


'''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


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






@require_sentencepiece
@require_tokenizers
class 		lowerCAmelCase__	(	UpperCAmelCase__			,				unittest.TestCase		):
			lowerCAmelCase       :		List[Any]				      =   SpeechTaTokenizer
			lowerCAmelCase       :		Optional[int]				      =   False
			lowerCAmelCase       :		str				      =   True




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



					'''simple docstring'''







					super().setUp()

					# We have a SentencePiece fixture for testing
					_UpperCAmelCase						:				Any	    =					SpeechTaTokenizer(lowerCamelCase__       )

					_UpperCAmelCase						:				Any	    =					AddedToken("<mask>"		,     lstrip=lowerCamelCase__		,     rstrip=lowerCamelCase__       )
					_UpperCAmelCase						:				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]		,     lowerCamelCase__     :   Optional[int]       )      ->str:



					'''simple docstring'''







					_UpperCAmelCase						:				str	    =					"this is a test"
					_UpperCAmelCase						:				Any	    =					"this is a test"
					return input_text, output_text




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



					'''simple docstring'''







					_UpperCAmelCase    ,			_UpperCAmelCase						:				str	    =					self.get_input_output_texts(lowerCamelCase__       )
					_UpperCAmelCase						:				Any	    =					tokenizer.encode(lowerCamelCase__		,     add_special_tokens=lowerCamelCase__       )
					_UpperCAmelCase						:				Union[str, Any]	    =					tokenizer.decode(lowerCamelCase__		,     clean_up_tokenization_spaces=lowerCamelCase__       )
					return text, ids




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



					'''simple docstring'''







					_UpperCAmelCase						:				Any	    =					"<pad>"
					_UpperCAmelCase						:				Optional[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     :   str       )      ->List[str]:



					'''simple docstring'''







					_UpperCAmelCase						:				int	    =					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     :   Union[str, Any]       )      ->Dict:



					'''simple docstring'''







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




			def 							lowerCAmelCase__			(						self     :   List[str]       )      ->Dict:



					'''simple docstring'''







					_UpperCAmelCase						:				int	    =					self.get_tokenizers(do_lower_case=lowerCamelCase__       )
					for tokenizer in tokenizers:
							with self.subTest(F"""{tokenizer.__class__.__name__}"""       ):
									_UpperCAmelCase						:				List[str]	    =					tokenizer.vocab_size
									_UpperCAmelCase						:				Optional[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)

									_UpperCAmelCase						:				str	    =					["aaaaa bbbbbb", "cccccccccdddddddd"]
									_UpperCAmelCase						:				Optional[int]	    =					tokenizer.add_tokens(lowerCamelCase__       )
									_UpperCAmelCase						:				Optional[int]	    =					tokenizer.vocab_size
									_UpperCAmelCase						:				Dict	    =					len(lowerCamelCase__       )

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

									_UpperCAmelCase						:				Union[str, 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       )

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

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

									_UpperCAmelCase						:				str	    =					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     :   List[str]       )      ->Union[str, Any]:



					'''simple docstring'''







					pass




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



					'''simple docstring'''







					pass




			def 							lowerCAmelCase__			(						self     :   Optional[Any]       )      ->List[Any]:



					'''simple docstring'''







					_UpperCAmelCase						:				List[Any]	    =					self.get_tokenizer()

					_UpperCAmelCase						:				List[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]		,     )

					_UpperCAmelCase						:				Tuple	    =					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", "."]       )

					_UpperCAmelCase						:				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

					_UpperCAmelCase						:				Any	    =					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]       )      ->List[str]:



					'''simple docstring'''







					_UpperCAmelCase						:				Tuple	    =					[
					    "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
					_UpperCAmelCase						:				List[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": [
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					    ]
					}
					# fmt: on

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







'''simple docstring'''


def        __lowerCAmelCase       (__lowerCAmelCase					,       __lowerCAmelCase      ):

		if density <= 0:
				raise ValueError("Impossible fluid density"      )
		if bulk_modulus <= 0:
				raise ValueError("Impossible bulk modulus"      )

		return (bulk_modulus / density) ** 0.5


if __name__ == "__main__":
						import doctest

						doctest.testmod()



