

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


__UpperCAmelCase    				=     logging.get_logger(__name__)

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

__UpperCAmelCase    				=     {
    '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'
        ),
    },
}

__UpperCAmelCase    				=     {
    'squeezebert/squeezebert-uncased': 5_1_2,
    'squeezebert/squeezebert-mnli': 5_1_2,
    'squeezebert/squeezebert-mnli-headless': 5_1_2,
}


__UpperCAmelCase    				=     {
    '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"""







 _lowercase     :					Optional[int]      =						VOCAB_FILES_NAMES
 _lowercase     :					int      =						PRETRAINED_VOCAB_FILES_MAP
 _lowercase     :					Any      =						PRETRAINED_INIT_CONFIGURATION
 _lowercase     :					Optional[int]      =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 _lowercase     :					Union[str, Any]      =						SqueezeBertTokenizer

 def __init__(		self :	Tuple     ,						A_ :	str=None     ,						A_ :	Dict=None     ,						A_ :	Optional[int]=True     ,						A_ :	Dict="[UNK]"     ,						A_ :	List[Any]="[SEP]"     ,						A_ :	List[Any]="[PAD]"     ,						A_ :	Tuple="[CLS]"     ,						A_ :	int="[MASK]"     ,						A_ :	Optional[int]=True     ,						A_ :	str=None     ,						**A_ :	Union[str, Any]     ,						):






      '''simple docstring'''




      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     ,						)

      _lowerCAmelCase   :					List[Any]        =    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
      ):
           _lowerCAmelCase   :					str        =    getattr(_lowerCamelCase     ,						normalizer_state.pop("type"       )       )
           _lowerCAmelCase   :					List[Any]        =    do_lower_case
           _lowerCAmelCase   :					int        =    strip_accents
           _lowerCAmelCase   :					List[Any]        =    tokenize_chinese_chars
           _lowerCAmelCase   :					Union[str, Any]        =    normalizer_class(**_lowerCamelCase       )

      _lowerCAmelCase   :					str        =    do_lower_case

 def    __magic_name__       (		self :	Dict     ,						A_ :	Union[str, Any]     ,						A_ :	str=None       ):






      '''simple docstring'''




      _lowerCAmelCase   :					Union[str, 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    __magic_name__       (		self :	Dict     ,						A_ :	List[str]     ,						A_ :	int = None       ):






      '''simple docstring'''




      _lowerCAmelCase   :					List[Any]        =    [self.sep_token_id]
      _lowerCAmelCase   :					Union[str, 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       ) * [0] + len(token_ids_a + sep       ) * [1]


 def    __magic_name__       (		self :	List[str]     ,						A_ :	Optional[int]     ,						A_ :	int = None       ):






      '''simple docstring'''




      _lowerCAmelCase   :					Dict        =    self._tokenizer.model.save(_lowerCamelCase     ,						name=_lowerCamelCase       )
      return tuple(_lowerCamelCase       )









from pathlib import PurePosixPath
from typing import Optional

import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo

from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url





class A__    ( A ):



 """simple docstring"""







 _lowercase     :					List[str]      =						''''''
 _lowercase     :					Optional[Any]      =						'''hf-legacy'''  # "hf://"" is reserved for hffs

 def __init__(		self :	Dict     ,						A_ :	Optional[DatasetInfo] = None     ,						A_ :	Optional[str] = None     ,						**A_ :	int     ,						):






      '''simple docstring'''




      super().__init__(self     ,						**A_       )
      _lowerCAmelCase   :					Union[str, Any]        =    repo_info
      _lowerCAmelCase   :					Optional[int]        =    token
      _lowerCAmelCase   :					str        =    None

 def    __magic_name__       (		self :	Tuple       ):






      '''simple docstring'''




      if self.dir_cache is None:
           _lowerCAmelCase   :					int        =    {}
           for hf_file in self.repo_info.siblings:
                # TODO(QL): add sizes
                _lowerCAmelCase   :					Optional[int]        =    {
                    "name": hf_file.rfilename,
                    "size": None,
                    "type": "file",
                }
                self.dir_cache.update(
                    {
                        str(A_       ): {"name": str(A_       ), "size": None, "type": "directory"}
                        for d in list(PurePosixPath(hf_file.rfilename       ).parents       )[:-1]
                    }       )

 def    __magic_name__       (		self :	Dict     ,						A_ :	str     ,						A_ :	str = "rb"     ,						**A_ :	Optional[int]     ,						):






      '''simple docstring'''




      if not isinstance(self.repo_info     ,						A_       ):
           raise NotImplementedError(F'''Open is only implemented for dataset repositories, but got {self.repo_info}'''       )
      _lowerCAmelCase   :					str        =    hf_hub_url(self.repo_info.id     ,						A_     ,						revision=self.repo_info.sha       )
      return fsspec.open(
          A_     ,						mode=A_     ,						headers=get_authentication_headers_for_url(A_     ,						use_auth_token=self.token       )     ,						client_kwargs={"trust_env": True}     ,						).open()

 def    __magic_name__       (		self :	Union[str, Any]     ,						A_ :	List[Any]     ,						**A_ :	str       ):






      '''simple docstring'''




      self._get_dirs()
      _lowerCAmelCase   :					Optional[int]        =    self._strip_protocol(A_       )
      if path in self.dir_cache:
           return self.dir_cache[path]
      else:
           raise FileNotFoundError(A_       )


 def    __magic_name__       (		self :	Any     ,						A_ :	str     ,						A_ :	Any=False     ,						**A_ :	Dict       ):






      '''simple docstring'''




      self._get_dirs()
      _lowerCAmelCase   :					Dict        =    PurePosixPath(path.strip("/"       )       )
      _lowerCAmelCase   :					str        =    {}
      for p, f in self.dir_cache.items():
           _lowerCAmelCase   :					List[str]        =    PurePosixPath(p.strip("/"       )       )
           _lowerCAmelCase   :					Tuple        =    p.parent
           if root == path:
                _lowerCAmelCase   :					Union[str, Any]        =    f
      _lowerCAmelCase   :					List[str]        =    list(paths.values()       )
      if detail:
           return out
      else:
           return sorted(f["name"] for f in out       )






