





import unittest

from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken

from ...test_tokenization_common import TokenizerTesterMixin


lowerCAmelCase_    =    get_tests_dir('''fixtures/test_sentencepiece_bpe_char.model''')



@require_sentencepiece
@require_tokenizers
class  __lowerCAmelCase	(      _a,					unittest.TestCase					):
			lowerCamelCase_					:					Optional[Any]	      =				SpeechTaTokenizer
			lowerCamelCase_					:					Tuple	      =				False
			lowerCamelCase_					:					int	      =				True






			def       lowerCamelCase  (self   )					->       Dict:


							'''simple docstring'''



							super().setUp()

							# We have a SentencePiece fixture for testing
							snake_case_						:   Dict           =  SpeechTaTokenizer(__magic_name__   )

							snake_case_						:   Optional[int]           =  AddedToken('''<mask>''' ,							lstrip=__magic_name__ ,							rstrip=__magic_name__   )
							snake_case_						:   Dict           =  mask_token
							tokenizer.add_special_tokens({'''mask_token''': mask_token}   )
							tokenizer.add_tokens(['''<ctc_blank>''']   )

							tokenizer.save_pretrained(self.tmpdirname   )






			def       lowerCamelCase  (self ,							__magic_name__   )					->       Union[str, Any]:


							'''simple docstring'''



							snake_case_						:   List[str]           =  '''this is a test'''
							snake_case_						:   str           =  '''this is a test'''
							return input_text, output_text






			def       lowerCamelCase  (self ,							__magic_name__ ,							__magic_name__=False ,							__magic_name__=20 ,							__magic_name__=5   )					->       Union[str, Any]:


							'''simple docstring'''



							snake_case_      ,							snake_case_						:   Optional[int]           =  self.get_input_output_texts(__magic_name__   )
							snake_case_						:   str           =  tokenizer.encode(__magic_name__ ,							add_special_tokens=__magic_name__   )
							snake_case_						:   List[Any]           =  tokenizer.decode(__magic_name__ ,							clean_up_tokenization_spaces=__magic_name__   )
							return text, ids






			def       lowerCamelCase  (self   )					->       int:


							'''simple docstring'''



							snake_case_						:   List[Any]           =  '''<pad>'''
							snake_case_						:   List[str]           =  1

							self.assertEqual(self.get_tokenizer()._convert_token_to_id(__magic_name__   ) ,							__magic_name__   )
							self.assertEqual(self.get_tokenizer()._convert_id_to_token(__magic_name__   ) ,							__magic_name__   )






			def       lowerCamelCase  (self   )					->       int:


							'''simple docstring'''



							snake_case_						:   List[Any]           =  list(self.get_tokenizer().get_vocab().keys()   )

							self.assertEqual(vocab_keys[0] ,							'''<s>'''   )
							self.assertEqual(vocab_keys[1] ,							'''<pad>'''   )
							self.assertEqual(vocab_keys[-4] ,							'''œ'''   )
							self.assertEqual(vocab_keys[-2] ,							'''<mask>'''   )
							self.assertEqual(vocab_keys[-1] ,							'''<ctc_blank>'''   )
							self.assertEqual(len(__magic_name__   ) ,							81   )






			def       lowerCamelCase  (self   )					->       Optional[int]:


							'''simple docstring'''



							self.assertEqual(self.get_tokenizer().vocab_size ,							79   )






			def       lowerCamelCase  (self   )					->       int:


							'''simple docstring'''



							snake_case_						:   Optional[Any]           =  self.get_tokenizers(do_lower_case=__magic_name__   )
							for tokenizer in tokenizers:
											with self.subTest(F'''{tokenizer.__class__.__name__}'''   ):
															snake_case_						:   Dict           =  tokenizer.vocab_size
															snake_case_						:   List[Any]           =  len(__magic_name__   )

															self.assertNotEqual(__magic_name__ ,							0   )

