


'''simple docstring'''



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 			a       (	unittest.TestCase ):


     """simple docstring"""






     def 				lowerCamelCase__				(       self  :	Optional[Any]    )		->							Union[str, Any]:
          __UpperCAmelCase			:				int													=    '''hf-internal-testing/tiny-random-t5'''
          __UpperCAmelCase			:				Dict													=    AutoTokenizer.from_pretrained(snake_case    )
          __UpperCAmelCase			:				Any													=    AutoModelForSeqaSeqLM.from_pretrained(snake_case    )

          __UpperCAmelCase			:				Tuple													=    tokenizer('''This is me'''							,				return_tensors='''pt'''    )

          __UpperCAmelCase			:				str													=    model.to_bettertransformer()

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

          __UpperCAmelCase			:				Optional[int]													=    model.generate(**snake_case    )

          __UpperCAmelCase			:				Union[str, Any]													=    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(snake_case    )

               __UpperCAmelCase			:				Any													=    AutoModelForSeqaSeqLM.from_pretrained(snake_case    )

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

               __UpperCAmelCase			:				Optional[int]													=    model_reloaded.generate(**snake_case    )
               self.assertTrue(torch.allclose(snake_case							,				snake_case    )    )






     def 				lowerCamelCase__				(       self  :	List[Any]    )		->							Any:
          __UpperCAmelCase			:				Any													=    '''hf-internal-testing/tiny-random-t5'''
          __UpperCAmelCase			:				Tuple													=    AutoModelForSeqaSeqLM.from_pretrained(snake_case    )

          __UpperCAmelCase			:				Optional[int]													=    model.to_bettertransformer()

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

               __UpperCAmelCase			:				Optional[Any]													=    model.reverse_bettertransformer()
               model.save_pretrained(snake_case    )



'''simple docstring'''



def 			_a			(		_lowercase      :			List[str]						):





     '''simple docstring'''






     __UpperCAmelCase			:				int													=    len(_lowercase						)
     while cur > 1:
          # Find the maximum number in arr
          __UpperCAmelCase			:				Union[str, Any]													=    arr.index(max(arr[0:cur]						)						)
          # Reverse from 0 to mi
          __UpperCAmelCase			:				Any													=    arr[mi::-1] + arr[mi + 1 : len(_lowercase						)]
          # Reverse whole list
          __UpperCAmelCase			:				List[str]													=    arr[cur - 1 :: -1] + arr[cur : len(_lowercase						)]
          cur -= 1
     return arr


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