






'''simple docstring'''
import json
from typing import Dict, List, Optional, Tuple, Union

from tokenizers import pre_tokenizers, processors

from ...tokenization_utils_base import AddedToken, BatchEncoding, EncodedInput
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_led import LEDTokenizer


UpperCamelCase__ =			logging.get_logger(__name__)


UpperCamelCase__ =			{'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', 'tokenizer_file': 'tokenizer.json'}

UpperCamelCase__ =			{
    'vocab_file': {
        'allenai/led-base-16384': 'https://huggingface.co/allenai/led-base-16384/resolve/main/vocab.json',
    },
    'merges_file': {
        'allenai/led-base-16384': 'https://huggingface.co/allenai/led-base-16384/resolve/main/merges.txt',
    },
    'tokenizer_file': {
        'allenai/led-base-16384': 'https://huggingface.co/allenai/led-base-16384/resolve/main/tokenizer.json',
    },
}

UpperCamelCase__ =			{
    'allenai/led-base-16384': 16384,
}


class        _UpperCAmelCase						(		snake_case			):
    __lowerCamelCase:   List[Any]		       =    VOCAB_FILES_NAMES
    __lowerCamelCase:   Any		       =    PRETRAINED_VOCAB_FILES_MAP
    __lowerCamelCase:   List[str]		       =    PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
    __lowerCamelCase:   Dict		       =    LEDTokenizer
    __lowerCamelCase:   List[str]		       =    ['input_ids', 'attention_mask']




    def __init__(			self  :       List[Any]  ,     a  :       Optional[int]=None  ,     a  :       List[Any]=None  ,     a  :       Union[str, Any]=None  ,     a  :       int="replace"  ,     a  :       List[Any]="<s>"  ,     a  :       str="</s>"  ,     a  :       List[str]="</s>"  ,     a  :       Union[str, Any]="<s>"  ,     a  :       Any="<unk>"  ,     a  :       Any="<pad>"  ,     a  :       Any="<mask>"  ,     a  :       int=False  ,     a  :       int=True  ,     **a  :       Union[str, Any]  ,     ):






       '''simple docstring'''






       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  ,     )

       lowercase_	:    Any           =     json.loads(self.backend_tokenizer.pre_tokenizer.__getstate__()			)
       if pre_tok_state.get("add_prefix_space"  ,     a			) != add_prefix_space:
          lowercase_	:    List[Any]           =     getattr(a  ,     pre_tok_state.pop("type"			)			)
          lowercase_	:    Optional[Any]           =     add_prefix_space
          lowercase_	:    List[str]           =     pre_tok_class(**a			)

       lowercase_	:    Dict           =     add_prefix_space

       # the pre_tokenizer is already updated in the GPT2TokenizerFast `__init__`
       lowercase_	:    Union[str, Any]           =     "post_processor"
       lowercase_	:    List[Any]           =     getattr(self.backend_tokenizer  ,     a  ,     a			)
       if tokenizer_component_instance:
          lowercase_	:    Tuple           =     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:
             lowercase_	:    Dict           =     tuple(state["sep"]			)
          if "cls" in state:
             lowercase_	:    Any           =     tuple(state["cls"]			)

          lowercase_	:    Optional[Any]           =     False

          if state.get("add_prefix_space"  ,     a			) != add_prefix_space:
             lowercase_	:    Optional[Any]           =     add_prefix_space
             lowercase_	:    int           =     True

          if state.get("trim_offsets"  ,     a			) != trim_offsets:
             lowercase_	:    Optional[int]           =     trim_offsets
             lowercase_	:    List[Any]           =     True

          if changes_to_apply:
             lowercase_	:    Optional[int]           =     getattr(a  ,     state.pop("type"			)			)
             lowercase_	:    Union[str, Any]           =     component_class(**a			)
             setattr(self.backend_tokenizer  ,     a  ,     a			)




    @property
    # Copied from transformers.models.bart.tokenization_bart_fast.BartTokenizerFast.mask_token with BART->LED
    def 				lowerCAmelCase__				(			self  :       int			):






       '''simple docstring'''






       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 				lowerCAmelCase__				(			self  :       Optional[Any]  ,     a  :       Optional[Any]			):






       '''simple docstring'''






       lowercase_	:    Optional[int]           =     AddedToken(a  ,     lstrip=a  ,     rstrip=a			) if isinstance(a  ,     a			) else value
       lowercase_	:    Union[str, Any]           =     value




    def 				lowerCAmelCase__				(			self  :       List[Any]  ,     *a  :       Optional[Any]  ,     **a  :       Optional[Any]			):






       '''simple docstring'''






       lowercase_	:    str           =     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 				lowerCAmelCase__				(			self  :       List[Any]  ,     *a  :       Optional[int]  ,     **a  :       Tuple			):






       '''simple docstring'''






       lowercase_	:    List[str]           =     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 				lowerCAmelCase__				(			self  :       Dict  ,     a  :       str  ,     a  :       Optional[str] = None			):






       '''simple docstring'''






       lowercase_	:    Union[str, Any]           =     self._tokenizer.model.save(a  ,     name=a			)
       return tuple(a			)




    def 				lowerCAmelCase__				(			self  :       Optional[Any]  ,     a  :       List[Any]  ,     a  :       Optional[Any]=None			):






       '''simple docstring'''






       lowercase_	:    Optional[Any]           =     [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 				lowerCAmelCase__				(			self  :       Optional[Any]  ,     a  :       List[int]  ,     a  :       Optional[List[int]] = None			):






