




"""simple docstring"""





def        _UpperCamelCase     (      UpperCamelCase = 1					,							UpperCamelCase = 1000				)      ->      int:


			"""simple docstring"""
			__UpperCAmelCase						:			int												=       1
			__UpperCAmelCase						:			Tuple												=       0

			for divide_by_number in range(UpperCamelCase					,							digit + 1				):
						__UpperCAmelCase						:			list[int]												=       []
						__UpperCAmelCase						:			int												=       numerator
						for _ in range(1					,							digit + 1				):
									if now_divide in has_been_divided:
												if longest_list_length < len(UpperCamelCase				):
															__UpperCAmelCase						:			Any												=       len(UpperCamelCase				)
															__UpperCAmelCase						:			Optional[int]												=       divide_by_number
									else:
												has_been_divided.append(UpperCamelCase				)
												__UpperCAmelCase						:			Union[str, Any]												=       now_divide * 10 % divide_by_number

			return the_digit


# Tests
if __name__ == "__main__":
					import doctest

					doctest.testmod()





'''simple docstring'''

import json
from typing import List, Optional, Tuple

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bart import BartTokenizer


SCREAMING_SNAKE_CASE							:				int     	=			logging.get_logger(__name__)


SCREAMING_SNAKE_CASE							:				Dict     	=			{"vocab_file": "vocab.json", "merges_file": "merges.txt", "tokenizer_file": "tokenizer.json"}

# See all BART models at https://huggingface.co/models?filter=bart
SCREAMING_SNAKE_CASE							:				str     	=			{
    "vocab_file": {
        "facebook/bart-base": "https://huggingface.co/facebook/bart-base/resolve/main/vocab.json",
        "facebook/bart-large": "https://huggingface.co/facebook/bart-large/resolve/main/vocab.json",
        "facebook/bart-large-mnli": "https://huggingface.co/facebook/bart-large-mnli/resolve/main/vocab.json",
        "facebook/bart-large-cnn": "https://huggingface.co/facebook/bart-large-cnn/resolve/main/vocab.json",
        "facebook/bart-large-xsum": "https://huggingface.co/facebook/bart-large-xsum/resolve/main/vocab.json",
        "yjernite/bart_eli5": "https://huggingface.co/yjernite/bart_eli5/resolve/main/vocab.json",
    },
    "merges_file": {
        "facebook/bart-base": "https://huggingface.co/facebook/bart-base/resolve/main/merges.txt",
        "facebook/bart-large": "https://huggingface.co/facebook/bart-large/resolve/main/merges.txt",
        "facebook/bart-large-mnli": "https://huggingface.co/facebook/bart-large-mnli/resolve/main/merges.txt",
        "facebook/bart-large-cnn": "https://huggingface.co/facebook/bart-large-cnn/resolve/main/merges.txt",
        "facebook/bart-large-xsum": "https://huggingface.co/facebook/bart-large-xsum/resolve/main/merges.txt",
        "yjernite/bart_eli5": "https://huggingface.co/yjernite/bart_eli5/resolve/main/merges.txt",
    },
    "tokenizer_file": {
        "facebook/bart-base": "https://huggingface.co/facebook/bart-base/resolve/main/tokenizer.json",
        "facebook/bart-large": "https://huggingface.co/facebook/bart-large/resolve/main/tokenizer.json",
        "facebook/bart-large-mnli": "https://huggingface.co/facebook/bart-large-mnli/resolve/main/tokenizer.json",
        "facebook/bart-large-cnn": "https://huggingface.co/facebook/bart-large-cnn/resolve/main/tokenizer.json",
        "facebook/bart-large-xsum": "https://huggingface.co/facebook/bart-large-xsum/resolve/main/tokenizer.json",
        "yjernite/bart_eli5": "https://huggingface.co/yjernite/bart_eli5/resolve/main/tokenizer.json",
    },
}

SCREAMING_SNAKE_CASE							:				Union[str, Any]     	=			{
    "facebook/bart-base": 1024,
    "facebook/bart-large": 1024,
    "facebook/bart-large-mnli": 1024,
    "facebook/bart-large-cnn": 1024,
    "facebook/bart-large-xsum": 1024,
    "yjernite/bart_eli5": 1024,
}






class    snake_case     (      lowercase_		):






				"""simple docstring"""
				_a    	=     VOCAB_FILES_NAMES
				_a    	=     PRETRAINED_VOCAB_FILES_MAP
				_a    	=     PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
				_a    	=     ["""input_ids""", """attention_mask"""]
				_a    	=     BartTokenizer



				def __init__(    self,     _lowercase=None,     _lowercase=None,     _lowercase=None,     _lowercase="replace",     _lowercase="<s>",     _lowercase="</s>",     _lowercase="</s>",     _lowercase="<s>",     _lowercase="<unk>",     _lowercase="<pad>",     _lowercase="<mask>",     _lowercase=False,     _lowercase=True,     **_lowercase,     )     ->							Dict:
											super().__init__(
											    _lowercase,     _lowercase,     tokenizer_file=_lowercase,     errors=_lowercase,     bos_token=_lowercase,     eos_token=_lowercase,     sep_token=_lowercase,     cls_token=_lowercase,     unk_token=_lowercase,     pad_token=_lowercase,     mask_token=_lowercase,     add_prefix_space=_lowercase,     trim_offsets=_lowercase,     **_lowercase,     )

