

"""simple docstring"""




from datetime import datetime as dt
import os

from github import Github


__UpperCAmelCase =				[
    'good first issue',
    'good second issue',
    'good difficult issue',
    'feature request',
    'new model',
    'wip',
]
def   lowerCAmelCase						(					):
 '''simple docstring'''





 UpperCAmelCase__					:  str					   =					Github(os.environ["""GITHUB_TOKEN"""]      )
 UpperCAmelCase__					:  int					   =					g.get_repo("""huggingface/transformers"""      )
 UpperCAmelCase__					:  Optional[int]					   =					repo.get_issues(state="""open"""      )

 for issue in open_issues:
  UpperCAmelCase__					:  Any					   =					sorted([comment for comment in issue.get_comments()]							,    key=lambda __UpperCamelCase      : i.created_at							,    reverse=__UpperCamelCase      )
  UpperCAmelCase__					:  Union[str, Any]					   =					comments[0] if len(__UpperCamelCase      ) > 0 else None
  if (
      last_comment is not None
      and last_comment.user.login == "github-actions[bot]"
      and (dt.utcnow() - issue.updated_at).days > 7
      and (dt.utcnow() - issue.created_at).days >= 30
      and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()      )
  ):
   # print(f"Would close issue {issue.number} since it has been 7 days of inactivity since bot mention.")
   issue.edit(state="""closed"""      )
  elif (
      (dt.utcnow() - issue.updated_at).days > 23
      and (dt.utcnow() - issue.created_at).days >= 30
      and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()      )
  ):
   # print(f"Would add stale comment to {issue.number}")
   issue.create_comment(
       """This issue has been automatically marked as stale because it has not had """
       """recent activity. If you think this still needs to be addressed """
       """please comment on this thread.\n\nPlease note that issues that do not follow the """
       """[contributing guidelines](https://github.com/huggingface/transformers/blob/main/CONTRIBUTING.md) """
       """are likely to be ignored."""      )


if __name__ == "__main__":
      main()








"""simple docstring"""




import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union

import regex as re

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging


__UpperCAmelCase =				logging.get_logger(__name__)


__UpperCAmelCase =				{'vocab_file': 'vocab.json', 'merges_file': 'merges.txt'}

# See all LED models at https://huggingface.co/models?filter=LED
__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': 1_6384,
}
@lru_cache()
# Copied from transformers.models.bart.tokenization_bart.bytes_to_unicode
def   lowerCAmelCase						(					):
 '''simple docstring'''





 UpperCAmelCase__					:  Tuple					   =					(
     list(range(ord("""!"""      )							,    ord("""~"""      ) + 1      )      ) + list(range(ord("""¡"""      )							,    ord("""¬"""      ) + 1      )      ) + list(range(ord("""®"""      )							,    ord("""ÿ"""      ) + 1      )      )
 )
 UpperCAmelCase__					:  int					   =					bs[:]
 UpperCAmelCase__					:  Union[str, Any]					   =					0
 for b in range(2**8      ):
  if b not in bs:
   bs.append(__UpperCamelCase      )
   cs.append(2**8 + n      )
   n += 1
 UpperCAmelCase__					:  Tuple					   =					[chr(__UpperCamelCase      ) for n in cs]
 return dict(zip(__UpperCamelCase							,    __UpperCamelCase      )      )
def   lowerCAmelCase						(					__UpperCamelCase      ):
 '''simple docstring'''





 UpperCAmelCase__					:  int					   =					set()
 UpperCAmelCase__					:  Tuple					   =					word[0]
 for char in word[1:]:
  pairs.add((prev_char, char)      )
  UpperCAmelCase__					:  Optional[Any]					   =					char
 return pairs







class      __lowercase			(    __lowerCamelCase					):
  snake_case_				       =       VOCAB_FILES_NAMES
  snake_case_				       =       PRETRAINED_VOCAB_FILES_MAP
  snake_case_				       =       PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
  snake_case_				       =       ["""input_ids""", """attention_mask"""]

  def __init__(  self		:			Union[str, Any]					,A		:			Any					,A		:			Dict					,A		:			Optional[Any]="replace"					,A		:			Dict="<s>"					,A		:			str="</s>"					,A		:			str="</s>"					,A		:			Dict="<s>"					,A		:			List[str]="<unk>"					,A		:			Union[str, Any]="<pad>"					,A		:			Any="<mask>"					,A		:			str=False					,**A		:			Optional[Any]					,):