															# We usually have added tokens from the start in tests because our vocab fixtures are
															# smaller than the original vocabs - let's not assert this
															# self.assertEqual(vocab_size, all_size)

															snake_case_						:   List[str]           =  ['''aaaaa bbbbbb''', '''cccccccccdddddddd''']
															snake_case_						:   str           =  tokenizer.add_tokens(__magic_name__   )
															snake_case_						:   Any           =  tokenizer.vocab_size
															snake_case_						:   Dict           =  len(__magic_name__   )

															self.assertNotEqual(__magic_name__ ,							0   )
															self.assertEqual(__magic_name__ ,							__magic_name__   )
															self.assertEqual(__magic_name__ ,							len(__magic_name__   )   )
															self.assertEqual(__magic_name__ ,							all_size + len(__magic_name__   )   )

															snake_case_						:   List[str]           =  tokenizer.encode('''aaaaa bbbbbb low cccccccccdddddddd l''' ,							add_special_tokens=__magic_name__   )

															self.assertGreaterEqual(len(__magic_name__   ) ,							4   )
															self.assertGreater(tokens[0] ,							tokenizer.vocab_size - 1   )
															self.assertGreater(tokens[-3] ,							tokenizer.vocab_size - 1   )

															snake_case_						:   Union[str, Any]           =  {'''eos_token''': '''>>>>|||<||<<|<<''', '''pad_token''': '''<<<<<|||>|>>>>|>'''}
															snake_case_						:   List[Any]           =  tokenizer.add_special_tokens(__magic_name__   )
															snake_case_						:   Optional[int]           =  tokenizer.vocab_size
															snake_case_						:   List[Any]           =  len(__magic_name__   )

															self.assertNotEqual(__magic_name__ ,							0   )
															self.assertEqual(__magic_name__ ,							__magic_name__   )
															self.assertEqual(__magic_name__ ,							len(__magic_name__   )   )
															self.assertEqual(__magic_name__ ,							all_size_a + len(__magic_name__   )   )

															snake_case_						:   Dict           =  tokenizer.encode(
															    '''>>>>|||<||<<|<< aaaaabbbbbb low cccccccccdddddddd <<<<<|||>|>>>>|> l''' ,							add_special_tokens=__magic_name__   )

															self.assertGreaterEqual(len(__magic_name__   ) ,							6   )
															self.assertGreater(tokens[0] ,							tokenizer.vocab_size - 1   )
															self.assertGreater(tokens[0] ,							tokens[1]   )
															self.assertGreater(tokens[-3] ,							tokenizer.vocab_size - 1   )
															self.assertGreater(tokens[-3] ,							tokens[-4]   )
															self.assertEqual(tokens[0] ,							tokenizer.eos_token_id   )
															self.assertEqual(tokens[-3] ,							tokenizer.pad_token_id   )






			def       lowerCamelCase  (self   )					->       List[Any]:


							'''simple docstring'''



							pass






			def       lowerCamelCase  (self   )					->       Any:


							'''simple docstring'''



							pass






			def       lowerCamelCase  (self   )					->       Optional[Any]:


							'''simple docstring'''



							snake_case_						:   Dict           =  self.get_tokenizer()

							snake_case_						:   List[str]           =  tokenizer.tokenize('''This is a test'''   )
							# fmt: off
							self.assertListEqual(__magic_name__ ,							[SPIECE_UNDERLINE, '''T''', '''h''', '''i''', '''s''', SPIECE_UNDERLINE, '''i''', '''s''', SPIECE_UNDERLINE, '''a''', SPIECE_UNDERLINE, '''t''', '''e''', '''s''', '''t''']   )
							# fmt: on

							self.assertListEqual(
							    tokenizer.convert_tokens_to_ids(__magic_name__   ) ,							[4, 32, 11, 10, 12, 4, 10, 12, 4, 7, 4, 6, 5, 12, 6] ,							)

							snake_case_						:   str           =  tokenizer.tokenize('''I was born in 92000, and this is falsé.'''   )
							self.assertListEqual(
							    __magic_name__ ,							[SPIECE_UNDERLINE, '''I''', SPIECE_UNDERLINE, '''w''', '''a''', '''s''', SPIECE_UNDERLINE, '''b''', '''o''', '''r''', '''n''', SPIECE_UNDERLINE, '''i''', '''n''', SPIECE_UNDERLINE, '''92000''', ''',''', SPIECE_UNDERLINE, '''a''', '''n''', '''d''', SPIECE_UNDERLINE, '''t''', '''h''', '''i''', '''s''', SPIECE_UNDERLINE, '''i''', '''s''', SPIECE_UNDERLINE, '''f''', '''a''', '''l''', '''s''', '''é''', '''.''']   )

