





'''simple docstring'''



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_rembert import RemBertTokenizer
else:
							lowerCAmelCase_     :       Union[str, Any]								=						None

lowerCAmelCase_     :       Dict								=						logging.get_logger(__name__)
lowerCAmelCase_     :       int								=						{'vocab_file': 'sentencepiece.model', 'tokenizer_file': 'tokenizer.json'}

lowerCAmelCase_     :       Any								=						{
    'vocab_file': {
        'google/rembert': 'https://huggingface.co/google/rembert/resolve/main/sentencepiece.model',
    },
    'tokenizer_file': {
        'google/rembert': 'https://huggingface.co/google/rembert/resolve/main/tokenizer.json',
    },
}

lowerCAmelCase_     :       Optional[Any]								=						{
    'google/rembert': 256,
}

lowerCAmelCase_     :       Tuple								=						'▁'
class 	lowerCamelCase_							(					snake_case_			):
						_lowerCAmelCase     :   List[Any]	     =				VOCAB_FILES_NAMES
						_lowerCAmelCase     :   List[str]	     =				PRETRAINED_VOCAB_FILES_MAP
						_lowerCAmelCase     :   Dict	     =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						_lowerCAmelCase     :   Union[str, Any]	     =				RemBertTokenizer







						def __init__(  self   :      Union[str, Any]				,    lowerCAmelCase__   :      Union[str, Any]=None				,    lowerCAmelCase__   :      str=None				,    lowerCAmelCase__   :      List[str]=True				,    lowerCAmelCase__   :      Optional[Any]=True				,    lowerCAmelCase__   :      Union[str, Any]=False				,    lowerCAmelCase__   :      int="[CLS]"				,    lowerCAmelCase__   :      Dict="[SEP]"				,    lowerCAmelCase__   :      Optional[Any]="<unk>"				,    lowerCAmelCase__   :      Union[str, Any]="[SEP]"				,    lowerCAmelCase__   :      List[Any]="<pad>"				,    lowerCAmelCase__   :      Union[str, Any]="[CLS]"				,    lowerCAmelCase__   :      List[Any]="[MASK]"				,    **lowerCAmelCase__   :      Union[str, Any]				,    ):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			AddedToken(lowerCAmelCase__				,    lstrip=lowerCAmelCase__				,    rstrip=lowerCAmelCase__				) if isinstance(lowerCAmelCase__				,    lowerCAmelCase__				) else mask_token

													super().__init__(
													    lowerCAmelCase__				,    tokenizer_file=lowerCAmelCase__				,    do_lower_case=lowerCAmelCase__				,    remove_space=lowerCAmelCase__				,    keep_accents=lowerCAmelCase__				,    bos_token=lowerCAmelCase__				,    eos_token=lowerCAmelCase__				,    unk_token=lowerCAmelCase__				,    sep_token=lowerCAmelCase__				,    pad_token=lowerCAmelCase__				,    cls_token=lowerCAmelCase__				,    mask_token=lowerCAmelCase__				,    **lowerCAmelCase__				,    )

													SCREAMING_SNAKE_CASE					:      Tuple     					=			do_lower_case
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			remove_space
													SCREAMING_SNAKE_CASE					:      Any     					=			keep_accents
													SCREAMING_SNAKE_CASE					:      List[Any]     					=			vocab_file
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			False if not self.vocab_file else True







						def 					__lowercase    (  self   :      List[Any]				,    lowerCAmelCase__   :      List[int]				,    lowerCAmelCase__   :      Optional[List[int]] = None				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Tuple     					=			[self.sep_token_id]
													SCREAMING_SNAKE_CASE					:      List[Any]     					=			[self.cls_token_id]
													if token_ids_a is None:
																				return cls + token_ids_a + sep
													return cls + token_ids_a + sep + token_ids_a + sep







						def 					__lowercase    (  self   :      Dict				,    lowerCAmelCase__   :      List[int]				,    lowerCAmelCase__   :      Optional[List[int]] = None				,    lowerCAmelCase__   :      bool = False				):

													"""simple docstring"""

													if already_has_special_tokens:
																				if token_ids_a is not None:
																											raise ValueError(
																											    '''You should not supply a second sequence if the provided sequence of '''
																											    '''ids is already formatted with special tokens for the model.'''				)
																				return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

													if token_ids_a is not None:
																				return [1] + ([0] * len(lowerCAmelCase__				)) + [1] + ([0] * len(lowerCAmelCase__				)) + [1]
													return [1] + ([0] * len(lowerCAmelCase__				)) + [1]







						def 					__lowercase    (  self   :      Any				,    lowerCAmelCase__   :      List[int]				,    lowerCAmelCase__   :      Optional[List[int]] = None				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      int     					=			[self.sep_token_id]
													SCREAMING_SNAKE_CASE					:      int     					=			[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				) * [0] + len(token_ids_a + sep				) * [1]







						def 					__lowercase    (  self   :      List[Any]				,    lowerCAmelCase__   :      str				,    lowerCAmelCase__   :      Optional[str] = None				):

													"""simple docstring"""
													if not os.path.isdir(lowerCAmelCase__				):
																				logger.error('''Vocabulary path ({}) should be a directory'''.format(lowerCAmelCase__				)				)
																				return
													SCREAMING_SNAKE_CASE					:      str     					=			os.path.join(
													    lowerCAmelCase__				,    (filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']				)

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

													return (out_vocab_file,)









'''simple docstring'''



import shutil
import tempfile
import unittest

from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio

from .test_feature_extraction_clap import floats_list
@require_torchaudio
@require_sentencepiece
class 	lowerCamelCase_							(					unittest.TestCase			):







