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


lowercase		:  Any     					=       get_tests_dir("""fixtures/test_sentencepiece_bpe_char.model""")






@require_sentencepiece
@require_tokenizers
class 					a__     ( __a  ,				unittest.TestCase ):
				_A       					=							SpeechTaTokenizer
				_A       					=							False
				_A       					=							True






				def   lowerCAmelCase (    self       :						str							)       ->      Optional[int]:

										"""simple docstring"""
										super().setUp()

										# We have a SentencePiece fixture for testing
										lowerCamelCase_:       Any					     = SpeechTaTokenizer(_lowerCamelCase							)

										lowerCamelCase_:       Union[str, Any]					     = AddedToken("""<mask>"""  ,							lstrip=_lowerCamelCase  ,							rstrip=_lowerCamelCase							)
										lowerCamelCase_:       List[Any]					     = mask_token
										tokenizer.add_special_tokens({"""mask_token""": mask_token}							)
										tokenizer.add_tokens(["""<ctc_blank>"""]							)

										tokenizer.save_pretrained(self.tmpdirname							)






				def   lowerCAmelCase (    self       :						List[Any]  ,							A_       :						str							)       ->      Optional[Any]:

										"""simple docstring"""
										lowerCamelCase_:       List[str]					     = """this is a test"""
										lowerCamelCase_:       Optional[Any]					     = """this is a test"""
										return input_text, output_text






				def   lowerCAmelCase (    self       :						Tuple  ,							A_       :						int  ,							A_       :						List[str]=False  ,							A_       :						Union[str, Any]=20  ,							A_       :						Tuple=5							)       ->      Any:

										"""simple docstring"""
										lowerCamelCase_     ,  lowerCamelCase_:       Optional[Any]					     = self.get_input_output_texts(_lowerCamelCase							)
										lowerCamelCase_:       Optional[Any]					     = tokenizer.encode(_lowerCamelCase  ,							add_special_tokens=_lowerCamelCase							)
										lowerCamelCase_:       List[Any]					     = tokenizer.decode(_lowerCamelCase  ,							clean_up_tokenization_spaces=_lowerCamelCase							)
										return text, ids






				def   lowerCAmelCase (    self       :						Tuple							)       ->      int:

										"""simple docstring"""
										lowerCamelCase_:       Dict					     = """<pad>"""
										lowerCamelCase_:       int					     = 1

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






				def   lowerCAmelCase (    self       :						List[Any]							)       ->      List[str]:

										"""simple docstring"""
										lowerCamelCase_:       Optional[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(_lowerCamelCase							)  ,							81							)






				def   lowerCAmelCase (    self       :						int							)       ->      List[str]:

										"""simple docstring"""
										self.assertEqual(self.get_tokenizer().vocab_size  ,							79							)






				def   lowerCAmelCase (    self       :						Dict							)       ->      int:

										"""simple docstring"""
										lowerCamelCase_:       List[str]					     = self.get_tokenizers(do_lower_case=_lowerCamelCase							)
										for tokenizer in tokenizers:
																with self.subTest(f"""{tokenizer.__class__.__name__}"""							):
																						lowerCamelCase_:       str					     = tokenizer.vocab_size
																						lowerCamelCase_:       List[Any]					     = len(_lowerCamelCase							)

																						self.assertNotEqual(_lowerCamelCase  ,							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)

																						lowerCamelCase_:       List[Any]					     = ["""aaaaa bbbbbb""", """cccccccccdddddddd"""]
																						lowerCamelCase_:       str					     = tokenizer.add_tokens(_lowerCamelCase							)
																						lowerCamelCase_:       Dict					     = tokenizer.vocab_size
																						lowerCamelCase_:       List[Any]					     = len(_lowerCamelCase							)

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

																						lowerCamelCase_:       Optional[Any]					     = tokenizer.encode("""aaaaa bbbbbb low cccccccccdddddddd l"""  ,							add_special_tokens=_lowerCamelCase							)