											SCREAMING_SNAKE_CASE_				=				json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()       )
											if pre_tok_state.get('add_prefix_space',     _lowercase       ) != add_prefix_space:
																		SCREAMING_SNAKE_CASE_				=				getattr(_lowercase,     pre_tok_state.pop('type'       )       )
																		SCREAMING_SNAKE_CASE_				=				add_prefix_space
																		SCREAMING_SNAKE_CASE_				=				pre_tok_class(**_lowercase       )

											SCREAMING_SNAKE_CASE_				=				add_prefix_space

											# the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
											SCREAMING_SNAKE_CASE_				=				'post_processor'
											SCREAMING_SNAKE_CASE_				=				getattr(self.backend_tokenizer,     _lowercase,     _lowercase       )
											if tokenizer_component_instance:
																		SCREAMING_SNAKE_CASE_				=				json.loads(tokenizer_component_instance.__getstate__()       )

																		# The lists 'sep' and 'cls' must be cased in tuples for the object `post_processor_class`
																		if "sep" in state:
																									SCREAMING_SNAKE_CASE_				=				tuple(state['sep']       )
																		if "cls" in state:
																									SCREAMING_SNAKE_CASE_				=				tuple(state['cls']       )

																		SCREAMING_SNAKE_CASE_				=				False

																		if state.get('add_prefix_space',     _lowercase       ) != add_prefix_space:
																									SCREAMING_SNAKE_CASE_				=				add_prefix_space
																									SCREAMING_SNAKE_CASE_				=				True

																		if state.get('trim_offsets',     _lowercase       ) != trim_offsets:
																									SCREAMING_SNAKE_CASE_				=				trim_offsets
																									SCREAMING_SNAKE_CASE_				=				True

																		if changes_to_apply:
																									SCREAMING_SNAKE_CASE_				=				getattr(_lowercase,     state.pop('type'       )       )
																									SCREAMING_SNAKE_CASE_				=				component_class(**_lowercase       )
																									setattr(self.backend_tokenizer,     _lowercase,     _lowercase       )



				@property
				def   a__					(    self       )     ->							str:
											if self._mask_token is None:
																		if self.verbose:
																									logger.error('Using mask_token, but it is not set yet.'       )
																		return None
											return str(self._mask_token       )



				@mask_token.setter
				def   a__					(    self,     _lowercase       )     ->							Dict:
											SCREAMING_SNAKE_CASE_				=				AddedToken(_lowercase,     lstrip=_lowercase,     rstrip=_lowercase       ) if isinstance(_lowercase,     _lowercase       ) else value
											SCREAMING_SNAKE_CASE_				=				value



				def   a__					(    self,     *_lowercase,     **_lowercase       )     ->							BatchEncoding:
											SCREAMING_SNAKE_CASE_				=				kwargs.get('is_split_into_words',     _lowercase       )

											if is_split_into_words and not self.add_prefix_space:
																		raise ValueError(
																		    f"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
																		    'to use it with pretokenized inputs.'       )

											return super()._batch_encode_plus(*_lowercase,     **_lowercase       )



				def   a__					(    self,     *_lowercase,     **_lowercase       )     ->							BatchEncoding:
											SCREAMING_SNAKE_CASE_				=				kwargs.get('is_split_into_words',     _lowercase       )

											if is_split_into_words and not self.add_prefix_space:
																		raise ValueError(
																		    f"""You need to instantiate {self.__class__.__name__} with add_prefix_space=True """
																		    'to use it with pretokenized inputs.'       )

											return super()._encode_plus(*_lowercase,     **_lowercase       )



				def   a__					(    self,     _lowercase,     _lowercase = None       )     ->							Tuple[str]:
											SCREAMING_SNAKE_CASE_				=				self._tokenizer.model.save(_lowercase,     name=_lowercase       )
											return tuple(_lowercase       )



				def   a__					(    self,     _lowercase,     _lowercase=None       )     ->							Optional[Any]:
											SCREAMING_SNAKE_CASE_				=				[self.bos_token_id] + token_ids_a + [self.eos_token_id]
											if token_ids_a is None:
																		return output

											return output + [self.eos_token_id] + token_ids_a + [self.eos_token_id]





				def   a__					(    self,     _lowercase,     _lowercase = None       )     ->							List[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 + sep + token_ids_a + sep       ) * [0]





