


"""simple docstring"""







def        UpperCAmelCase__	(lowerCAmelCase_       ):




					'''simple docstring'''


					if len(lowerCAmelCase_       ) < 2:
										return collection

					def circle_sort_util(lowerCAmelCase_  ,						lowerCAmelCase_  ,						lowerCAmelCase_       ) -> bool:
										__SCREAMING_SNAKE_CASE						       =    False

										if low == high:
															return swapped

										__SCREAMING_SNAKE_CASE						       =    low
										__SCREAMING_SNAKE_CASE						       =    high

										while left < right:
															if collection[left] > collection[right]:
																				__SCREAMING_SNAKE_CASE       ,  __SCREAMING_SNAKE_CASE						       =    (
																				    collection[right],
																				    collection[left],
																				)
																				__SCREAMING_SNAKE_CASE						       =    True

															left += 1
															right -= 1

										if left == right and collection[left] > collection[right + 1]:
															__SCREAMING_SNAKE_CASE       ,  __SCREAMING_SNAKE_CASE						       =    (
															    collection[right + 1],
															    collection[left],
															)

															__SCREAMING_SNAKE_CASE						       =    True

										__SCREAMING_SNAKE_CASE						       =    low + int((high - low) / 2       )
										__SCREAMING_SNAKE_CASE						       =    circle_sort_util(lowerCAmelCase_  ,						lowerCAmelCase_  ,						lowerCAmelCase_       )
										__SCREAMING_SNAKE_CASE						       =    circle_sort_util(lowerCAmelCase_  ,						mid + 1  ,						lowerCAmelCase_       )

										return swapped or left_swap or right_swap

					__SCREAMING_SNAKE_CASE						       =    True

					while is_not_sorted is True:
										__SCREAMING_SNAKE_CASE						       =    circle_sort_util(lowerCAmelCase_  ,						0  ,						len(lowerCAmelCase_       ) - 1       )

					return collection


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




"""simple docstring"""







from typing import TYPE_CHECKING

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


if is_sentencepiece_available():
		from ..ta.tokenization_ta import TaTokenizer
else:
		from ...utils.dummy_sentencepiece_objects import TaTokenizer

a__    :							Dict            =					TaTokenizer

if is_tokenizers_available():
		from ..ta.tokenization_ta_fast import TaTokenizerFast
else:
		from ...utils.dummy_tokenizers_objects import TaTokenizerFast

a__    :							Any            =					TaTokenizerFast

a__    :							Tuple            =					{'''configuration_mt5''': ['''MT5Config''', '''MT5OnnxConfig''']}

try:
		if not is_torch_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		a__    :							int            =					[
		    '''MT5EncoderModel''',
		    '''MT5ForConditionalGeneration''',
		    '''MT5ForQuestionAnswering''',
		    '''MT5Model''',
		    '''MT5PreTrainedModel''',
		    '''MT5Stack''',
		]

try:
		if not is_tf_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		a__    :							str            =					['''TFMT5EncoderModel''', '''TFMT5ForConditionalGeneration''', '''TFMT5Model''']

try:
		if not is_flax_available():
				raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
		pass
else:
		a__    :							Union[str, Any]            =					['''FlaxMT5EncoderModel''', '''FlaxMT5ForConditionalGeneration''', '''FlaxMT5Model''']


if TYPE_CHECKING:
		from .configuration_mta import MTaConfig, MTaOnnxConfig

		try:
				if not is_torch_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_mta import (
				    MTaEncoderModel,
				    MTaForConditionalGeneration,
				    MTaForQuestionAnswering,
				    MTaModel,
				    MTaPreTrainedModel,
				    MTaStack,
				)

		try:
				if not is_tf_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_tf_mta import TFMTaEncoderModel, TFMTaForConditionalGeneration, TFMTaModel

		try:
				if not is_flax_available():
						raise OptionalDependencyNotAvailable()
		except OptionalDependencyNotAvailable:
				pass
		else:
				from .modeling_flax_mta import FlaxMTaEncoderModel, FlaxMTaForConditionalGeneration, FlaxMTaModel

else:
		import sys

		a__    :							str            =					_LazyModule(
		    __name__,
		    globals()['''__file__'''],
		    _import_structure,
		    extra_objects={'''MT5Tokenizer''': MTaTokenizer, '''MT5TokenizerFast''': MTaTokenizerFast},
		    module_spec=__spec__,
		)