       '''simple docstring'''






       lowercase_	:    Union[str, Any]           =     [self.sep_token_id]
       lowercase_	:    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 + sep + token_ids_a + sep			) * [0]





    def 				lowerCAmelCase__				(			self  :       Dict  ,     a  :       Union[Dict[str, EncodedInput], BatchEncoding]  ,     a  :       Optional[int] = None  ,     a  :       PaddingStrategy = PaddingStrategy.DO_NOT_PAD  ,     a  :       Optional[int] = None  ,     a  :       Optional[bool] = None  ,     ):






       '''simple docstring'''






       lowercase_	:    List[Any]           =     super()._pad(
           encoded_inputs=a  ,     max_length=a  ,     padding_strategy=a  ,     pad_to_multiple_of=a  ,     return_attention_mask=a  ,     )

       # Load from model defaults
       if return_attention_mask is None:
          lowercase_	:    List[str]           =     "attention_mask" in self.model_input_names

       if return_attention_mask and "global_attention_mask" in encoded_inputs:
          lowercase_	:    Optional[Any]           =     encoded_inputs[self.model_input_names[0]]
          # `global_attention_mask` need to have the same length as other (sequential) inputs.
          lowercase_	:    Optional[Any]           =     len(encoded_inputs["global_attention_mask"]			) != len(a			)

          if needs_to_be_padded:
             lowercase_	:    Optional[int]           =     len(a			) - len(encoded_inputs["global_attention_mask"]			)

             if self.padding_side == "right":
                # Use `-1` since `0` in `global_attention_mask` means `local attention` instead of `not to attend`
                lowercase_	:    List[Any]           =     (
                    encoded_inputs["global_attention_mask"] + [-1] * difference
                )
             elif self.padding_side == "left":
                lowercase_	:    Optional[Any]           =     [-1] * difference + encoded_inputs[
                    "global_attention_mask"
                ]
             else:
                raise ValueError("Invalid padding strategy:" + str(self.padding_side			)			)

       return encoded_inputs












'''simple docstring'''
import heapq as hq
import math
from collections.abc import Iterator


class        _UpperCAmelCase						:




    def __init__(			self  :       Optional[Any]  ,     a  :       Any			):






       '''simple docstring'''






       lowercase_	:    List[Any]           =     str(id_			)
       lowercase_	:    List[str]           =     None
       lowercase_	:    Tuple           =     None
       lowercase_	:    Dict           =     []
       lowercase_	:    Union[str, Any]           =     {}  # {vertex:distance}




    def __lt__(			self  :       Optional[Any]  ,     a  :       int			):






       '''simple docstring'''






       return self.key < other.key




    def __repr__(			self  :       Union[str, Any]			):






       '''simple docstring'''






       return self.id




    def 				lowerCAmelCase__				(			self  :       Union[str, Any]  ,     a  :       Optional[int]			):






       '''simple docstring'''






       self.neighbors.append(a			)





    def 				lowerCAmelCase__				(			self  :       Dict  ,     a  :       int  ,     a  :       Optional[int]			):






       '''simple docstring'''






       lowercase_	:    int           =     weight




def 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase						,		_UpperCamelCase						,		_UpperCamelCase						,		_UpperCamelCase							):


   """simple docstring"""




   graph[a - 1].add_neighbor(graph[b - 1]							)
   graph[b - 1].add_neighbor(graph[a - 1]							)
   # add the edges:
   graph[a - 1].add_edge(graph[b - 1]						,		_UpperCamelCase							)
   graph[b - 1].add_edge(graph[a - 1]						,		_UpperCamelCase							)




def 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase						,		_UpperCamelCase							):


   """simple docstring"""




   lowercase_	:    Any           =     []
   for u in graph:
      lowercase_	:    List[Any]           =     math.inf
      lowercase_	:    str           =     None
   lowercase_	:    Tuple           =     0
   lowercase_	:    Tuple           =     graph[:]
   while q:
      lowercase_	:    List[Any]           =     min(_UpperCamelCase							)
      q.remove(_UpperCamelCase							)
      for v in u.neighbors:
         if (v in q) and (u.edges[v.id] < v.key):
            lowercase_	:    Optional[int]           =     u
            lowercase_	:    Union[str, Any]           =     u.edges[v.id]
   for i in range(1						,		len(_UpperCamelCase							)							):
      a.append((int(graph[i].id							) + 1, int(graph[i].pi.id							) + 1)							)
   return a




def 		__SCREAMING_SNAKE_CASE					(  _UpperCamelCase						,		_UpperCamelCase							):


   """simple docstring"""




   for u in graph:
      lowercase_	:    str           =     math.inf
      lowercase_	:    int           =     None
   lowercase_	:    List[Any]           =     0

   lowercase_	:    str           =     list(_UpperCamelCase							)
   hq.heapify(_UpperCamelCase							)

   while h:
      lowercase_	:    List[Any]           =     hq.heappop(_UpperCamelCase							)
      for v in u.neighbors:
         if (v in h) and (u.edges[v.id] < v.key):
            lowercase_	:    str           =     u
            lowercase_	:    Optional[int]           =     u.edges[v.id]
            hq.heapify(_UpperCamelCase							)

   for i in range(1						,		len(_UpperCamelCase							)							):
      yield (int(graph[i].id							) + 1, int(graph[i].pi.id							) + 1)




def 		__SCREAMING_SNAKE_CASE					(  ):


   """simple docstring"""






if __name__ == "__main__":
 import doctest

 doctest.testmod()