							snake_case_						:   Union[str, Any]           =  tokenizer.convert_tokens_to_ids(__magic_name__   )
							# fmt: off
							self.assertListEqual(__magic_name__ ,							[4, 30, 4, 20, 7, 12, 4, 25, 8, 13, 9, 4, 10, 9, 4, 3, 23, 4, 7, 9, 14, 4, 6, 11, 10, 12, 4, 10, 12, 4, 19, 7, 15, 12, 73, 26]   )
							# fmt: on

							snake_case_						:   Tuple           =  tokenizer.convert_ids_to_tokens(__magic_name__   )
							self.assertListEqual(
							    __magic_name__ ,							[SPIECE_UNDERLINE, '''I''', SPIECE_UNDERLINE, '''w''', '''a''', '''s''', SPIECE_UNDERLINE, '''b''', '''o''', '''r''', '''n''', SPIECE_UNDERLINE, '''i''', '''n''', SPIECE_UNDERLINE, '''<unk>''', ''',''', SPIECE_UNDERLINE, '''a''', '''n''', '''d''', SPIECE_UNDERLINE, '''t''', '''h''', '''i''', '''s''', SPIECE_UNDERLINE, '''i''', '''s''', SPIECE_UNDERLINE, '''f''', '''a''', '''l''', '''s''', '''é''', '''.''']   )






			@slow
			def       lowerCamelCase  (self   )					->       Optional[Any]:


							'''simple docstring'''



							snake_case_						:   Optional[Any]           =  [
							    '''Transformers (formerly known as pytorch-transformers and pytorch-pretrained-bert) provides '''
							    '''general-purpose architectures (BERT, GPT, RoBERTa, XLM, DistilBert, XLNet...) for Natural '''
							    '''Language Understanding (NLU) and Natural Language Generation (NLG) with over thirty-two pretrained '''
							    '''models in one hundred plus languages and deep interoperability between Jax, PyTorch and TensorFlow.''',
							    '''BERT is designed to pre-train deep bidirectional representations from unlabeled text by jointly '''
							    '''conditioning on both left and right context in all layers.''',
							    '''The quick brown fox jumps over the lazy dog.''',
							]

