
'''simple docstring'''







def  snake_case_		(    __SCREAMING_SNAKE_CASE :			list							):



						"""simple docstring"""





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

						lowercase_     :					Tuple													=	[]

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

												generate(k - 1				,				__SCREAMING_SNAKE_CASE							)

												for i in range(k - 1							):
																		if k % 2 == 0:  # k is even
																								lowercase_						,			lowercase_     :					int													=	arr[k - 1], arr[i]
																		else:  # k is odd
																								lowercase_						,			lowercase_     :					int													=	arr[k - 1], arr[0]
																		generate(k - 1				,				__SCREAMING_SNAKE_CASE							)

						generate(len(__SCREAMING_SNAKE_CASE							)				,				__SCREAMING_SNAKE_CASE							)
						return res


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





'''simple docstring'''







from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


_lowercase			:  Tuple   							=	{"configuration_vit_msn": ["VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP", "ViTMSNConfig"]}

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							_lowercase			:  str   							=	[
							    "VIT_MSN_PRETRAINED_MODEL_ARCHIVE_LIST",
							    "ViTMSNModel",
							    "ViTMSNForImageClassification",
							    "ViTMSNPreTrainedModel",
							]

if TYPE_CHECKING:
							from .configuration_vit_msn import VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP, ViTMSNConfig

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_vit_msn import (
														    VIT_MSN_PRETRAINED_MODEL_ARCHIVE_LIST,
														    ViTMSNForImageClassification,
														    ViTMSNModel,
														    ViTMSNPreTrainedModel,
														)

else:
							import sys

							_lowercase			:  int   							=	_LazyModule(__name__, globals()["__file__"], _import_structure, module_spec=__spec__)



