def       _snake_case	(   lowerCAmelCase							:   list	):
		"""simple docstring"""







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

		SCREAMING_SNAKE_CASE_  :		Tuple				      =    []

		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
								SCREAMING_SNAKE_CASE_      ,    SCREAMING_SNAKE_CASE_  :		Optional[int]				      =    arr[k - 1], arr[i]
						else:  # k is odd
								SCREAMING_SNAKE_CASE_      ,    SCREAMING_SNAKE_CASE_  :		str				      =    arr[k - 1], arr[0]
						generate(k - 1   , lowerCAmelCase	)

		generate(len(lowerCAmelCase	)   , lowerCAmelCase	)
		return res


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

from typing import TYPE_CHECKING

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


__lowerCamelCase					:	Dict       =  {'''configuration_vit_mae''': ['''VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMAEConfig''']}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCamelCase					:	Any       =  [
		    '''VIT_MAE_PRETRAINED_MODEL_ARCHIVE_LIST''',
		    '''ViTMAEForPreTraining''',
		    '''ViTMAELayer''',
		    '''ViTMAEModel''',
		    '''ViTMAEPreTrainedModel''',
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		__lowerCamelCase					:	Optional[Any]       =  [
		    '''TFViTMAEForPreTraining''',
		    '''TFViTMAEModel''',
		    '''TFViTMAEPreTrainedModel''',
		]

if TYPE_CHECKING:
		from .configuration_vit_mae import VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTMAEConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_vit_mae import (
				    VIT_MAE_PRETRAINED_MODEL_ARCHIVE_LIST,
				    ViTMAEForPreTraining,
				    ViTMAELayer,
				    ViTMAEModel,
				    ViTMAEPreTrainedModel,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_vit_mae import TFViTMAEForPreTraining, TFViTMAEModel, TFViTMAEPreTrainedModel


else:
		import sys

		__lowerCamelCase					:	Any       =  _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)
