


"""simple docstring"""






from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tf_available,
    is_tokenizers_available,
    is_torch_available,
)


UpperCamelCase__				:Any			   =	{"""configuration_xlnet""": ["""XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """XLNetConfig"""]}

try:
					if not is_sentencepiece_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase__				:int			   =	["""XLNetTokenizer"""]

try:
					if not is_tokenizers_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase__				:int			   =	["""XLNetTokenizerFast"""]

try:
					if not is_torch_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase__				:Union[str, Any]			   =	[
					    """XLNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """XLNetForMultipleChoice""",
					    """XLNetForQuestionAnswering""",
					    """XLNetForQuestionAnsweringSimple""",
					    """XLNetForSequenceClassification""",
					    """XLNetForTokenClassification""",
					    """XLNetLMHeadModel""",
					    """XLNetModel""",
					    """XLNetPreTrainedModel""",
					    """load_tf_weights_in_xlnet""",
					]

try:
					if not is_tf_available():
										raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
					pass
else:
					UpperCamelCase__				:Dict			   =	[
					    """TF_XLNET_PRETRAINED_MODEL_ARCHIVE_LIST""",
					    """TFXLNetForMultipleChoice""",
					    """TFXLNetForQuestionAnsweringSimple""",
					    """TFXLNetForSequenceClassification""",
					    """TFXLNetForTokenClassification""",
					    """TFXLNetLMHeadModel""",
					    """TFXLNetMainLayer""",
					    """TFXLNetModel""",
					    """TFXLNetPreTrainedModel""",
					]


if TYPE_CHECKING:
					from .configuration_xlnet import XLNET_PRETRAINED_CONFIG_ARCHIVE_MAP, XLNetConfig

					try:
										if not is_sentencepiece_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_xlnet import XLNetTokenizer

					try:
										if not is_tokenizers_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .tokenization_xlnet_fast import XLNetTokenizerFast

					try:
										if not is_torch_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_xlnet import (
										    XLNET_PRETRAINED_MODEL_ARCHIVE_LIST,
										    XLNetForMultipleChoice,
										    XLNetForQuestionAnswering,
										    XLNetForQuestionAnsweringSimple,
										    XLNetForSequenceClassification,
										    XLNetForTokenClassification,
										    XLNetLMHeadModel,
										    XLNetModel,
										    XLNetPreTrainedModel,
										    load_tf_weights_in_xlnet,
										)

					try:
										if not is_tf_available():
															raise OptionalDependencyNotAvailable()
					except OptionalDependencyNotAvailable:
										pass
					else:
										from .modeling_tf_xlnet import (
										    TF_XLNET_PRETRAINED_MODEL_ARCHIVE_LIST,
										    TFXLNetForMultipleChoice,
										    TFXLNetForQuestionAnsweringSimple,
										    TFXLNetForSequenceClassification,
										    TFXLNetForTokenClassification,
										    TFXLNetLMHeadModel,
										    TFXLNetMainLayer,
										    TFXLNetModel,
										    TFXLNetPreTrainedModel,
										)

else:
					import sys

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







def SCREAMING_SNAKE_CASE							(			lowercase_		)  ->			list:



       """simple docstring"""

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

       A__ 					=       []

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

              generate(k - 1					,							lowercase_		)

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

       generate(len(lowercase_		)					,							lowercase_		)
       return res


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