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

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      int     					=			'''laion/clap-htsat-unfused'''
													SCREAMING_SNAKE_CASE					:      Tuple     					=			tempfile.mkdtemp()







						def 					__lowercase    (  self   :      Tuple				,    **lowerCAmelCase__   :      Dict				):

													"""simple docstring"""
													return RobertaTokenizer.from_pretrained(self.checkpoint				,    **lowerCAmelCase__				)







						def 					__lowercase    (  self   :      int				,    **lowerCAmelCase__   :      str				):

													"""simple docstring"""
													return ClapFeatureExtractor.from_pretrained(self.checkpoint				,    **lowerCAmelCase__				)







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

													"""simple docstring"""
													shutil.rmtree(self.tmpdirname				)







						def 					__lowercase    (  self   :      Dict				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      List[str]     					=			self.get_tokenizer()
													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			self.get_feature_extractor()

													SCREAMING_SNAKE_CASE					:      List[str]     					=			ClapProcessor(tokenizer=lowerCAmelCase__				,    feature_extractor=lowerCAmelCase__				)

													processor.save_pretrained(self.tmpdirname				)
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			ClapProcessor.from_pretrained(self.tmpdirname				)

													self.assertEqual(processor.tokenizer.get_vocab()				,    tokenizer.get_vocab()				)
													self.assertIsInstance(processor.tokenizer				,    lowerCAmelCase__				)

													self.assertEqual(processor.feature_extractor.to_json_string()				,    feature_extractor.to_json_string()				)
													self.assertIsInstance(processor.feature_extractor				,    lowerCAmelCase__				)







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

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Dict     					=			ClapProcessor(tokenizer=self.get_tokenizer()				,    feature_extractor=self.get_feature_extractor()				)
													processor.save_pretrained(self.tmpdirname				)

													SCREAMING_SNAKE_CASE					:      List[Any]     					=			self.get_tokenizer(bos_token='''(BOS)'''				,    eos_token='''(EOS)'''				)
													SCREAMING_SNAKE_CASE					:      List[Any]     					=			self.get_feature_extractor(do_normalize=lowerCAmelCase__				,    padding_value=1.0				)

													SCREAMING_SNAKE_CASE					:      str     					=			ClapProcessor.from_pretrained(
													    self.tmpdirname				,    bos_token='''(BOS)'''				,    eos_token='''(EOS)'''				,    do_normalize=lowerCAmelCase__				,    padding_value=1.0				)

													self.assertEqual(processor.tokenizer.get_vocab()				,    tokenizer_add_kwargs.get_vocab()				)
													self.assertIsInstance(processor.tokenizer				,    lowerCAmelCase__				)

													self.assertEqual(processor.feature_extractor.to_json_string()				,    feature_extractor_add_kwargs.to_json_string()				)
													self.assertIsInstance(processor.feature_extractor				,    lowerCAmelCase__				)







						def 					__lowercase    (  self   :      Dict				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      List[Any]     					=			self.get_feature_extractor()
													SCREAMING_SNAKE_CASE					:      Tuple     					=			self.get_tokenizer()

													SCREAMING_SNAKE_CASE					:      Tuple     					=			ClapProcessor(tokenizer=lowerCAmelCase__				,    feature_extractor=lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			floats_list((3, 10_00)				)

													SCREAMING_SNAKE_CASE					:      Any     					=			feature_extractor(lowerCAmelCase__				,    return_tensors='''np'''				)
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			processor(audios=lowerCAmelCase__				,    return_tensors='''np'''				)

													for key in input_feat_extract.keys():
																				self.assertAlmostEqual(input_feat_extract[key].sum()				,    input_processor[key].sum()				,    delta=1e-2				)







						def 					__lowercase    (  self   :      Any				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Tuple     					=			self.get_feature_extractor()
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			self.get_tokenizer()

													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			ClapProcessor(tokenizer=lowerCAmelCase__				,    feature_extractor=lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      int     					=			'''This is a test string'''

													SCREAMING_SNAKE_CASE					:      int     					=			processor(text=lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      Optional[int]     					=			tokenizer(lowerCAmelCase__				)

													for key in encoded_tok.keys():
																				self.assertListEqual(encoded_tok[key]				,    encoded_processor[key]				)







						def 					__lowercase    (  self   :      Optional[Any]				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      str     					=			self.get_feature_extractor()
													SCREAMING_SNAKE_CASE					:      List[str]     					=			self.get_tokenizer()

													SCREAMING_SNAKE_CASE					:      Any     					=			ClapProcessor(tokenizer=lowerCAmelCase__				,    feature_extractor=lowerCAmelCase__				)

													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			[[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

													SCREAMING_SNAKE_CASE					:      Tuple     					=			processor.batch_decode(lowerCAmelCase__				)
													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			tokenizer.batch_decode(lowerCAmelCase__				)

													self.assertListEqual(lowerCAmelCase__				,    lowerCAmelCase__				)







						def 					__lowercase    (  self   :      Optional[Any]				):

													"""simple docstring"""
													SCREAMING_SNAKE_CASE					:      Union[str, Any]     					=			self.get_feature_extractor()
													SCREAMING_SNAKE_CASE					:      str     					=			self.get_tokenizer()

													SCREAMING_SNAKE_CASE					:      Optional[Any]     					=			ClapProcessor(tokenizer=lowerCAmelCase__				,    feature_extractor=lowerCAmelCase__				)

													self.assertListEqual(
													    processor.model_input_names[2:]				,    feature_extractor.model_input_names				,    msg='''`processor` and `feature_extractor` model input names do not match'''				,    )




