


import json
from typing import List, Optional, Tuple

from tokenizers import normalizers

from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer


_snake_case  :	List[str]			      =       logging.get_logger(__name__)

_snake_case  :	Union[str, Any]			      =       {"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}

_snake_case  :	List[Any]			      =       {
    "vocab_file": {
        "squeezebert/squeezebert-uncased": (
            "https://huggingface.co/squeezebert/squeezebert-uncased/resolve/main/vocab.txt"
        ),
        "squeezebert/squeezebert-mnli": "https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/vocab.txt",
        "squeezebert/squeezebert-mnli-headless": (
            "https://huggingface.co/squeezebert/squeezebert-mnli-headless/resolve/main/vocab.txt"
        ),
    },
    "tokenizer_file": {
        "squeezebert/squeezebert-uncased": (
            "https://huggingface.co/squeezebert/squeezebert-uncased/resolve/main/tokenizer.json"
        ),
        "squeezebert/squeezebert-mnli": (
            "https://huggingface.co/squeezebert/squeezebert-mnli/resolve/main/tokenizer.json"
        ),
        "squeezebert/squeezebert-mnli-headless": (
            "https://huggingface.co/squeezebert/squeezebert-mnli-headless/resolve/main/tokenizer.json"
        ),
    },
}

_snake_case  :	Union[str, Any]			      =       {
    "squeezebert/squeezebert-uncased": 512,
    "squeezebert/squeezebert-mnli": 512,
    "squeezebert/squeezebert-mnli-headless": 512,
}


_snake_case  :	Optional[Any]			      =       {
    "squeezebert/squeezebert-uncased": {"do_lower_case": True},
    "squeezebert/squeezebert-mnli": {"do_lower_case": True},
    "squeezebert/squeezebert-mnli-headless": {"do_lower_case": True},
}

class        a	(_lowerCAmelCase   ):




							"""simple docstring"""


							__UpperCAmelCase					:							Optional[Any]  						=						VOCAB_FILES_NAMES
							__UpperCAmelCase					:							Any  						=						PRETRAINED_VOCAB_FILES_MAP
							__UpperCAmelCase					:							List[Any]  						=						PRETRAINED_INIT_CONFIGURATION
							__UpperCAmelCase					:							List[Any]  						=						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
							__UpperCAmelCase					:							Union[str, Any]  						=						SqueezeBertTokenizer

							def __init__(							self :						int					,			lowerCamelCase :						str=None					,			lowerCamelCase :						Union[str, Any]=None					,			lowerCamelCase :						Optional[int]=True					,			lowerCamelCase :						int="[UNK]"					,			lowerCamelCase :						int="[SEP]"					,			lowerCamelCase :						Optional[Any]="[PAD]"					,			lowerCamelCase :						Any="[CLS]"					,			lowerCamelCase :						Dict="[MASK]"					,			lowerCamelCase :						Tuple=True					,			lowerCamelCase :						Optional[Any]=None					,			**lowerCamelCase :						int					,			)			->					int:
														super().__init__(
														    lowerCamelCase					,			tokenizer_file=lowerCamelCase					,			do_lower_case=lowerCamelCase					,			unk_token=lowerCamelCase					,			sep_token=lowerCamelCase					,			pad_token=lowerCamelCase					,			cls_token=lowerCamelCase					,			mask_token=lowerCamelCase					,			tokenize_chinese_chars=lowerCamelCase					,			strip_accents=lowerCamelCase					,			**lowerCamelCase					,			)

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

														__snake_case	:    Optional[int]											=     do_lower_case

							def 					__snake_case      (							self :						Union[str, Any]					,			lowerCamelCase :						Tuple					,			lowerCamelCase :						List[str]=None       )			->					Dict:
														__snake_case	:    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 					__snake_case      (							self :						int					,			lowerCamelCase :						List[int]					,			lowerCamelCase :						Optional[List[int]] = None       )			->					List[int]:
														__snake_case	:    Dict											=     [self.sep_token_id]
														__snake_case	:    Tuple											=     [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 					__snake_case      (							self :						Any					,			lowerCamelCase :						str					,			lowerCamelCase :						Optional[str] = None       )			->					Tuple[str]:
														__snake_case	:    Any											=     self._tokenizer.model.save(lowerCamelCase					,			name=lowerCamelCase       )
														return tuple(lowerCamelCase       )





import unittest

from transformers import DonutProcessor


_snake_case  :	Dict			      =       "naver-clova-ix/donut-base"

class        a	(unittest.TestCase   ):




							"""simple docstring"""


							def 					__snake_case      (							self :						Dict       )			->					int:
														__snake_case	:    Any											=     DonutProcessor.from_pretrained(lowerCamelCase       )






							def 					__snake_case      (							self :						str       )			->					List[Any]:
														__snake_case	:    Union[str, Any]											=     {
														    "name": "John Doe",
														    "age": "99",
														    "city": "Atlanta",
														    "state": "GA",
														    "zip": "30301",
														    "phone": "123-4567",
														    "nicknames": [{"nickname": "Johnny"}, {"nickname": "JD"}],
														}

														__snake_case	:    Union[str, Any]											=     (
														    "<s_name>John Doe</s_name><s_age>99</s_age><s_city>Atlanta</s_city>"
														    "<s_state>GA</s_state><s_zip>30301</s_zip><s_phone>123-4567</s_phone>"
														    "<s_nicknames><s_nickname>Johnny</s_nickname>"
														    "<sep/><s_nickname>JD</s_nickname></s_nicknames>"
														)
														__snake_case	:    Tuple											=     self.processor.tokenajson(lowerCamelCase       )

														self.assertDictEqual(lowerCamelCase					,			lowerCamelCase       )

