






from typing import TYPE_CHECKING

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


_a       =    {
    "configuration_bart": ["BART_PRETRAINED_CONFIG_ARCHIVE_MAP", "BartConfig", "BartOnnxConfig"],
    "tokenization_bart": ["BartTokenizer"],
}

try:
		if not is_tokenizers_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_a       =    ["BartTokenizerFast"]

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_a       =    [
		    "BART_PRETRAINED_MODEL_ARCHIVE_LIST",
		    "BartForCausalLM",
		    "BartForConditionalGeneration",
		    "BartForQuestionAnswering",
		    "BartForSequenceClassification",
		    "BartModel",
		    "BartPretrainedModel",
		    "PretrainedBartModel",
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_a       =    [
		    "TFBartForConditionalGeneration",
		    "TFBartForSequenceClassification",
		    "TFBartModel",
		    "TFBartPretrainedModel",
		]

try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		_a       =    [
		    "FlaxBartDecoderPreTrainedModel",
		    "FlaxBartForCausalLM",
		    "FlaxBartForConditionalGeneration",
		    "FlaxBartForQuestionAnswering",
		    "FlaxBartForSequenceClassification",
		    "FlaxBartModel",
		    "FlaxBartPreTrainedModel",
		]

if TYPE_CHECKING:
		from .configuration_bart import BART_PRETRAINED_CONFIG_ARCHIVE_MAP, BartConfig, BartOnnxConfig
		from .tokenization_bart import BartTokenizer

		try:
				if not is_tokenizers_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .tokenization_bart_fast import BartTokenizerFast

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_bart import (
				    BART_PRETRAINED_MODEL_ARCHIVE_LIST,
				    BartForCausalLM,
				    BartForConditionalGeneration,
				    BartForQuestionAnswering,
				    BartForSequenceClassification,
				    BartModel,
				    BartPretrainedModel,
				    PretrainedBartModel,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_bart import (
				    TFBartForConditionalGeneration,
				    TFBartForSequenceClassification,
				    TFBartModel,
				    TFBartPretrainedModel,
				)

		try:
				if not is_flax_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_flax_bart import (
				    FlaxBartDecoderPreTrainedModel,
				    FlaxBartForCausalLM,
				    FlaxBartForConditionalGeneration,
				    FlaxBartForQuestionAnswering,
				    FlaxBartForSequenceClassification,
				    FlaxBartModel,
				    FlaxBartPreTrainedModel,
				)

else:
		import sys

		_a       =    _LazyModule(__name__, globals()['''__file__'''], _import_structure, module_spec=__spec__)





'''simple docstring'''



def 							__UpperCAmelCase				(				UpperCamelCase__				:int			)		->						Any:
				snake_case__      :   Dict      =    len(UpperCamelCase__			)
				for _ in range(
				    0   ,				int(((no_of_elements - 1) / 2) + 1			)			):  # we don't need to traverse to end of list as
								for j in range(0   ,				no_of_elements - 1			):
												if (
												    lst[j + 1] < lst[j]
												):  # applying bubble sort algorithm from left to right (or forwards)
																snake_case__      :   int      =    lst[j + 1]
																snake_case__      :   Tuple      =    lst[j]
																snake_case__      :   Tuple      =    temp
												if (
												    lst[no_of_elements - 1 - j] < lst[no_of_elements - 2 - j]
												):  # applying bubble sort algorithm from right to left (or backwards)
																snake_case__      :   Optional[Any]      =    lst[no_of_elements - 1 - j]
																snake_case__      :   Tuple      =    lst[no_of_elements - 2 - j]
																snake_case__      :   Any      =    temp
				return lst


if __name__ == "__main__":
				print("enter the list to be sorted")
				_lowercase       :						Any						=[int(x) for x in input().split()]  # inputing elements of the list in one line
				_lowercase       :						Tuple						=double_sort(lst)
				print("the sorted list is")
				print(sorted_lst)




