

'''simple docstring'''





from __future__ import annotations

from cmath import sqrt






def 				_lowerCAmelCase			(   __magic_name__						:     int   , __magic_name__						:     int   , __magic_name__						:     int						)				->  tuple[complex, complex]:

						if a == 0:
												raise ValueError('''Coefficient \'a\' must not be zero.'''						)
						lowercase :							Dict    		=b * b - 4 * a * c

						lowercase :							List[Any]    		=(-b + sqrt(__magic_name__						)) / (2 * a)
						lowercase :							Dict    		=(-b - sqrt(__magic_name__						)) / (2 * a)

						return (
						    root_a.real if not root_a.imag else root_a,
						    root_a.real if not root_a.imag else root_a,
						)






def 				_lowerCAmelCase			(   )				->  Optional[Any]:
						lowercase		,	lowercase :							Optional[int]    		=quadratic_roots(a=5   , b=6   , c=1						)
						print(f'''The solutions are: {solutiona} and {solutiona}'''						)


if __name__ == "__main__":
							main()







"""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 						a__		( unittest.TestCase		):
   @slow
   def      __magic_name__     (     self							):
          lowercase       :							Tuple									=				AutoModelForSeqaSeqLM.from_pretrained("google/mt5-small"      ,       return_dict=_a							).to(_a							)
          lowercase       :							Union[str, Any]									=				AutoTokenizer.from_pretrained("google/mt5-small"							)

          lowercase       :							Optional[Any]									=				tokenizer("Hello there"      ,       return_tensors="pt"							).input_ids
          lowercase       :							Union[str, Any]									=				tokenizer("Hi I am"      ,       return_tensors="pt"							).input_ids

          lowercase       :							int									=				model(input_ids.to(_a							)      ,       labels=labels.to(_a							)							).loss
          lowercase       :							str									=				-(labels.shape[-1] * loss.item())

          lowercase       :							List[str]									=				-8_4.9_1_2_7
          self.assertTrue(abs(mtf_score - EXPECTED_SCORE							) < 1E-4							)


