
from typing import TYPE_CHECKING

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


lowerCamelCase__          =		{"""configuration_beit""": ["""BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BeitConfig""", """BeitOnnxConfig"""]}

try:
					if not is_vision_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCamelCase__          =		["""BeitFeatureExtractor"""]
					lowerCamelCase__          =		["""BeitImageProcessor"""]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCamelCase__          =		[
					    """BEIT_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """BeitForImageClassification""",
					    """BeitForMaskedImageModeling""",
					    """BeitForSemanticSegmentation""",
					    """BeitModel""",
					    """BeitPreTrainedModel""",
					]


try:
					if not is_flax_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					lowerCamelCase__          =		[
					    """FlaxBeitForImageClassification""",
					    """FlaxBeitForMaskedImageModeling""",
					    """FlaxBeitModel""",
					    """FlaxBeitPreTrainedModel""",
					]

if TYPE_CHECKING:
					from .configuration_beit import BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP, BeitConfig, BeitOnnxConfig

					try:
										if not is_vision_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .feature_extraction_beit import BeitFeatureExtractor
										from .image_processing_beit import BeitImageProcessor

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_beit import (
										    BEIT_PRETRAINED_MODEL_ARCHIVE_LIST,
										    BeitForImageClassification,
										    BeitForMaskedImageModeling,
										    BeitForSemanticSegmentation,
										    BeitModel,
										    BeitPreTrainedModel,
										)

					try:
										if not is_flax_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_flax_beit import (
										    FlaxBeitForImageClassification,
										    FlaxBeitForMaskedImageModeling,
										    FlaxBeitModel,
										    FlaxBeitPreTrainedModel,
										)


else:
					import sys

					lowerCamelCase__          =		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)

def  lowerCAmelCase__			(  SCREAMING_SNAKE_CASE_     )				->		list:

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

			lowerCAmelCase__      :      Optional[Any]         =		[]

			def generate(SCREAMING_SNAKE_CASE_       ,							SCREAMING_SNAKE_CASE_     ):
						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
												lowerCAmelCase__      ,				lowerCAmelCase__      :      str         =		arr[k - 1], arr[i]
									else:  # k is odd
												lowerCAmelCase__      ,				lowerCAmelCase__      :      Union[str, Any]         =		arr[k - 1], arr[0]
									generate(k - 1       ,							SCREAMING_SNAKE_CASE_     )

			generate(len(SCREAMING_SNAKE_CASE_     )       ,							SCREAMING_SNAKE_CASE_     )
			return res


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