							# fmt: off
							snake_case_						:   Any           =  {
							    '''input_ids''': [
							        [4, 32, 13, 7, 9, 12, 19, 8, 13, 18, 5, 13, 12, 4, 64, 19, 8, 13, 18, 5, 13, 15, 22, 4, 28, 9, 8, 20, 9, 4, 7, 12, 4, 24, 22, 6, 8, 13, 17, 11, 39, 6, 13, 7, 9, 12, 19, 8, 13, 18, 5, 13, 12, 4, 7, 9, 14, 4, 24, 22, 6, 8, 13, 17, 11, 39, 24, 13, 5, 6, 13, 7, 10, 9, 5, 14, 39, 25, 5, 13, 6, 63, 4, 24, 13, 8, 27, 10, 14, 5, 12, 4, 21, 5, 9, 5, 13, 7, 15, 39, 24, 16, 13, 24, 8, 12, 5, 4, 7, 13, 17, 11, 10, 6, 5, 17, 6, 16, 13, 5, 12, 4, 64, 40, 47, 54, 32, 23, 4, 53, 49, 32, 23, 4, 54, 8, 40, 47, 54, 32, 7, 23, 4, 69, 52, 43, 23, 4, 51, 10, 12, 6, 10, 15, 40, 5, 13, 6, 23, 4, 69, 52, 48, 5, 6, 26, 26, 26, 63, 4, 19, 8, 13, 4, 48, 7, 6, 16, 13, 7, 15, 4, 52, 7, 9, 21, 16, 7, 21, 5, 4, 61, 9, 14, 5, 13, 12, 6, 7, 9, 14, 10, 9, 21, 4, 64, 48, 52, 61, 63, 4, 7, 9, 14, 4, 48, 7, 6, 16, 13, 7, 15, 4, 52, 7, 9, 21, 16, 7, 21, 5, 4, 53, 5, 9, 5, 13, 7, 6, 10, 8, 9, 4, 64, 48, 52, 53, 63, 4, 20, 10, 6, 11, 4, 8, 27, 5, 13, 4, 6, 11, 10, 13, 6, 22, 39, 6, 20, 8, 4, 24, 13, 5, 6, 13, 7, 10, 9, 5, 14, 4, 18, 8, 14, 5, 15, 12, 4, 10, 9, 4, 8, 9, 5, 4, 11, 16, 9, 14, 13, 5, 14, 4, 24, 15, 16, 12, 4, 15, 7, 9, 21, 16, 7, 21, 5, 12, 4, 7, 9, 14, 4, 14, 5, 5, 24, 4, 10, 9, 6, 5, 13, 8, 24, 5, 13, 7, 25, 10, 15, 10, 6, 22, 4, 25, 5, 6, 20, 5, 5, 9, 4, 58, 7, 37, 23, 4, 49, 22, 32, 8, 13, 17, 11, 4, 7, 9, 14, 4, 32, 5, 9, 12, 8, 13, 55, 15, 8, 20, 26, 2],
							        [4, 40, 47, 54, 32, 4, 10, 12, 4, 14, 5, 12, 10, 21, 9, 5, 14, 4, 6, 8, 4, 24, 13, 5, 39, 6, 13, 7, 10, 9, 4, 14, 5, 5, 24, 4, 25, 10, 14, 10, 13, 5, 17, 6, 10, 8, 9, 7, 15, 4, 13, 5, 24, 13, 5, 12, 5, 9, 6, 7, 6, 10, 8, 9, 12, 4, 19, 13, 8, 18, 4, 16, 9, 15, 7, 25, 5, 15, 5, 14, 4, 6, 5, 37, 6, 4, 25, 22, 4, 46, 8, 10, 9, 6, 15, 22, 4, 17, 8, 9, 14, 10, 6, 10, 8, 9, 10, 9, 21, 4, 8, 9, 4, 25, 8, 6, 11, 4, 15, 5, 19, 6, 4, 7, 9, 14, 4, 13, 10, 21, 11, 6, 4, 17, 8, 9, 6, 5, 37, 6, 4, 10, 9, 4, 7, 15, 15, 4, 15, 7, 22, 5, 13, 12, 26, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
							        [4, 32, 11, 5, 4, 45, 16, 10, 17, 28, 4, 25, 13, 8, 20, 9, 4, 19, 8, 37, 4, 46, 16, 18, 24, 12, 4, 8, 27, 5, 13, 4, 6, 11, 5, 4, 15, 7, 57, 22, 4, 14, 8, 21, 26, 2, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
							    ],
							    '''attention_mask''': [
							        [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
							        [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
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							    ]
							}
							# fmt: on

							self.tokenizer_integration_test_util(
							    expected_encoding=__magic_name__ ,							model_name='''microsoft/speecht5_asr''' ,							revision='''c5ef64c71905caeccde0e4462ef3f9077224c524''' ,							sequences=__magic_name__ ,							)







import unittest

from transformers import load_tool
from transformers.utils import is_torch_available


if is_torch_available():
	import torch

from transformers.testing_utils import require_torch

from .test_tools_common import ToolTesterMixin



@require_torch
class  __lowerCAmelCase	(      unittest.TestCase,					_a					):






			def       lowerCamelCase  (self   )					->       int:


							'''simple docstring'''



							snake_case_						:   Dict           =  load_tool('''text-to-speech'''   )
							self.tool.setup()






			def       lowerCamelCase  (self   )					->       List[str]:


							'''simple docstring'''



							torch.manual_seed(0   )
							snake_case_						:   Optional[int]           =  self.tool('''hey'''   )
							snake_case_						:   Union[str, Any]           =  result.to_raw()
							self.assertTrue(
							    torch.allclose(
							        resulting_tensor[:3] ,							torch.tensor([-0.0_005_966_668_832_115_829, -0.0_003_657_640_190_795_064, -0.00_013_439_502_799_883_485]   ) ,							)   )






			def       lowerCamelCase  (self   )					->       Optional[Any]:


							'''simple docstring'''



							torch.manual_seed(0   )
							snake_case_						:   Any           =  self.tool('''hey'''   )
							snake_case_						:   str           =  result.to_raw()
							self.assertTrue(
							    torch.allclose(
							        resulting_tensor[:3] ,							torch.tensor([-0.0_005_966_668_832_115_829, -0.0_003_657_640_190_795_064, -0.00_013_439_502_799_883_485]   ) ,							)   )
