


'''simple docstring'''
import unittest
from pathlib import Path
from shutil import copyfile

from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCAB_FILES_NAMES, save_json
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow

from ...test_tokenization_common import TokenizerTesterMixin


__snake_case							   =  get_tests_dir('''fixtures/test_sentencepiece.model''')

if is_sentencepiece_available():
		import sentencepiece as sp


__snake_case							   =  5
__snake_case							   =  10
@require_sentencepiece
@require_tokenizers
class      lowercase			(							A__			,	unittest.TestCase      ):

		"""simple docstring"""

		_a									=       SpeechaTextTokenizer
		_a									=       False
		_a									=       True




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							super().setUp()

							UpperCamelCase__     :Optional[Any]							      =				sp.SentencePieceProcessor()
							spm_model.Load(UpperCamelCase_							)
							UpperCamelCase__     :Union[str, Any]							      =				['''<s>''', '''<pad>''', '''</s>''', '''<unk>''']

							vocab += [spm_model.IdToPiece(id_							) for id_ in range(len(UpperCamelCase_							)							)]
							UpperCamelCase__     :List[Any]							      =				dict(zip(UpperCamelCase_					,     range(len(UpperCamelCase_							)							)							)							)

							UpperCamelCase__     :int							      =				Path(self.tmpdirname							)
							save_json(UpperCamelCase_					,     save_dir / VOCAB_FILES_NAMES['''vocab_file''']							)
							if not (save_dir / VOCAB_FILES_NAMES["spm_file"]).exists():
												copyfile(UpperCamelCase_					,     save_dir / VOCAB_FILES_NAMES['''spm_file''']							)

							UpperCamelCase__     :Dict							      =				SpeechaTextTokenizer.from_pretrained(self.tmpdirname							)
							tokenizer.save_pretrained(self.tmpdirname							)




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							UpperCamelCase__     :int							      =				'''<pad>'''
							UpperCamelCase__     :Optional[int]							      =				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							):

							'''simple docstring'''


							UpperCamelCase__     :Any							      =				list(self.get_tokenizer().get_vocab().keys()							)

							self.assertEqual(vocab_keys[0]					,     '''<s>'''							)
							self.assertEqual(vocab_keys[1]					,     '''<pad>'''							)
							self.assertEqual(vocab_keys[-1]					,     '''j'''							)
							self.assertEqual(len(UpperCamelCase_							)					,     1001							)




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							self.assertEqual(self.get_tokenizer().vocab_size					,     1001							)




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							UpperCamelCase__     :int							      =				SpeechaTextTokenizer.from_pretrained(self.tmpdirname							)

							UpperCamelCase__     :str							      =				tokenizer.tokenize('''This is a test'''							)
							self.assertListEqual(UpperCamelCase_					,     ['''▁This''', '''▁is''', '''▁a''', '''▁t''', '''est''']							)

							self.assertListEqual(
							    tokenizer.convert_tokens_to_ids(UpperCamelCase_							)					,     [289, 50, 14, 174, 386]					,     )

							UpperCamelCase__     :str							      =				tokenizer.tokenize('''I was born in 92000, and this is falsé.'''							)
							self.assertListEqual(
							    UpperCamelCase_					,     [SPIECE_UNDERLINE + '''I''', SPIECE_UNDERLINE + '''was''', SPIECE_UNDERLINE + '''b''', '''or''', '''n''', SPIECE_UNDERLINE + '''in''', SPIECE_UNDERLINE + '''''', '''9''', '''2''', '''0''', '''0''', '''0''', ''',''', SPIECE_UNDERLINE + '''and''', SPIECE_UNDERLINE + '''this''', SPIECE_UNDERLINE + '''is''', SPIECE_UNDERLINE + '''f''', '''al''', '''s''', '''é''', '''.''']					,     )
							UpperCamelCase__     :List[Any]							      =				tokenizer.convert_tokens_to_ids(UpperCamelCase_							)
							self.assertListEqual(UpperCamelCase_					,     [12, 25, 88, 59, 28, 23, 11, 4, 606, 351, 351, 351, 7, 16, 70, 50, 76, 84, 10, 4, 8]							)

