
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


_A						      =				logging.get_logger(__name__)


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

# See all BART models at https://huggingface.co/models?filter=bart
_A						      =				{
    "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",
    },
}

_A						      =				{
    "facebook/bart-base": 10_24,
    "facebook/bart-large": 10_24,
    "facebook/bart-large-mnli": 10_24,
    "facebook/bart-large-cnn": 10_24,
    "facebook/bart-large-xsum": 10_24,
    "yjernite/bart_eli5": 10_24,
}







class   lowerCamelCase	(						A_						):
     UpperCAmelCase__       :							Dict     =	VOCAB_FILES_NAMES
     UpperCAmelCase__       :							Dict     =	PRETRAINED_VOCAB_FILES_MAP
     UpperCAmelCase__       :							List[Any]     =	PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     UpperCAmelCase__       :							Any     =	["input_ids", "attention_mask"]
     UpperCAmelCase__       :							str     =	BartTokenizer





     def __init__(self   :					Optional[Any]       ,					_A   :					Any=None       ,					_A   :					Optional[Any]=None       ,					_A   :					int=None       ,					_A   :					Tuple="replace"       ,					_A   :					Any="<s>"       ,					_A   :					Tuple="</s>"       ,					_A   :					Dict="</s>"       ,					_A   :					Dict="<s>"       ,					_A   :					Tuple="<unk>"       ,					_A   :					Any="<pad>"       ,					_A   :					str="<mask>"       ,					_A   :					Optional[int]=False       ,					_A   :					List[str]=True       ,					**_A   :					Tuple       ,					)		->		Any:
         super().__init__(
             _A       ,					_A       ,					tokenizer_file=_A       ,					errors=_A       ,					bos_token=_A       ,					eos_token=_A       ,					sep_token=_A       ,					cls_token=_A       ,					unk_token=_A       ,					pad_token=_A       ,					mask_token=_A       ,					add_prefix_space=_A       ,					trim_offsets=_A       ,					**_A       ,					)

         snake_case				  =      json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()     )
         if pre_tok_state.get("add_prefix_space"       ,					_A     ) != add_prefix_space:
             snake_case				  =      getattr(_A       ,					pre_tok_state.pop("type"     )     )
             snake_case				  =      add_prefix_space
             snake_case				  =      pre_tok_class(**_A     )

         snake_case				  =      add_prefix_space

         # the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
         snake_case				  =      "post_processor"
         snake_case				  =      getattr(self.backend_tokenizer       ,					_A       ,					_A     )
         if tokenizer_component_instance:
             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:
                 snake_case				  =      tuple(state["sep"]     )
             if "cls" in state:
                 snake_case				  =      tuple(state["cls"]     )

             snake_case				  =      False

             if state.get("add_prefix_space"       ,					_A     ) != add_prefix_space:
                 snake_case				  =      add_prefix_space
                 snake_case				  =      True

             if state.get("trim_offsets"       ,					_A     ) != trim_offsets:
                 snake_case				  =      trim_offsets
                 snake_case				  =      True

             if changes_to_apply:
                 snake_case				  =      getattr(_A       ,					state.pop("type"     )     )
                 snake_case				  =      component_class(**_A     )
                 setattr(self.backend_tokenizer       ,					_A       ,					_A     )





     @property
     def 	UpperCAmelCase(self   :					Optional[int]     )		->		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 	UpperCAmelCase(self   :					List[Any]       ,					_A   :					Union[str, Any]     )		->		Dict:
         snake_case				  =      AddedToken(_A       ,					lstrip=_A       ,					rstrip=_A     ) if isinstance(_A       ,					_A     ) else value
         snake_case				  =      value





     def 	UpperCAmelCase(self   :					Any       ,					*_A   :					Union[str, Any]       ,					**_A   :					List[str]     )		->		BatchEncoding:
         snake_case				  =      kwargs.get("is_split_into_words"       ,					_A     )

         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(*_A       ,					**_A     )





     def 	UpperCAmelCase(self   :					List[str]       ,					*_A   :					Optional[int]       ,					**_A   :					Any     )		->		BatchEncoding:
         snake_case				  =      kwargs.get("is_split_into_words"       ,					_A     )

         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(*_A       ,					**_A     )





     def 	UpperCAmelCase(self   :					Optional[Any]       ,					_A   :					str       ,					_A   :					Optional[str] = None     )		->		Tuple[str]:
         snake_case				  =      self._tokenizer.model.save(_A       ,					name=_A     )
         return tuple(_A     )





     def 	UpperCAmelCase(self   :					Optional[int]       ,					_A   :					Dict       ,					_A   :					Union[str, Any]=None     )		->		List[Any]:
         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 	UpperCAmelCase(self   :					Dict       ,					_A   :					List[int]       ,					_A   :					Optional[List[int]] = None     )		->		List[int]:
         snake_case				  =      [self.sep_token_id]
         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]



def 		lowercase_    (     A__ = 1000	)							->							int:
    """simple docstring"""

    snake_case				  =      -1
    snake_case				  =      0
    for a in range(1				,	n // 3	):
        # Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
        snake_case				  =      (n * n - 2 * a * n) // (2 * n - 2 * a)
        snake_case				  =      n - a - b
        if c * c == (a * a + b * b):
            snake_case				  =      a * b * c
            if candidate >= product:
                snake_case				  =      candidate
    return product


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

