



def    lowerCamelCase_(lowerCamelCase_    ) ->       list[int]:
						UpperCAmelCase         =     len(lowerCamelCase_    )
						for i in range(lowerCamelCase_    ):
												for j in range(i + 1    ,   lowerCamelCase_    ):
																		if numbers[j] < numbers[i]:
																								UpperCAmelCase       ,		UpperCAmelCase         =     numbers[j], numbers[i]
						return numbers


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








import tempfile
import unittest

from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.testing_utils import (
    is_torch_available,
    require_optimum,
    require_torch,
    slow,
)


if is_torch_available():
		import torch





@require_torch
@require_optimum
@slow
class  __magic_name__   (							unittest.TestCase						):






		def SCREAMING_SNAKE_CASE_			(						self      :     Tuple      )				->					Optional[int]:
								'''simple docstring'''







								UpperCAmelCase         =     "hf-internal-testing/tiny-random-t5"
								UpperCAmelCase         =     AutoTokenizer.from_pretrained(UpperCamelCase__      )
								UpperCAmelCase         =     AutoModelForSeqaSeqLM.from_pretrained(UpperCamelCase__      )

								UpperCAmelCase         =     tokenizer("This is me"				,		return_tensors="pt"      )

								UpperCAmelCase         =     model.to_bettertransformer()

								self.assertTrue(any("BetterTransformer" in mod.__class__.__name__ for _, mod in model.named_modules()      )      )

								UpperCAmelCase         =     model.generate(**UpperCamelCase__      )

								UpperCAmelCase         =     model.reverse_bettertransformer()

								self.assertFalse(any("BetterTransformer" in mod.__class__.__name__ for _, mod in model.named_modules()      )      )

								with tempfile.TemporaryDirectory() as tmpdirname:
														model.save_pretrained(UpperCamelCase__      )

														UpperCAmelCase         =     AutoModelForSeqaSeqLM.from_pretrained(UpperCamelCase__      )

														self.assertFalse(
														    any("BetterTransformer" in mod.__class__.__name__ for _, mod in model_reloaded.named_modules()      )      )

														UpperCAmelCase         =     model_reloaded.generate(**UpperCamelCase__      )
														self.assertTrue(torch.allclose(UpperCamelCase__				,		UpperCamelCase__      )      )







		def SCREAMING_SNAKE_CASE_			(						self      :     List[str]      )				->					Optional[int]:
								'''simple docstring'''







								UpperCAmelCase         =     "hf-internal-testing/tiny-random-t5"
								UpperCAmelCase         =     AutoModelForSeqaSeqLM.from_pretrained(UpperCamelCase__      )

								UpperCAmelCase         =     model.to_bettertransformer()

								with tempfile.TemporaryDirectory() as tmpdirname:
														with self.assertRaises(UpperCamelCase__      ):
																				model.save_pretrained(UpperCamelCase__      )

														UpperCAmelCase         =     model.reverse_bettertransformer()
														model.save_pretrained(UpperCamelCase__      )



