




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


UpperCamelCase__ :   Tuple						=							get_tests_dir('''fixtures/test_sentencepiece.model''')

if is_sentencepiece_available():
						import sentencepiece as sp


UpperCamelCase__ :   int						=							5
UpperCamelCase__ :   Tuple						=							10







@require_sentencepiece
@require_tokenizers
class 				lowerCAmelCase_       (					lowerCamelCase_						,     unittest.TestCase							):
				__a     :       List[str]						=     SpeechaTextTokenizer
				__a     :       Dict						=     False
				__a     :       str						=     True






				def 		snake_case	(			self ):
							super().setUp()

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

							vocab += [spm_model.IdToPiece(id_ ) for id_ in range(len(snake_case__ ) )]
							SCREAMING_SNAKE_CASE_   : Dict					  =      dict(zip(snake_case__      ,range(len(snake_case__ ) ) ) )

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

							SCREAMING_SNAKE_CASE_   : Optional[int]					  =      SpeechaTextTokenizer.from_pretrained(self.tmpdirname )
							tokenizer.save_pretrained(self.tmpdirname )






				def 		snake_case	(			self ):
							SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      '<pad>'
							SCREAMING_SNAKE_CASE_   : List[str]					  =      1

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






				def 		snake_case	(			self ):
							SCREAMING_SNAKE_CASE_   : Optional[int]					  =      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(snake_case__ )      ,1001 )






				def 		snake_case	(			self ):
							self.assertEqual(self.get_tokenizer().vocab_size      ,1001 )






				def 		snake_case	(			self ):
							SCREAMING_SNAKE_CASE_   : Tuple					  =      SpeechaTextTokenizer.from_pretrained(self.tmpdirname )

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

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

							SCREAMING_SNAKE_CASE_   : Dict					  =      tokenizer.tokenize('I was born in 92000, and this is falsé.' )
							self.assertListEqual(
							    snake_case__      ,[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', '.']      ,)
							SCREAMING_SNAKE_CASE_   : int					  =      tokenizer.convert_tokens_to_ids(snake_case__ )
							self.assertListEqual(snake_case__      ,[12, 25, 88, 59, 28, 23, 11, 4, 606, 351, 351, 351, 7, 16, 70, 50, 76, 84, 10, 4, 8] )

							SCREAMING_SNAKE_CASE_   : Optional[Any]					  =      tokenizer.convert_ids_to_tokens(snake_case__ )
							self.assertListEqual(
							    snake_case__      ,[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 		snake_case	(			self ):
							# fmt: off
							SCREAMING_SNAKE_CASE_   : 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=snake_case__      ,model_name='facebook/s2t-small-mustc-en-de-st'      ,revision='a14f04cf0776c02f62a8cb800cf7909e15ea23ad'      ,)







@require_sentencepiece
class 				lowerCAmelCase_       (					unittest.TestCase							):
				__a     :       Tuple						=     "valhalla/s2t_mustc_multilinguial_medium"

				__a     :       List[Any]						=     "C'est trop cool"
				__a     :       Dict						=     "Esto es genial"






				@classmethod
				def 		snake_case	(			cls ):
							SCREAMING_SNAKE_CASE_   : SpeechaTextTokenizer					  =      SpeechaTextTokenizer.from_pretrained(cls.checkpoint_name )
							return cls






				def 		snake_case	(			self ):
							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 		snake_case	(			self ):
							self.assertEqual(self.tokenizer.vocab_size      ,10000 )






				def 		snake_case	(			self ):
							self.assertIn(snake_case__      ,self.tokenizer.all_special_ids )
							SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      [ES_CODE, 4, 1601, 47, 7647, 2]
							SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      self.tokenizer.decode(snake_case__      ,skip_special_tokens=snake_case__ )
							SCREAMING_SNAKE_CASE_   : Tuple					  =      self.tokenizer.decode(generated_ids[1:]      ,skip_special_tokens=snake_case__ )
							self.assertEqual(snake_case__      ,snake_case__ )
							self.assertNotIn(self.tokenizer.eos_token      ,snake_case__ )






				def 		snake_case	(			self ):
							SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      'fr'
							SCREAMING_SNAKE_CASE_   : List[str]					  =      self.tokenizer(self.french_text ).input_ids
							self.assertEqual(encoded[0]      ,snake_case__ )
							self.assertEqual(encoded[-1]      ,self.tokenizer.eos_token_id )






				def 		snake_case	(			self ):
							SCREAMING_SNAKE_CASE_   : Union[str, Any]					  =      'fr'
							self.assertListEqual(self.tokenizer.prefix_tokens      ,[FR_CODE] )

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









import os
from shutil import copyfile
from typing import List, Optional, Tuple

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
						from .tokenization_barthez import BarthezTokenizer
else:
						UpperCamelCase__ :   Dict						=							None

