





"""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 					_UpperCAmelCase   (	unittest.TestCase ):


					@slow
					def 	lowerCamelCase       (					self			:List[str]		):
												A		=  AutoModelForSeqaSeqLM.from_pretrained("google/mt5-small"     ,       return_dict=__UpperCamelCase		).to(__UpperCamelCase		)
												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(__UpperCamelCase		)     ,       labels=labels.to(__UpperCamelCase		)		).loss
												A		=  -(labels.shape[-1] * loss.item())

												A		=  -84.9_127
												self.assertTrue(abs(mtf_score - EXPECTED_SCORE		) < 1e-4		)









"""simple docstring"""
def 					A__				(			UpperCamelCase					,  UpperCamelCase = False       ):

							if not isinstance(UpperCamelCase					,  UpperCamelCase       ):
														A		=  F"Expected string as input, found {type(UpperCamelCase       )}"
														raise ValueError(UpperCamelCase       )
							if not isinstance(UpperCamelCase					,  UpperCamelCase       ):
														A		=  F"Expected boolean as use_pascal parameter, found {type(UpperCamelCase       )}"
														raise ValueError(UpperCamelCase       )

							A		=  input_str.split("_"       )

							A		=  0 if use_pascal else 1

							A		=  words[start_index:]

							A		=  [word[0].upper() + word[1:] for word in words_to_capitalize]

							A		=  "" if use_pascal else words[0]

							return "".join([initial_word, *capitalized_words]       )


if __name__ == "__main__":
		from doctest import testmod

		testmod()


