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  _lowerCamelCase			(unittest.TestCase     ):







				def 							__UpperCAmelCase					( self    :       Dict						):

					"""simple docstring"""






					_lowercase :    Tuple							=							'hf-internal-testing/tiny-random-t5'
					_lowercase :    List[str]							=							AutoTokenizer.from_pretrained(lowerCamelCase_						)
					_lowercase :    Union[str, Any]							=							AutoModelForSeqaSeqLM.from_pretrained(lowerCamelCase_						)

					_lowercase :    Union[str, Any]							=							tokenizer('This is me'			,					return_tensors='pt'						)

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

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

					_lowercase :    int							=							model.generate(**lowerCamelCase_						)

					_lowercase :    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(lowerCamelCase_						)

						_lowercase :    str							=							AutoModelForSeqaSeqLM.from_pretrained(lowerCamelCase_						)

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

						_lowercase :    int							=							model_reloaded.generate(**lowerCamelCase_						)
						self.assertTrue(torch.allclose(lowerCamelCase_			,					lowerCamelCase_						)						)







				def 							__UpperCAmelCase					( self    :       Dict						):

					"""simple docstring"""






					_lowercase :    Tuple							=							'hf-internal-testing/tiny-random-t5'
					_lowercase :    List[Any]							=							AutoModelForSeqaSeqLM.from_pretrained(lowerCamelCase_						)

					_lowercase :    Dict							=							model.to_bettertransformer()

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

						_lowercase :    str							=							model.reverse_bettertransformer()
						model.save_pretrained(lowerCamelCase_						)




"""simple docstring"""







def      __lowerCAmelCase(		__UpperCAmelCase     ,__UpperCAmelCase			):






	"""simple docstring"""





	_lowercase :    Any							=							len(__UpperCAmelCase			)
	_lowercase :    Any							=							len(__UpperCAmelCase			)
	_lowercase :    List[Any]							=							[[False for _ in range(m + 1			)] for _ in range(n + 1			)]
	_lowercase :    Union[str, Any]							=							True
	for i in range(__UpperCAmelCase			):
		for j in range(m + 1			):
			if dp[i][j]:
				if j < m and a[i].upper() == b[j]:
					_lowercase :    Optional[int]							=							True
				if a[i].islower():
					_lowercase :    Union[str, Any]							=							True
	return dp[n][m]


if __name__ == "__main__":
						import doctest

						doctest.testmod()



