration_efficientformer import EFFICIENTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP, EfficientFormerConfig

   try:
      if not is_vision_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .image_processing_efficientformer import EfficientFormerImageProcessor

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_efficientformer import (
          EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
          EfficientFormerForImageClassification,
          EfficientFormerForImageClassificationWithTeacher,
          EfficientFormerModel,
          EfficientFormerPreTrainedModel,
      )
   try:
      if not is_tf_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_tf_efficientformer import (
          TF_EFFICIENTFORMER_PRETRAINED_MODEL_ARCHIVE_LIST,
          TFEfficientFormerForImageClassification,
          TFEfficientFormerForImageClassificationWithTeacher,
          TFEfficientFormerModel,
          TFEfficientFormerPreTrainedModel,
      )

else:
   import sys

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



