






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   :   Optional[Any]      =    get_tests_dir("""fixtures/test_sentencepiece_bpe_char.model""")


@require_sentencepiece
@require_tokenizers
class 							__UpperCamelCase     (  _lowerCAmelCase ,      unittest.TestCase ):
	__snake_case						:Tuple =							SpeechTaTokenizer
	__snake_case						:int =							False
	__snake_case						:Dict =							True







	def 			_a (	self   :				List[Any]      )		->			List[Any]:
		"""simple docstring"""







		super().setUp()

		# We have a SentencePiece fixture for testing
		__lowercase   							=	SpeechTaTokenizer(_lowerCAmelCase      )

		__lowercase   							=	AddedToken("""<mask>"""							,					lstrip=_lowerCAmelCase							,					rstrip=_lowerCAmelCase      )
		__lowercase   							=	mask_token
		tokenizer.add_special_tokens({"""mask_token""": mask_token}      )
		tokenizer.add_tokens(["""<ctc_blank>"""]      )

		tokenizer.save_pretrained(self.tmpdirname      )







	def 			_a (	self   :				Optional[int]							,					_lowerCAmelCase   :				Optional[Any]      )		->			Any:
		"""simple docstring"""







		__lowercase   							=	"""this is a test"""
		__lowercase   							=	"""this is a test"""
		return input_text, output_text







	def 			_a (	self   :				List[Any]							,					_lowerCAmelCase   :				Tuple							,					_lowerCAmelCase   :				List[Any]=False							,					_lowerCAmelCase   :				str=20							,					_lowerCAmelCase   :				List[str]=5      )		->			str:
		"""simple docstring"""







		__lowercase							,    __lowercase   							=	self.get_input_output_texts(_lowerCAmelCase      )
		__lowercase   							=	tokenizer.encode(_lowerCAmelCase							,					add_special_tokens=_lowerCAmelCase      )
		__lowercase   							=	tokenizer.decode(_lowerCAmelCase							,					clean_up_tokenization_spaces=_lowerCAmelCase      )
		return text, ids







	def 			_a (	self   :				int      )		->			Optional[Any]:
		"""simple docstring"""







		__lowercase   							=	"""<pad>"""
		__lowercase   							=	1

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







	def 			_a (	self   :				str      )		->			Any:
		"""simple docstring"""







		__lowercase   							=	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 			_a (	self   :				List[Any]      )		->			str:
		"""simple docstring"""







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







	def 			_a (	self   :				str      )		->			Union[str, Any]:
		"""simple docstring"""







		__lowercase   							=	self.get_tokenizers(do_lower_case=_lowerCAmelCase      )
		for tokenizer in tokenizers:
			with self.subTest(F'{tokenizer.__class__.__name__}'      ):
				__lowercase   							=	tokenizer.vocab_size
				__lowercase   							=	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)

				__lowercase   							=	["""aaaaa bbbbbb""", """cccccccccdddddddd"""]
				__lowercase   							=	tokenizer.add_tokens(_lowerCAmelCase      )
				__lowercase   							=	tokenizer.vocab_size
				__lowercase   							=	len(_lowerCAmelCase      )

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

				__lowercase   							=	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      )

				__lowercase   							=	{"""eos_token""": """>>>>|||<||<<|<<""", """pad_token""": """<<<<<|||>|>>>>|>"""}
				__lowercase   							=	tokenizer.add_special_tokens(_lowerCAmelCase      )
				__lowercase   							=	tokenizer.vocab_size
				__lowercase   							=	len(_lowerCAmelCase      )

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

				__lowercase   							=	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 			_a (	self   :				Union[str, Any]      )		->			Optional[int]:
		"""simple docstring"""







		pass







	def 			_a (	self   :				Any      )		->			Any:
		"""simple docstring"""







		pass







	def 			_a (	self   :				Optional[Any]      )		->			Any:
		"""simple docstring"""







		__lowercase   							=	self.get_tokenizer()

		__lowercase   							=	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]							,					)

		__lowercase   							=	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""", """."""]      )

		__lowercase   							=	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

		__lowercase   							=	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 			_a (	self   :				str      )		->			Union[str, Any]:
		"""simple docstring"""







		__lowercase   							=	[
		    """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   							=	{
		    """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							,					)









class 					A__     :

     '''simple docstring'''






     def __init__( self      :    Optional[int]   ,						_SCREAMING_SNAKE_CASE      :    str = ""   ,						_SCREAMING_SNAKE_CASE      :    bool = False ):






           """simple docstring"""




           UpperCamelCase					       =  {}

           # A node will be a leaf if the tree contains its word
           UpperCamelCase					       =  is_leaf

           UpperCamelCase					       =  prefix







     def   _SCREAMING_SNAKE_CASE     ( self      :    Optional[int]   ,						_SCREAMING_SNAKE_CASE      :    str ):






           """simple docstring"""




           UpperCamelCase					       =  0
           for q, w in zip(self.prefix   ,						_SCREAMING_SNAKE_CASE ):
                 if q != w:
                       break

                 x += 1

           return self.prefix[:x], self.prefix[x:], word[x:]







     def   _SCREAMING_SNAKE_CASE     ( self      :    Any   ,						_SCREAMING_SNAKE_CASE      :    list[str] ):






           """simple docstring"""




           for word in words:
                 self.insert(_SCREAMING_SNAKE_CASE )







     def   _SCREAMING_SNAKE_CASE     ( self      :    Union[str, Any]   ,						_SCREAMING_SNAKE_CASE      :    str ):