   '''simple docstring'''
   UpperCAmelCase__					:  List[str]					   =					AddedToken(A					,lstrip=A					,rstrip=A    ) if isinstance(A					,A    ) else bos_token
   UpperCAmelCase__					:  Any					   =					AddedToken(A					,lstrip=A					,rstrip=A    ) if isinstance(A					,A    ) else eos_token
   UpperCAmelCase__					:  List[str]					   =					AddedToken(A					,lstrip=A					,rstrip=A    ) if isinstance(A					,A    ) else sep_token
   UpperCAmelCase__					:  Tuple					   =					AddedToken(A					,lstrip=A					,rstrip=A    ) if isinstance(A					,A    ) else cls_token
   UpperCAmelCase__					:  Tuple					   =					AddedToken(A					,lstrip=A					,rstrip=A    ) if isinstance(A					,A    ) else unk_token
   UpperCAmelCase__					:  List[str]					   =					AddedToken(A					,lstrip=A					,rstrip=A    ) if isinstance(A					,A    ) else pad_token

   # Mask token behave like a normal word, i.e. include the space before it
   UpperCAmelCase__					:  Union[str, Any]					   =					AddedToken(A					,lstrip=A					,rstrip=A    ) if isinstance(A					,A    ) else mask_token

   super().__init__(
       errors=A					,bos_token=A					,eos_token=A					,unk_token=A					,sep_token=A					,cls_token=A					,pad_token=A					,mask_token=A					,add_prefix_space=A					,**A					,)

   with open(A					,encoding="""utf-8"""    ) as vocab_handle:
    UpperCAmelCase__					:  Tuple					   =					json.load(A    )
   UpperCAmelCase__					:  Any					   =					{v: k for k, v in self.encoder.items()}
   UpperCAmelCase__					:  List[Any]					   =					errors  # how to handle errors in decoding
   UpperCAmelCase__					:  List[str]					   =					bytes_to_unicode()
   UpperCAmelCase__					:  int					   =					{v: k for k, v in self.byte_encoder.items()}
   with open(A					,encoding="""utf-8"""    ) as merges_handle:
    UpperCAmelCase__					:  List[Any]					   =					merges_handle.read().split("""\n"""    )[1:-1]
   UpperCAmelCase__					:  Tuple					   =					[tuple(merge.split()    ) for merge in bpe_merges]
   UpperCAmelCase__					:  Any					   =					dict(zip(A					,range(len(A    )    )    )    )
   UpperCAmelCase__					:  Optional[Any]					   =					{}
   UpperCAmelCase__					:  Optional[int]					   =					add_prefix_space

   # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
   UpperCAmelCase__					:  Union[str, Any]					   =					re.compile(R"""'s|'t|'re|'ve|'m|'ll|'d| ?\p{L}+| ?\p{N}+| ?[^\s\p{L}\p{N}]+|\s+(?!\S)|\s+"""    )

  @property
  # Copied from transformers.models.bart.tokenization_bart.BartTokenizer.vocab_size
  def    __lowercase       (  self		:			List[Any]    ):






   '''simple docstring'''
   return len(self.encoder    )

  def    __lowercase       (  self		:			Optional[Any]    ):






   '''simple docstring'''
   return dict(self.encoder					,**self.added_tokens_encoder    )

  def    __lowercase       (  self		:			Optional[int]					,A		:			Union[str, Any]    ):






   '''simple docstring'''
   if token in self.cache:
    return self.cache[token]
   UpperCAmelCase__					:  Optional[Any]					   =					tuple(A    )
   UpperCAmelCase__					:  int					   =					get_pairs(A    )

   if not pairs:
    return token

   while True:
    UpperCAmelCase__					:  str					   =					min(A					,key=lambda A    : self.bpe_ranks.get(A					,float("""inf"""    )    )    )
    if bigram not in self.bpe_ranks:
     break
    UpperCAmelCase__   ,      UpperCAmelCase__					:  Tuple					   =					bigram
    UpperCAmelCase__					:  Optional[Any]					   =					[]
    UpperCAmelCase__					:  Any					   =					0
    while i < len(A    ):
     try:
      UpperCAmelCase__					:  Optional[Any]					   =					word.index(A					,A    )
     except ValueError:
      new_word.extend(word[i:]    )
      break
     else:
      new_word.extend(word[i:j]    )
      UpperCAmelCase__					:  int					   =					j

     if word[i] == first and i < len(A    ) - 1 and word[i + 1] == second:
      new_word.append(first + second    )
      i += 2
     else:
      new_word.append(word[i]    )
      i += 1
    UpperCAmelCase__					:  List[str]					   =					tuple(A    )
    UpperCAmelCase__					:  str					   =					new_word
    if len(A    ) == 1:
     break
    else:
     UpperCAmelCase__					:  str					   =					get_pairs(A    )
   UpperCAmelCase__					:  int					   =					""" """.join(A    )
   UpperCAmelCase__					:  List[str]					   =					word
   return word

  def    __lowercase       (  self		:			Optional[Any]					,A		:			Any    ):