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

																						lowerCamelCase_:       Optional[int]					     = {"""eos_token""": """>>>>|||<||<<|<<""", """pad_token""": """<<<<<|||>|>>>>|>"""}
																						lowerCamelCase_:       Dict					     = tokenizer.add_special_tokens(_lowerCamelCase							)
																						lowerCamelCase_:       Any					     = tokenizer.vocab_size
																						lowerCamelCase_:       List[str]					     = len(_lowerCamelCase							)

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

																						lowerCamelCase_:       Optional[int]					     = tokenizer.encode(
																						    """>>>>|||<||<<|<< aaaaabbbbbb low cccccccccdddddddd <<<<<|||>|>>>>|> l"""  ,							add_special_tokens=_lowerCamelCase							)

																						self.assertGreaterEqual(len(_lowerCamelCase							)  ,							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       :						Tuple							)       ->      List[Any]:

										"""simple docstring"""
										pass






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

										"""simple docstring"""
										pass






				def   lowerCAmelCase (    self       :						int							)       ->      List[Any]:

										"""simple docstring"""
										lowerCamelCase_:       Tuple					     = self.get_tokenizer()

										lowerCamelCase_:       Any					     = tokenizer.tokenize("""This is a test"""							)
										# fmt: off
										self.assertListEqual(_lowerCamelCase  ,							[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(_lowerCamelCase							)  ,							[4, 32, 11, 10, 12, 4, 10, 12, 4, 7, 4, 6, 5, 12, 6]  ,							)

										lowerCamelCase_:       int					     = tokenizer.tokenize("""I was born in 92000, and this is falsé."""							)
										self.assertListEqual(
										    _lowerCamelCase  ,							[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""", """."""]							)

										lowerCamelCase_:       Any					     = tokenizer.convert_tokens_to_ids(_lowerCamelCase							)
										# fmt: off
										self.assertListEqual(_lowerCamelCase  ,							[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

										lowerCamelCase_:       Tuple					     = tokenizer.convert_ids_to_tokens(_lowerCamelCase							)
										self.assertListEqual(
										    _lowerCamelCase  ,							[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       :						List[Any]							)       ->      Union[str, Any]:

										"""simple docstring"""
										lowerCamelCase_:       List[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
										lowerCamelCase_:       Optional[int]					     = {
										    """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],
										        [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 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, 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],
										    ]
										}
										# fmt: on

										self.tokenizer_integration_test_util(
										    expected_encoding=_lowerCamelCase  ,							model_name="""microsoft/speecht5_asr"""  ,							revision="""c5ef64c71905caeccde0e4462ef3f9077224c524"""  ,							sequences=_lowerCamelCase  ,							)






"""simple docstring"""






def      lowerCAmelCase__			(		__magic_name__      )						->int:

			if not isinstance(__magic_name__			,   __magic_name__      ):
						raise ValueError("multiplicative_persistence() only accepts integral values"      )
			if num < 0:
						raise ValueError("multiplicative_persistence() does not accept negative values"      )

			__lowercase       =       0
			__lowercase       =       str(__magic_name__      )

			while len(__magic_name__      ) != 1:
						__lowercase       =       [int(__magic_name__      ) for i in num_string]

						__lowercase       =       1
						for i in range(0			,   len(__magic_name__      )      ):
									total *= numbers[i]

						__lowercase       =       str(__magic_name__      )

						steps += 1
			return steps



def      lowerCAmelCase__			(		__magic_name__      )						->int:

			if not isinstance(__magic_name__			,   __magic_name__      ):
						raise ValueError("additive_persistence() only accepts integral values"      )
			if num < 0:
						raise ValueError("additive_persistence() does not accept negative values"      )

			__lowercase       =       0
			__lowercase       =       str(__magic_name__      )

			while len(__magic_name__      ) != 1:
						__lowercase       =       [int(__magic_name__      ) for i in num_string]

						__lowercase       =       0
						for i in range(0			,   len(__magic_name__      )      ):
									total += numbers[i]

						__lowercase       =       str(__magic_name__      )

						steps += 1
			return steps


if __name__ == "__main__":
					import doctest

					doctest.testmod()