           """simple docstring"""




           if self.prefix == word:
                 UpperCamelCase					       =  True

           # Case 2: The node has no edges that have a prefix to the word
           # Solution: We create an edge from the current node to a new one
           # containing the word
           elif word[0] not in self.nodes:
                 UpperCamelCase					       =  RadixNode(prefix=_SCREAMING_SNAKE_CASE   ,						is_leaf=_SCREAMING_SNAKE_CASE )

           else:
                 UpperCamelCase					       =  self.nodes[word[0]]
                 UpperCamelCase       ,  UpperCamelCase       ,  UpperCamelCase					       =  incoming_node.match(
                     _SCREAMING_SNAKE_CASE )

                 # Case 3: The node prefix is equal to the matching
                 # Solution: We insert remaining word on the next node
                 if remaining_prefix == "":
                       self.nodes[matching_string[0]].insert(_SCREAMING_SNAKE_CASE )

                 # Case 4: The word is greater equal to the matching
                 # Solution: Create a node in between both nodes, change
                 # prefixes and add the new node for the remaining word
                 else:
                       UpperCamelCase					       =  remaining_prefix

                       UpperCamelCase					       =  self.nodes[matching_string[0]]
                       UpperCamelCase					       =  RadixNode(_SCREAMING_SNAKE_CASE   ,						_SCREAMING_SNAKE_CASE )
                       UpperCamelCase					       =  aux_node

                       if remaining_word == "":
                             UpperCamelCase					       =  True
                       else:
                             self.nodes[matching_string[0]].insert(_SCREAMING_SNAKE_CASE )







     def   _SCREAMING_SNAKE_CASE     ( self      :    Any   ,						_SCREAMING_SNAKE_CASE      :    str ):






           """simple docstring"""




           UpperCamelCase					       =  self.nodes.get(word[0]   ,						_SCREAMING_SNAKE_CASE )
           if not incoming_node:
                 return False
           else:
                 UpperCamelCase       ,  UpperCamelCase       ,  UpperCamelCase					       =  incoming_node.match(
                     _SCREAMING_SNAKE_CASE )
                 # If there is remaining prefix, the word can't be on the tree
                 if remaining_prefix != "":
                       return False
                 # This applies when the word and the prefix are equal
                 elif remaining_word == "":
                       return incoming_node.is_leaf
                 # We have word remaining so we check the next node
                 else:
                       return incoming_node.find(_SCREAMING_SNAKE_CASE )







     def   _SCREAMING_SNAKE_CASE     ( self      :    List[Any]   ,						_SCREAMING_SNAKE_CASE      :    str ):






           """simple docstring"""




           UpperCamelCase					       =  self.nodes.get(word[0]   ,						_SCREAMING_SNAKE_CASE )
           if not incoming_node:
                 return False
           else:
                 UpperCamelCase       ,  UpperCamelCase       ,  UpperCamelCase					       =  incoming_node.match(
                     _SCREAMING_SNAKE_CASE )
                 # If there is remaining prefix, the word can't be on the tree
                 if remaining_prefix != "":
                       return False
                 # We have word remaining so we check the next node
                 elif remaining_word != "":
                       return incoming_node.delete(_SCREAMING_SNAKE_CASE )
                 else:
                       # If it is not a leaf, we don't have to delete
                       if not incoming_node.is_leaf:
                             return False
                       else:
                             # We delete the nodes if no edges go from it
                             if len(incoming_node.nodes ) == 0:
                                   del self.nodes[word[0]]
                                   # We merge the current node with its only child
                                   if len(self.nodes ) == 1 and not self.is_leaf:
                                         UpperCamelCase					       =  list(self.nodes.values() )[0]
                                         UpperCamelCase					       =  merging_node.is_leaf
                                         self.prefix += merging_node.prefix
                                         UpperCamelCase					       =  merging_node.nodes
                    # If there is more than 1 edge, we just mark it as non-leaf
                             elif len(incoming_node.nodes ) > 1:
                                   UpperCamelCase					       =  False
                             # If there is 1 edge, we merge it with its child
                             else:
                                   UpperCamelCase					       =  list(incoming_node.nodes.values() )[0]
                                   UpperCamelCase					       =  merging_node.is_leaf
                                   incoming_node.prefix += merging_node.prefix
                                   UpperCamelCase					       =  merging_node.nodes

                             return True







     def   _SCREAMING_SNAKE_CASE     ( self      :    Tuple   ,						_SCREAMING_SNAKE_CASE      :    int = 0 ):






           """simple docstring"""




           if self.prefix != "":
                 print('-' * height   ,						self.prefix   ,						'  (leaf)' if self.is_leaf else '' )

           for value in self.nodes.values():
                 value.print_tree(height + 1 )

def 		lowercase__  (				) ->			bool:
      """simple docstring"""

      UpperCamelCase					       =  'banana bananas bandana band apple all beast'.split()
      UpperCamelCase					       =  RadixNode()
      root.insert_many(_UpperCamelCase)

      assert all(root.find(_UpperCamelCase) for word in words)
      assert not root.find('bandanas')
      assert not root.find('apps')
      root.delete('all')
      assert not root.find('all')
      root.delete('banana')
      assert not root.find('banana')
      assert root.find('bananas')

      return True
def 		lowercase__  (				) ->			None:
      """simple docstring"""

      assert test_trie()
def 		lowercase__  (				) ->			None:
      """simple docstring"""

      UpperCamelCase					       =  RadixNode()
      UpperCamelCase					       =  'banana bananas bandanas bandana band apple all beast'.split()
      root.insert_many(_UpperCamelCase)

      print('Words:'       ,							_UpperCamelCase)
      print('Tree:')
      root.print_tree()


if __name__ == "__main__":
       main()