   '''simple docstring'''
   UpperCAmelCase__					:  Any					   =					[]
   for token in re.findall(self.pat					,A    ):
    UpperCAmelCase__					:  Any					   =					"""""".join(
        self.byte_encoder[b] for b in token.encode("""utf-8"""    )    )  # Maps all our bytes to unicode strings, avoiding control tokens of the BPE (spaces in our case)
    bpe_tokens.extend(bpe_token for bpe_token in self.bpe(A    ).split(""" """    )    )
   return bpe_tokens

  def    __lowercase       (  self		:			Dict					,A		:			int    ):






   '''simple docstring'''
   return self.encoder.get(A					,self.encoder.get(self.unk_token    )    )

  def    __lowercase       (  self		:			Dict					,A		:			Optional[Any]    ):






   '''simple docstring'''
   return self.decoder.get(A    )

  def    __lowercase       (  self		:			Optional[Any]					,A		:			int    ):






   '''simple docstring'''
   UpperCAmelCase__					:  int					   =					"""""".join(A    )
   UpperCAmelCase__					:  Dict					   =					bytearray([self.byte_decoder[c] for c in text]    ).decode("""utf-8"""					,errors=self.errors    )
   return text

  def    __lowercase       (  self		:			Optional[int]					,A		:			str					,A		:			Optional[str] = None    ):






   '''simple docstring'''
   if not os.path.isdir(A    ):
    logger.error(f"Vocabulary path ({save_directory}) should be a directory"    )
    return
   UpperCAmelCase__					:  Any					   =					os.path.join(
       A					,(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]    )
   UpperCAmelCase__					:  List[str]					   =					os.path.join(
       A					,(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""merges_file"""]    )

   with open(A					,"""w"""					,encoding="""utf-8"""    ) as f:
    f.write(json.dumps(self.encoder					,indent=2					,sort_keys=A					,ensure_ascii=A    ) + """\n"""    )

   UpperCAmelCase__					:  Any					   =					0
   with open(A					,"""w"""					,encoding="""utf-8"""    ) as writer:
    writer.write("""#version: 0.2\n"""    )
    for bpe_tokens, token_index in sorted(self.bpe_ranks.items()					,key=lambda A    : kv[1]    ):
     if index != token_index:
      logger.warning(
          f"Saving vocabulary to {merge_file}: BPE merge indices are not consecutive."
          """ Please check that the tokenizer is not corrupted!"""    )
      UpperCAmelCase__					:  Optional[int]					   =					token_index
     writer.write(""" """.join(A    ) + """\n"""    )
     index += 1

   return vocab_file, merge_file

  def    __lowercase       (  self		:			Union[str, Any]					,A		:			List[int]					,A		:			Optional[List[int]] = None    ):






   '''simple docstring'''
   if token_ids_a is None:
    return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
   UpperCAmelCase__					:  Dict					   =					[self.cls_token_id]
   UpperCAmelCase__					:  Optional[Any]					   =					[self.sep_token_id]
   return cls + token_ids_a + sep + sep + token_ids_a + sep

  def    __lowercase       (  self		:			int					,A		:			List[int]					,A		:			Optional[List[int]] = None					,A		:			bool = False    ):






   '''simple docstring'''
   if already_has_special_tokens:
    return super().get_special_tokens_mask(
        token_ids_a=A					,token_ids_a=A					,already_has_special_tokens=A    )

   if token_ids_a is None:
    return [1] + ([0] * len(A    )) + [1]
   return [1] + ([0] * len(A    )) + [1, 1] + ([0] * len(A    )) + [1]

  def    __lowercase       (  self		:			Tuple					,A		:			List[int]					,A		:			Optional[List[int]] = None    ):






   '''simple docstring'''
   UpperCAmelCase__					:  str					   =					[self.sep_token_id]
   UpperCAmelCase__					:  List[str]					   =					[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       (  self		:			Any					,A		:			str					,A		:			List[Any]=False					,**A		:			Tuple    ):






   '''simple docstring'''
   UpperCAmelCase__					:  Any					   =					kwargs.pop("""add_prefix_space"""					,self.add_prefix_space    )
   if (is_split_into_words or add_prefix_space) and (len(A    ) > 0 and not text[0].isspace()):
    UpperCAmelCase__					:  Dict					   =					""" """ + text
   return (text, kwargs)




  def    __lowercase       (  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'''
   UpperCAmelCase__					:  Union[str, 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:
    UpperCAmelCase__					:  str					   =					"""attention_mask""" in self.model_input_names

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

    if needs_to_be_padded:
     UpperCAmelCase__					:  List[Any]					   =					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`
      UpperCAmelCase__					:  Tuple					   =					(
          encoded_inputs["""global_attention_mask"""] + [-1] * difference
      )
     elif self.padding_side == "left":
      UpperCAmelCase__					:  Dict					   =					[-1] * difference + encoded_inputs[
          """global_attention_mask"""
      ]
     else:
      raise ValueError("""Invalid padding strategy:""" + str(self.padding_side    )    )

   return encoded_inputs





