

import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ....tokenization_utils_fast import PreTrainedTokenizerFast
from ....utils import logging
from .tokenization_retribert import RetriBertTokenizer


SCREAMING_SNAKE_CASE_				    =      logging.get_logger(__name__)

SCREAMING_SNAKE_CASE_				    =      {'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}

SCREAMING_SNAKE_CASE_				    =      {
    'vocab_file': {
        'yjernite/retribert-base-uncased': (
            'https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/vocab.txt'
        ),
    },
    'tokenizer_file': {
        'yjernite/retribert-base-uncased': (
            'https://huggingface.co/yjernite/retribert-base-uncased/resolve/main/tokenizer.json'
        ),
    },
}

SCREAMING_SNAKE_CASE_				    =      {
    'yjernite/retribert-base-uncased': 512,
}


SCREAMING_SNAKE_CASE_				    =      {
    'yjernite/retribert-base-uncased': {'do_lower_case': True},
}

class 				a  (	__snake_case				):
						_lowercase    						=			VOCAB_FILES_NAMES
						_lowercase    						=			PRETRAINED_VOCAB_FILES_MAP
						_lowercase    						=			PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
						_lowercase    						=			PRETRAINED_INIT_CONFIGURATION
						_lowercase    						=			RetriBertTokenizer
						_lowercase    						=			["input_ids", "attention_mask"]


						def __init__(       self						,					A_=None						,					A_=None						,					A_=True						,					A_="[UNK]"						,					A_="[SEP]"						,					A_="[PAD]"						,					A_="[CLS]"						,					A_="[MASK]"						,					A_=True						,					A_=None						,					**A_						,					):







										'''simple docstring'''


										super().__init__(
										    _lowercase						,					tokenizer_file=_lowercase						,					do_lower_case=_lowercase						,					unk_token=_lowercase						,					sep_token=_lowercase						,					pad_token=_lowercase						,					cls_token=_lowercase						,					mask_token=_lowercase						,					tokenize_chinese_chars=_lowercase						,					strip_accents=_lowercase						,					**_lowercase						,					)

										_UpperCAmelCase       :		Tuple 		=    json.loads(self.backend_tokenizer.normalizer.__getstate__()	)
										if (
										    normalizer_state.get("lowercase"						,					_lowercase	) != do_lower_case
										    or normalizer_state.get("strip_accents"						,					_lowercase	) != strip_accents
										    or normalizer_state.get("handle_chinese_chars"						,					_lowercase	) != tokenize_chinese_chars
										):
														_UpperCAmelCase       :		str 		=    getattr(_lowercase						,					normalizer_state.pop("type"	)	)
														_UpperCAmelCase       :		str 		=    do_lower_case
														_UpperCAmelCase       :		str 		=    strip_accents
														_UpperCAmelCase       :		List[str] 		=    tokenize_chinese_chars
														_UpperCAmelCase       :		Optional[Any] 		=    normalizer_class(**_lowercase	)

										_UpperCAmelCase       :		List[Any] 		=    do_lower_case


						def        _UpperCAmelCase				(       self						,					A_						,					A_=None	):







										'''simple docstring'''


										_UpperCAmelCase       :		Optional[Any] 		=    [self.cls_token_id] + token_ids_a + [self.sep_token_id]

										if token_ids_a:
														output += token_ids_a + [self.sep_token_id]

										return output


						def        _UpperCAmelCase				(       self						,					A_						,					A_ = None	):







										'''simple docstring'''


										_UpperCAmelCase       :		Union[str, Any] 		=    [self.sep_token_id]
										_UpperCAmelCase       :		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        _UpperCAmelCase				(       self						,					A_						,					A_ = None	):







										'''simple docstring'''


										_UpperCAmelCase       :		List[Any] 		=    self._tokenizer.model.save(_lowercase						,					name=_lowercase	)
										return tuple(_lowercase	)





import warnings

from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor


SCREAMING_SNAKE_CASE_        =      logging.get_logger(__name__)

class 				a  (	UpperCAmelCase				):


						def __init__(       self						,					*A_						,					**A_	):







										'''simple docstring'''


										warnings.warn(
										    "The class PerceiverFeatureExtractor is deprecated and will be removed in version 5 of Transformers."
										    " Please use PerceiverImageProcessor instead."						,					A_						,					)
										super().__init__(*A_						,					**A_	)