UpperCamelCase__ :   Tuple						=							logging.get_logger(__name__)

UpperCamelCase__ :   Union[str, Any]						=							{'''vocab_file''': '''sentencepiece.bpe.model''', '''tokenizer_file''': '''tokenizer.json'''}

UpperCamelCase__ :   Dict						=							{
    '''vocab_file''': {
        '''moussaKam/mbarthez''': '''https://huggingface.co/moussaKam/mbarthez/resolve/main/sentencepiece.bpe.model''',
        '''moussaKam/barthez''': '''https://huggingface.co/moussaKam/barthez/resolve/main/sentencepiece.bpe.model''',
        '''moussaKam/barthez-orangesum-title''': (
            '''https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/sentencepiece.bpe.model'''
        ),
    },
    '''tokenizer_file''': {
        '''moussaKam/mbarthez''': '''https://huggingface.co/moussaKam/mbarthez/resolve/main/tokenizer.json''',
        '''moussaKam/barthez''': '''https://huggingface.co/moussaKam/barthez/resolve/main/tokenizer.json''',
        '''moussaKam/barthez-orangesum-title''': (
            '''https://huggingface.co/moussaKam/barthez-orangesum-title/resolve/main/tokenizer.json'''
        ),
    },
}

UpperCamelCase__ :   Dict						=							{
    '''moussaKam/mbarthez''': 10_24,
    '''moussaKam/barthez''': 10_24,
    '''moussaKam/barthez-orangesum-title''': 10_24,
}

UpperCamelCase__ :   Any						=							'''▁'''







class 				lowerCAmelCase_       (					lowerCamelCase_							):
				__a     :       List[str]						=     VOCAB_FILES_NAMES
				__a     :       int						=     PRETRAINED_VOCAB_FILES_MAP
				__a     :       Optional[int]						=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				__a     :       List[Any]						=     ["input_ids", "attention_mask"]
				__a     :       Dict						=     BarthezTokenizer






				def __init__(			self      ,snake_case__=None      ,snake_case__=None      ,snake_case__="<s>"      ,snake_case__="</s>"      ,snake_case__="</s>"      ,snake_case__="<s>"      ,snake_case__="<unk>"      ,snake_case__="<pad>"      ,snake_case__="<mask>"      ,**snake_case__      ,):
							# Mask token behave like a normal word, i.e. include the space before it
							SCREAMING_SNAKE_CASE_   : str					  =      AddedToken(snake_case__      ,lstrip=snake_case__      ,rstrip=snake_case__ ) if isinstance(snake_case__      ,snake_case__ ) else mask_token

							super().__init__(
							    snake_case__      ,tokenizer_file=snake_case__      ,bos_token=snake_case__      ,eos_token=snake_case__      ,unk_token=snake_case__      ,sep_token=snake_case__      ,cls_token=snake_case__      ,pad_token=snake_case__      ,mask_token=snake_case__      ,**snake_case__      ,)

							SCREAMING_SNAKE_CASE_   : List[Any]					  =      vocab_file
							SCREAMING_SNAKE_CASE_   : int					  =      False if not self.vocab_file else True






				def 		snake_case	(			self      ,snake_case__      ,snake_case__ = None ):

							if token_ids_a is None:
										return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
							SCREAMING_SNAKE_CASE_   : List[str]					  =      [self.cls_token_id]
							SCREAMING_SNAKE_CASE_   : Optional[int]					  =      [self.sep_token_id]
							return cls + token_ids_a + sep + sep + token_ids_a + sep






				def 		snake_case	(			self      ,snake_case__      ,snake_case__ = None ):
							SCREAMING_SNAKE_CASE_   : Dict					  =      [self.sep_token_id]
							SCREAMING_SNAKE_CASE_   : Any					  =      [self.cls_token_id]

							if token_ids_a is None:
										return len(cls + token_ids_a + sep ) * [0]
							return len(cls + token_ids_a + sep + sep + token_ids_a + sep ) * [0]






				def 		snake_case	(			self      ,snake_case__      ,snake_case__ = None ):
							if not self.can_save_slow_tokenizer:
										raise ValueError(
										    'Your fast tokenizer does not have the necessary information to save the vocabulary for a slow '
										    'tokenizer.' )

							if not os.path.isdir(snake_case__ ):
										logger.error(F'Vocabulary path ({save_directory}) should be a directory' )
										return
							SCREAMING_SNAKE_CASE_   : Optional[Any]					  =      os.path.join(
							    snake_case__      ,(filename_prefix + '-' if filename_prefix else '') + VOCAB_FILES_NAMES['vocab_file'] )

							if os.path.abspath(self.vocab_file ) != os.path.abspath(snake_case__ ):
										copyfile(self.vocab_file      ,snake_case__ )

							return (out_vocab_file,)