							UpperCamelCase__     :Union[str, Any]							      =				tokenizer.convert_ids_to_tokens(UpperCamelCase_							)
							self.assertListEqual(
							    UpperCamelCase_					,     [SPIECE_UNDERLINE + '''I''', SPIECE_UNDERLINE + '''was''', SPIECE_UNDERLINE + '''b''', '''or''', '''n''', SPIECE_UNDERLINE + '''in''', SPIECE_UNDERLINE + '''''', '''<unk>''', '''2''', '''0''', '''0''', '''0''', ''',''', SPIECE_UNDERLINE + '''and''', SPIECE_UNDERLINE + '''this''', SPIECE_UNDERLINE + '''is''', SPIECE_UNDERLINE + '''f''', '''al''', '''s''', '''<unk>''', '''.''']					,     )




		@slow
		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							UpperCamelCase__     :Dict							      =				{'''input_ids''': [[3791, 797, 31, 11, 64, 797, 31, 2429, 433, 12, 1176, 12, 20, 786, 915, 142, 2413, 240, 37, 3238, 797, 31, 11, 35, 93, 915, 142, 2413, 240, 37, 5540, 567, 1276, 93, 37, 610, 40, 62, 455, 657, 1042, 123, 780, 177, 37, 309, 241, 1298, 514, 20, 292, 2737, 114, 2469, 241, 85, 64, 302, 548, 528, 423, 4, 509, 406, 423, 37, 601, 4, 777, 302, 548, 528, 423, 284, 4, 3388, 511, 459, 4, 3555, 40, 321, 302, 705, 4, 3388, 511, 583, 326, 5, 5, 5, 62, 3310, 560, 177, 2680, 217, 1508, 32, 31, 853, 418, 64, 583, 511, 1605, 62, 35, 93, 560, 177, 2680, 217, 1508, 1521, 64, 583, 511, 519, 62, 20, 1515, 764, 20, 149, 261, 5625, 7972, 20, 5540, 567, 1276, 93, 3925, 1675, 11, 15, 802, 7972, 576, 217, 1508, 11, 35, 93, 1253, 2441, 15, 289, 652, 31, 416, 321, 3842, 115, 40, 911, 8, 476, 619, 4, 380, 142, 423, 335, 240, 35, 93, 264, 8, 11, 335, 569, 420, 163, 5, 2], [260, 548, 528, 423, 20, 451, 20, 2681, 1153, 3434, 20, 5540, 37, 567, 126, 1253, 2441, 3376, 449, 210, 431, 1563, 177, 767, 5540, 11, 1203, 472, 11, 2953, 685, 285, 364, 706, 1153, 20, 6799, 20, 2869, 20, 4464, 126, 40, 2429, 20, 1040, 866, 2664, 418, 20, 318, 20, 1726, 186, 20, 265, 522, 35, 93, 2191, 4634, 20, 1040, 12, 6799, 15, 228, 2356, 142, 31, 11, 5, 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], [2575, 2666, 684, 1582, 1176, 12, 627, 149, 619, 20, 4902, 563, 11, 20, 149, 261, 3420, 2356, 174, 142, 4714, 131, 5, 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]], '''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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 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, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
							# fmt: on

							self.tokenizer_integration_test_util(
							    expected_encoding=UpperCamelCase_					,     model_name='''facebook/s2t-small-mustc-en-de-st'''					,     revision='''a14f04cf0776c02f62a8cb800cf7909e15ea23ad'''					,     )



@require_sentencepiece
class      lowercase			(							unittest.TestCase      ):

		"""simple docstring"""

		_a									=       'valhalla/s2t_mustc_multilinguial_medium'

		_a									=       'C\'est trop cool'
		_a									=       'Esto es genial'




		@classmethod
		def 					lowerCAmelCase__       (	cls							):

							'''simple docstring'''


							UpperCamelCase__     :SpeechaTextTokenizer							      =				SpeechaTextTokenizer.from_pretrained(cls.checkpoint_name							)
							return cls




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							self.assertEqual(self.tokenizer.lang_code_to_id['''pt''']					,     4							)
							self.assertEqual(self.tokenizer.lang_code_to_id['''ru''']					,     6							)
							self.assertEqual(self.tokenizer.lang_code_to_id['''it''']					,     9							)
							self.assertEqual(self.tokenizer.lang_code_to_id['''de''']					,     11							)




