

'''simple docstring'''





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


UpperCamelCase_      	=					get_tests_dir("""fixtures/test_sentencepiece_bpe_char.model""")





@require_sentencepiece
@require_tokenizers
class 		__SCREAMING_SNAKE_CASE       ( _UpperCamelCase	,       unittest.TestCase			):
				lowerCamelCase_							=						SpeechTaTokenizer
				lowerCamelCase_							=						False
				lowerCamelCase_							=						True







				def    lowerCamelCase_  (					self    :		Optional[int]      ):
										'''simple docstring'''
										super().setUp()

										# We have a SentencePiece fixture for testing
										lowercase   :       Union[str, Any]								=SpeechTaTokenizer(UpperCAmelCase__      )

										lowercase   :       List[str]								=AddedToken('''<mask>'''		,				lstrip=UpperCAmelCase__		,				rstrip=UpperCAmelCase__      )
										lowercase   :       List[str]								=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]		,				UpperCAmelCase__    :		Tuple      ):
										'''simple docstring'''
										lowercase   :       List[str]								="this is a test"
										lowercase   :       Union[str, Any]								="this is a test"
										return input_text, output_text







				def    lowerCamelCase_  (					self    :		int		,				UpperCAmelCase__    :		Any		,				UpperCAmelCase__    :		List[Any]=False		,				UpperCAmelCase__    :		Optional[Any]=20		,				UpperCAmelCase__    :		Tuple=5      ):
										'''simple docstring'''
										lowercase   :       Optional[int]								=self.get_input_output_texts(UpperCAmelCase__      )
										lowercase   :       Tuple								=tokenizer.encode(UpperCAmelCase__		,				add_special_tokens=UpperCAmelCase__      )
										lowercase   :       str								=tokenizer.decode(UpperCAmelCase__		,				clean_up_tokenization_spaces=UpperCAmelCase__      )
										return text, ids







				def    lowerCamelCase_  (					self    :		Union[str, Any]      ):
										'''simple docstring'''
										lowercase   :       str								="<pad>"
										lowercase   :       Tuple								=1

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







				def    lowerCamelCase_  (					self    :		str      ):
										'''simple docstring'''
										lowercase   :       str								=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(UpperCAmelCase__      )		,				81      )







				def    lowerCamelCase_  (					self    :		List[str]      ):
										'''simple docstring'''
										self.assertEqual(self.get_tokenizer().vocab_size		,				79      )







				def    lowerCamelCase_  (					self    :		List[str]      ):
										'''simple docstring'''
										lowercase   :       Dict								=self.get_tokenizers(do_lower_case=UpperCAmelCase__      )
										for tokenizer in tokenizers:
																with self.subTest(F'''{tokenizer.__class__.__name__}'''      ):
																						lowercase   :       int								=tokenizer.vocab_size
																						lowercase   :       Optional[Any]								=len(UpperCAmelCase__      )

																						self.assertNotEqual(UpperCAmelCase__		,				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)

																						lowercase   :       Dict								=["aaaaa bbbbbb", "cccccccccdddddddd"]
																						lowercase   :       Dict								=tokenizer.add_tokens(UpperCAmelCase__      )
																						lowercase   :       Tuple								=tokenizer.vocab_size
																						lowercase   :       List[str]								=len(UpperCAmelCase__      )

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

																						lowercase   :       List[Any]								=tokenizer.encode('''aaaaa bbbbbb low cccccccccdddddddd l'''		,				add_special_tokens=UpperCAmelCase__      )

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

																						lowercase   :       Optional[int]								={"eos_token": ">>>>|||<||<<|<<", "pad_token": "<<<<<|||>|>>>>|>"}
																						lowercase   :       List[Any]								=tokenizer.add_special_tokens(UpperCAmelCase__      )
																						lowercase   :       Tuple								=tokenizer.vocab_size
																						lowercase   :       Optional[int]								=len(UpperCAmelCase__      )

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

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

																						self.assertGreaterEqual(len(UpperCAmelCase__      )		,				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    :		int      ):
										'''simple docstring'''
										pass







				def    lowerCamelCase_  (					self    :		Union[str, Any]      ):
										'''simple docstring'''
										pass







				def    lowerCamelCase_  (					self    :		Union[str, Any]      ):
										'''simple docstring'''
										lowercase   :       List[Any]								=self.get_tokenizer()

										lowercase   :       str								=tokenizer.tokenize('''This is a test'''      )
										# fmt: off
										self.assertListEqual(UpperCAmelCase__		,				[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(UpperCAmelCase__      )		,				[4, 32, 11, 10, 12, 4, 10, 12, 4, 7, 4, 6, 5, 12, 6]		,				)

										lowercase   :       Tuple								=tokenizer.tokenize('''I was born in 92000, and this is falsé.'''      )
										self.assertListEqual(
										    UpperCAmelCase__		,				[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''', '''.''']      )

										lowercase   :       Optional[int]								=tokenizer.convert_tokens_to_ids(UpperCAmelCase__      )
										# fmt: off
										self.assertListEqual(UpperCAmelCase__		,				[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

										lowercase   :       Union[str, Any]								=tokenizer.convert_ids_to_tokens(UpperCAmelCase__      )
										self.assertListEqual(
										    UpperCAmelCase__		,				[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    :		str      ):
										'''simple docstring'''
										# Use custom sequence because this tokenizer does not handle numbers.
										lowercase   :       List[str]								=[
										    "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
										lowercase   :       Dict								={
										    "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": [
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										        [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 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=UpperCAmelCase__		,				model_name='''microsoft/speecht5_asr'''		,				revision='''c5ef64c71905caeccde0e4462ef3f9077224c524'''		,				sequences=UpperCAmelCase__		,				)








