





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": 512,
    "squeezebert/squeezebert-mnli": 512,
    "squeezebert/squeezebert-mnli-headless": 512,
}


UpperCamelCase__      ={
    "squeezebert/squeezebert-uncased": {"do_lower_case": True},
    "squeezebert/squeezebert-mnli": {"do_lower_case": True},
    "squeezebert/squeezebert-mnli-headless": {"do_lower_case": True},
}





class 			lowerCAmelCase__( UpperCamelCase_    ):






       '''simple docstring'''


       __snake_case 			=    VOCAB_FILES_NAMES
       __snake_case 			=    PRETRAINED_VOCAB_FILES_MAP
       __snake_case 			=    PRETRAINED_INIT_CONFIGURATION
       __snake_case 			=    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
       __snake_case 			=    SqueezeBertTokenizer




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

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

            _SCREAMING_SNAKE_CASE       :	int						    =							do_lower_case




       def     UpperCamelCase_			(      self    ,						__lowerCamelCase    ,						__lowerCamelCase=None							)			->     Tuple:
            _SCREAMING_SNAKE_CASE       :	str						    =							[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    ,						__lowerCamelCase    ,						__lowerCamelCase = None							)			->     List[int]:
            _SCREAMING_SNAKE_CASE       :	Optional[Any]						    =							[self.sep_token_id]
            _SCREAMING_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     UpperCamelCase_			(      self    ,						__lowerCamelCase    ,						__lowerCamelCase = None							)			->     Tuple[str]:
            _SCREAMING_SNAKE_CASE       :	Dict						    =							self._tokenizer.model.save(_a    ,						name=_a							)
            return tuple(_a							)











from __future__ import annotations

import requests






def     lowerCamelCase__			(__lowerCamelCase	):
     _SCREAMING_SNAKE_CASE       :	Dict						    =							f"""https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty"""
     return requests.get(__lowerCamelCase	).json()






def     lowerCamelCase__			(__lowerCamelCase = 10	):
     _SCREAMING_SNAKE_CASE       :	List[Any]						    =							"https://hacker-news.firebaseio.com/v0/topstories.json?print=pretty"
     _SCREAMING_SNAKE_CASE       :	Optional[Any]						    =							requests.get(__lowerCamelCase	).json()[:max_stories]
     return [get_hackernews_story(__lowerCamelCase	) for story_id in story_ids]






def     lowerCamelCase__			(__lowerCamelCase = 10	):
     _SCREAMING_SNAKE_CASE       :	List[str]						    =							hackernews_top_stories(__lowerCamelCase	)
     return "\n".join("* [{title}]({url})".format(**__lowerCamelCase	) for story in stories	)


if __name__ == "__main__":
       print(hackernews_top_stories_as_markdown())