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							self.assertEqual(self.tokenizer.vocab_size					,     10000							)




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							self.assertIn(UpperCamelCase_					,     self.tokenizer.all_special_ids							)
							UpperCamelCase__     :List[Any]							      =				[ES_CODE, 4, 1601, 47, 7647, 2]
							UpperCamelCase__     :List[str]							      =				self.tokenizer.decode(UpperCamelCase_					,     skip_special_tokens=UpperCamelCase_							)
							UpperCamelCase__     :Optional[int]							      =				self.tokenizer.decode(generated_ids[1:]					,     skip_special_tokens=UpperCamelCase_							)
							self.assertEqual(UpperCamelCase_					,     UpperCamelCase_							)
							self.assertNotIn(self.tokenizer.eos_token					,     UpperCamelCase_							)




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							UpperCamelCase__     :Tuple							      =				'''fr'''
							UpperCamelCase__     :List[Any]							      =				self.tokenizer(self.french_text							).input_ids
							self.assertEqual(encoded[0]					,     UpperCamelCase_							)
							self.assertEqual(encoded[-1]					,     self.tokenizer.eos_token_id							)




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							UpperCamelCase__     :Optional[int]							      =				'''fr'''
							self.assertListEqual(self.tokenizer.prefix_tokens					,     [FR_CODE]							)

							UpperCamelCase__     :Optional[Any]							      =				'''es'''
							self.assertListEqual(self.tokenizer.prefix_tokens					,     [ES_CODE]							)



'''simple docstring'''
import tempfile
import unittest

from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.testing_utils import (
    is_torch_available,
    require_optimum,
    require_torch,
    slow,
)


if is_torch_available():
		import torch
@require_torch
@require_optimum
@slow
class      lowercase			(							unittest.TestCase      ):

		"""simple docstring"""

		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							UpperCamelCase__     :Tuple							      =				'''hf-internal-testing/tiny-random-t5'''
							UpperCamelCase__     :int							      =				AutoTokenizer.from_pretrained(UpperCamelCase_							)
							UpperCamelCase__     :int							      =				AutoModelForSeqaSeqLM.from_pretrained(UpperCamelCase_							)

							UpperCamelCase__     :int							      =				tokenizer('''This is me'''					,     return_tensors='''pt'''							)

							UpperCamelCase__     :Optional[int]							      =				model.to_bettertransformer()

							self.assertTrue(any('''BetterTransformer''' in mod.__class__.__name__ for _, mod in model.named_modules()							)							)

							UpperCamelCase__     :int							      =				model.generate(**UpperCamelCase_							)

							UpperCamelCase__     :Optional[Any]							      =				model.reverse_bettertransformer()

							self.assertFalse(any('''BetterTransformer''' in mod.__class__.__name__ for _, mod in model.named_modules()							)							)

							with tempfile.TemporaryDirectory() as tmpdirname:
												model.save_pretrained(UpperCamelCase_							)

												UpperCamelCase__     :Tuple							      =				AutoModelForSeqaSeqLM.from_pretrained(UpperCamelCase_							)

												self.assertFalse(
												    any('''BetterTransformer''' in mod.__class__.__name__ for _, mod in model_reloaded.named_modules()							)							)

												UpperCamelCase__     :Tuple							      =				model_reloaded.generate(**UpperCamelCase_							)
												self.assertTrue(torch.allclose(UpperCamelCase_					,     UpperCamelCase_							)							)




		def 					lowerCAmelCase__       (	self							):

							'''simple docstring'''


							UpperCamelCase__     :List[Any]							      =				'''hf-internal-testing/tiny-random-t5'''
							UpperCamelCase__     :Dict							      =				AutoModelForSeqaSeqLM.from_pretrained(UpperCamelCase_							)

							UpperCamelCase__     :Union[str, Any]							      =				model.to_bettertransformer()

							with tempfile.TemporaryDirectory() as tmpdirname:
												with self.assertRaises(UpperCamelCase_							):
																	model.save_pretrained(UpperCamelCase_							)

												UpperCamelCase__     :Tuple							      =				model.reverse_bettertransformer()
												model.save_pretrained(UpperCamelCase_							)