




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


lowercase__  		=		logging.get_logger(__name__)

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

lowercase__  		=		{
    """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"""
        ),
    },
}

lowercase__  		=		{
    """squeezebert/squeezebert-uncased""": 512,
    """squeezebert/squeezebert-mnli""": 512,
    """squeezebert/squeezebert-mnli-headless""": 512,
}


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






class lowerCAmelCase__			(  _snake_case		):






			'''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						,   lowercase=None						,   lowercase=None						,   lowercase=True						,   lowercase="[UNK]"						,   lowercase="[SEP]"						,   lowercase="[PAD]"						,   lowercase="[CLS]"						,   lowercase="[MASK]"						,   lowercase=True						,   lowercase=None						,   **lowercase						,   ):
							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  :    Tuple					=					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  :    Optional[Any]					=					getattr(lowerCAmelCase__						,   normalizer_state.pop('type'						)						)
											_lowerCamelCase  :    List[str]					=					do_lower_case
											_lowerCamelCase  :    Dict					=					strip_accents
											_lowerCamelCase  :    str					=					tokenize_chinese_chars
											_lowerCamelCase  :    Tuple					=					normalizer_class(**lowerCAmelCase__						)

							_lowerCamelCase  :    str					=					do_lower_case
			def       A_					(						self						,   lowercase						,   lowercase=None						):
							_lowerCamelCase  :    Dict					=					[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						,   lowercase						,   lowercase = None						):
							_lowerCamelCase  :    Tuple					=					[self.sep_token_id]
							_lowerCamelCase  :    List[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       A_					(						self						,   lowercase						,   lowercase = None						):
							_lowerCamelCase  :    Tuple					=					self._tokenizer.model.save(lowerCAmelCase__						,   name=lowerCAmelCase__						)
							return tuple(lowerCAmelCase__						)





"""simple docstring"""






from __future__ import annotations

lowercase__  		=		10







def   _snake_case    (       lowercase__	):
				_lowerCamelCase  :    List[Any]					=					1
				_lowerCamelCase  :    Optional[int]					=					max(lowercase__	)
				while placement <= max_digit:
								# declare and initialize empty buckets
								_lowerCamelCase  :    list[list]					=					[[] for _ in range(lowercase__	)]
								# split list_of_ints between the buckets
								for i in list_of_ints:
												_lowerCamelCase  :    Dict					=					int((i / placement) % RADIX	)
												buckets[tmp].append(lowercase__	)
								# put each buckets' contents into list_of_ints
								_lowerCamelCase  :    str					=					0
								for b in range(lowercase__	):
												for i in buckets[b]:
																_lowerCamelCase  :    str					=					i
																a += 1
        # move to next
								placement *= RADIX
				return list_of_ints


if __name__ == "__main__":
			import doctest

			doctest.testmod()