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


A     :  List[Any]					     =       logging.get_logger(__name__)

A     :  Tuple					     =       {"vocab_file": "vocab.txt", "tokenizer_file": "tokenizer.json"}

A     :  Optional[int]					     =       {
    "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"
        ),
    },
}

A     :  Union[str, Any]					     =       {
    "squeezebert/squeezebert-uncased": 5_12,
    "squeezebert/squeezebert-mnli": 5_12,
    "squeezebert/squeezebert-mnli-headless": 5_12,
}


A     :  Union[str, Any]					     =       {
    "squeezebert/squeezebert-uncased": {"do_lower_case": True},
    "squeezebert/squeezebert-mnli": {"do_lower_case": True},
    "squeezebert/squeezebert-mnli-headless": {"do_lower_case": True},
}


class   lowerCamelCase					(A_					):
		"""simple docstring"""







		lowerCamelCase__     =						VOCAB_FILES_NAMES
		lowerCamelCase__     =						PRETRAINED_VOCAB_FILES_MAP
		lowerCamelCase__     =						PRETRAINED_INIT_CONFIGURATION
		lowerCamelCase__     =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		lowerCamelCase__     =						SqueezeBertTokenizer







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

								SCREAMING_SNAKE_CASE_          =  json.loads(self.backend_tokenizer.normalizer.__getstate__()   )
								if (
								    normalizer_state.get("lowercase"  ,     __magic_name__   ) != do_lower_case
								    or normalizer_state.get("strip_accents"  ,     __magic_name__   ) != strip_accents
								    or normalizer_state.get("handle_chinese_chars"  ,     __magic_name__   ) != tokenize_chinese_chars
								):
														SCREAMING_SNAKE_CASE_          =  getattr(__magic_name__  ,     normalizer_state.pop("type"   )   )
														SCREAMING_SNAKE_CASE_          =  do_lower_case
														SCREAMING_SNAKE_CASE_          =  strip_accents
														SCREAMING_SNAKE_CASE_          =  tokenize_chinese_chars
														SCREAMING_SNAKE_CASE_          =  normalizer_class(**__magic_name__   )

								SCREAMING_SNAKE_CASE_          =  do_lower_case







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



from typing import Optional
from urllib.parse import quote

import huggingface_hub as hfh
from packaging import version


def      a__ (		__UpperCamelCase     ,      __UpperCamelCase     ,      __UpperCamelCase = None				):
      if version.parse(hfh.__version__				).release < version.parse("0.11.0"				).release:
            # old versions of hfh don't url-encode the file path
            SCREAMING_SNAKE_CASE_          =  quote(__UpperCamelCase				)
      return hfh.hf_hub_url(__UpperCamelCase     ,      __UpperCamelCase     ,      repo_type="dataset"     ,      revision=__UpperCamelCase				)