'''simple docstring'''





import mpmath  # for roots of unity
import numpy as np





class 		__SCREAMING_SNAKE_CASE       :







				def __init__(					self    :		Union[str, Any]		,				UpperCAmelCase__    :		List[Any]=None		,				UpperCAmelCase__    :		Optional[Any]=None      ):
										'''simple docstring'''
										# Input as list
										lowercase   :       Optional[int]								=list(poly_a or [0]      )[:]
										lowercase   :       Optional[Any]								=list(poly_b or [0]      )[:]

										# Remove leading zero coefficients
										while self.polyA[-1] == 0:
																self.polyA.pop()
										lowercase   :       Any								=len(self.polyA      )

										while self.polyB[-1] == 0:
																self.polyB.pop()
										lowercase   :       Dict								=len(self.polyB      )

										# Add 0 to make lengths equal a power of 2
										lowercase   :       int								=int(
										    2 ** np.ceil(np.loga(len(self.polyA      ) + len(self.polyB      ) - 1      )      )      )

										while len(self.polyA      ) < self.c_max_length:
																self.polyA.append(0      )
										while len(self.polyB      ) < self.c_max_length:
																self.polyB.append(0      )
										# A complex root used for the fourier transform
										lowercase   :       Union[str, Any]								=complex(mpmath.root(x=1		,				n=self.c_max_length		,				k=1      )      )

										# The product
										lowercase   :       Tuple								=self.__multiply()







				def    lowerCamelCase_  (					self    :		Union[str, Any]		,				UpperCAmelCase__    :		Tuple      ):
										'''simple docstring'''
										lowercase   :       Union[str, Any]								=[[x] for x in self.polyA] if which == '''A''' else [[x] for x in self.polyB]
										# Corner case
										if len(UpperCAmelCase__      ) <= 1:
																return dft[0]
										#
										lowercase   :       Any								=self.c_max_length // 2
										while next_ncol > 0:
																lowercase   :       Optional[int]								=[[] for i in range(UpperCAmelCase__      )]
																lowercase   :       Tuple								=self.root**next_ncol

																# First half of next step
																lowercase   :       str								=1
																for j in range(self.c_max_length // (next_ncol * 2)      ):
																						for i in range(UpperCAmelCase__      ):
																												new_dft[i].append(dft[i][j] + current_root * dft[i + next_ncol][j]      )
																						current_root *= root
																# Second half of next step
																lowercase   :       int								=1
																for j in range(self.c_max_length // (next_ncol * 2)      ):
																						for i in range(UpperCAmelCase__      ):
																												new_dft[i].append(dft[i][j] - current_root * dft[i + next_ncol][j]      )
																						current_root *= root
																# Update
																lowercase   :       Dict								=new_dft
																lowercase   :       Tuple								=next_ncol // 2
										return dft[0]







				def    lowerCamelCase_  (					self    :		List[Any]      ):
										'''simple docstring'''
										lowercase   :       Any								=self.__dft('''A'''      )
										lowercase   :       Any								=self.__dft('''B'''      )
										lowercase   :       Optional[int]								=[[dft_a[i] * dft_b[i] for i in range(self.c_max_length      )]]
										del dft_a
										del dft_b

										# Corner Case
										if len(inverce_c[0]      ) <= 1:
																return inverce_c[0]
										# Inverse DFT
										lowercase   :       Optional[int]								=2
										while next_ncol <= self.c_max_length:
																lowercase   :       Optional[int]								=[[] for i in range(UpperCAmelCase__      )]
																lowercase   :       List[str]								=self.root ** (next_ncol // 2)
																lowercase   :       Optional[int]								=1
																# First half of next step
																for j in range(self.c_max_length // next_ncol      ):
																						for i in range(next_ncol // 2      ):
																												# Even positions
																												new_inverse_c[i].append(
																												    (
																												        inverce_c[i][j]
																												        + inverce_c[i][j + self.c_max_length // next_ncol]
																												    )
																												    / 2      )
																												# Odd positions
																												new_inverse_c[i + next_ncol // 2].append(
																												    (
																												        inverce_c[i][j]
																												        - inverce_c[i][j + self.c_max_length // next_ncol]
																												    )
																												    / (2 * current_root)      )
																						current_root *= root
																# Update
																lowercase   :       List[Any]								=new_inverse_c
																next_ncol *= 2
										# Unpack
										lowercase   :       Tuple								=[round(x[0].real		,				8      ) + round(x[0].imag		,				8      ) * 1J for x in inverce_c]

										# Remove leading 0's
										while inverce_c[-1] == 0:
																inverce_c.pop()
										return inverce_c







				def __str__(					self    :		Any      ):
										'''simple docstring'''
										lowercase   :       Any								='''A = ''' + ''' + '''.join(
										    F'''{coef}*x^{i}''' for coef, i in enumerate(self.polyA[: self.len_A]      )      )
										lowercase   :       Tuple								='''B = ''' + ''' + '''.join(
										    F'''{coef}*x^{i}''' for coef, i in enumerate(self.polyB[: self.len_B]      )      )
										lowercase   :       List[str]								='''A*B = ''' + ''' + '''.join(
										    F'''{coef}*x^{i}''' for coef, i in enumerate(self.product      )      )

										return F'''{a}\n{b}\n{c}'''


# Unit tests
if __name__ == "__main__":
							import doctest

							doctest.testmod()





