


"""simple docstring"""


import unittest

from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device


if is_torch_available():
	from transformers import AutoModelForSeqaSeqLM, AutoTokenizer



@require_torch
@require_sentencepiece
@require_tokenizers
class 			lowerCamelCase__						(   unittest.TestCase			):







						@slow
						def __a						(							self   :    Tuple		):
								A					       = AutoModelForSeqaSeqLM.from_pretrained('google/mt5-small'			,			return_dict=_lowercase		).to(_lowercase		)
								A					       = AutoTokenizer.from_pretrained('google/mt5-small'		)

								A					       = tokenizer('Hello there'			,			return_tensors='pt'		).input_ids
								A					       = tokenizer('Hi I am'			,			return_tensors='pt'		).input_ids

								A					       = model(input_ids.to(_lowercase		)			,			labels=labels.to(_lowercase		)		).loss
								A					       = -(labels.shape[-1] * loss.item())

								A					       = -8_4.9_1_2_7
								self.assertTrue(abs(mtf_score - EXPECTED_SCORE		) < 1e-4		)









"""simple docstring"""


from __future__ import annotations







def  __snake_case       (   UpperCamelCase__	)      ->		int:







		"""simple docstring"""





		if not nums:
				return 0
		A					       = nums[0]
		A					       = 0
		for num in nums[1:]:
				A       , A					       = (
				    max_excluding + num,
				    max(UpperCamelCase__ ,			UpperCamelCase__	),
				)
		return max(UpperCamelCase__ ,			UpperCamelCase__	)


if __name__ == "__main__":
	import doctest

	doctest.testmod()





