





def        __UpperCAmelCase    (       UpperCAmelCase       )->       list:



			"""simple docstring"""







			lowercase							=		False
			while is_sorted is False:  # Until all the indices are traversed keep looping
						lowercase							=		True
						for i in range(0,		len(UpperCAmelCase       ) - 1,		2       ):  # iterating over all even indices
									if input_list[i] > input_list[i + 1]:
												lowercase		,lowercase							=		input_list[i + 1], input_list[i]
												# swapping if elements not in order
												lowercase							=		False

						for i in range(1,		len(UpperCAmelCase       ) - 1,		2       ):  # iterating over all odd indices
									if input_list[i] > input_list[i + 1]:
												lowercase		,lowercase							=		input_list[i + 1], input_list[i]
												# swapping if elements not in order
												lowercase							=		False
			return input_list


if __name__ == "__main__":
						print("Enter list to be sorted")
						A_      =      [int(x) for x in input().split()]
						# inputing elements of the list in one line
						A_      =      odd_even_sort(input_list)
						print("The sorted list is")
						print(sorted_list)






from typing import TYPE_CHECKING

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


A_      =      {
    "configuration_gpt_bigcode": ["GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTBigCodeConfig"],
}

try:
						if not is_torch_available():
												raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
						pass
else:
						A_      =      [
						    "GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST",
						    "GPTBigCodeForSequenceClassification",
						    "GPTBigCodeForTokenClassification",
						    "GPTBigCodeForCausalLM",
						    "GPTBigCodeModel",
						    "GPTBigCodePreTrainedModel",
						]

if TYPE_CHECKING:
						from .configuration_gpt_bigcode import GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP, GPTBigCodeConfig

						try:
												if not is_torch_available():
																		raise OptionalDependencyNotAvailable()
						except OptionalDependencyNotAvailable:
												pass
						else:
												from .modeling_gpt_bigcode import (
												    GPT_BIGCODE_PRETRAINED_MODEL_ARCHIVE_LIST,
												    GPTBigCodeForCausalLM,
												    GPTBigCodeForSequenceClassification,
												    GPTBigCodeForTokenClassification,
												    GPTBigCodeModel,
												    GPTBigCodePreTrainedModel,
												)


else:
						import sys

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





