


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 : int		=				logging.get_logger(__name__)

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

a : Union[str, 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'''
        ),
    },
}

a : Optional[int]		=				{
    '''squeezebert/squeezebert-uncased''': 512,
    '''squeezebert/squeezebert-mnli''': 512,
    '''squeezebert/squeezebert-mnli-headless''': 512,
}


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_       (				lowerCAmelCase__				):



					'''simple docstring'''







					__UpperCAmelCase            =				VOCAB_FILES_NAMES
					__UpperCAmelCase            =				PRETRAINED_VOCAB_FILES_MAP
					__UpperCAmelCase            =				PRETRAINED_INIT_CONFIGURATION
					__UpperCAmelCase            =				PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					__UpperCAmelCase            =				SqueezeBertTokenizer






					def __init__(				self ,       snake_case_=None ,       snake_case_=None ,       snake_case_=True ,       snake_case_="[UNK]" ,       snake_case_="[SEP]" ,       snake_case_="[PAD]" ,       snake_case_="[CLS]" ,       snake_case_="[MASK]" ,       snake_case_=True ,       snake_case_=None ,       **snake_case_ ,       )   ->			List[Any]:







								'''simple docstring'''

								super().__init__(
								    snake_case_ ,       tokenizer_file=snake_case_ ,       do_lower_case=snake_case_ ,       unk_token=snake_case_ ,       sep_token=snake_case_ ,       pad_token=snake_case_ ,       cls_token=snake_case_ ,       mask_token=snake_case_ ,       tokenize_chinese_chars=snake_case_ ,       strip_accents=snake_case_ ,       **snake_case_ ,       )

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

								__lowercase 					=   do_lower_case






					def A      (				self ,       snake_case_ ,       snake_case_=None						)   ->			Union[str, Any]:







								'''simple docstring'''

								__lowercase 					=   [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 ,       snake_case_ ,       snake_case_ = None						)   ->			List[int]:







								'''simple docstring'''

								__lowercase 					=   [self.sep_token_id]
								__lowercase 					=   [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 ,       snake_case_ ,       snake_case_ = None						)   ->			Tuple[str]:







								'''simple docstring'''

								__lowercase 					=   self._tokenizer.model.save(snake_case_ ,       name=snake_case_						)
								return tuple(snake_case_						)






from itertools import count


def 		lowercase_  (     _UpperCamelCase = 50  ):


			'''simple docstring'''







			__lowercase 					=   [1] * min_block_length

			for n in count(_UpperCamelCase  ):
						fill_count_functions.append(1  )

						for block_length in range(_UpperCamelCase       ,			n + 1  ):
									for block_start in range(n - block_length  ):
												fill_count_functions[n] += fill_count_functions[
												    n - block_start - block_length - 1
												]

									fill_count_functions[n] += 1

						if fill_count_functions[n] > 1_00_00_00:
									break

			return n


if __name__ == "__main__":
	print(f'''{solution() = }''')


