
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 				SCREAMING_SNAKE_CASE__			(							unittest.TestCase			):

							"""simple docstring"""






							@slow
							def 			A__						(     self	)->      Optional[int]:





													'''simple docstring'''






													__UpperCamelCase        =	AutoModelForSeqaSeqLM.from_pretrained('''google/mt5-small'''   ,		return_dict=__SCREAMING_SNAKE_CASE	).to(__SCREAMING_SNAKE_CASE	)
													__UpperCamelCase        =	AutoTokenizer.from_pretrained('''google/mt5-small'''	)

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

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

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






'''simple docstring'''







import json
import os
import tempfile

from transformers.testing_utils import check_json_file_has_correct_format






class  lowerCAmelCase__   :
					lowerCAmelCase_        =     None






					def 	_snake_case    (   self		):


											"""simple docstring"""





											lowercase_	:     Tuple													=       self.feature_extraction_class(**self.feat_extract_dict		)
											lowercase_	:     Any													=       json.loads(feat_extract.to_json_string()		)
											for key, value in self.feat_extract_dict.items():
																	self.assertEqual(obj[key]				,							__SCREAMING_SNAKE_CASE		)






					def 	_snake_case    (   self		):


											"""simple docstring"""





											lowercase_	:     str													=       self.feature_extraction_class(**self.feat_extract_dict		)

											with tempfile.TemporaryDirectory() as tmpdirname:
																	lowercase_	:     str													=       os.path.join(__SCREAMING_SNAKE_CASE				,							'''feat_extract.json'''		)
																	feat_extract_first.to_json_file(__SCREAMING_SNAKE_CASE		)
																	lowercase_	:     str													=       self.feature_extraction_class.from_json_file(__SCREAMING_SNAKE_CASE		)

											self.assertEqual(feat_extract_second.to_dict()				,							feat_extract_first.to_dict()		)






					def 	_snake_case    (   self		):


											"""simple docstring"""





											lowercase_	:     Tuple													=       self.feature_extraction_class(**self.feat_extract_dict		)

											with tempfile.TemporaryDirectory() as tmpdirname:
																	lowercase_	:     Union[str, Any]													=       feat_extract_first.save_pretrained(__SCREAMING_SNAKE_CASE		)[0]
																	check_json_file_has_correct_format(__SCREAMING_SNAKE_CASE		)
																	lowercase_	:     str													=       self.feature_extraction_class.from_pretrained(__SCREAMING_SNAKE_CASE		)

											self.assertEqual(feat_extract_second.to_dict()				,							feat_extract_first.to_dict()		)






					def 	_snake_case    (   self		):


											"""simple docstring"""





											lowercase_	:     Optional[Any]													=       self.feature_extraction_class()
											self.assertIsNotNone(__SCREAMING_SNAKE_CASE		)



