



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


_snake_case            = logging.get_logger(__name__)


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

# See all LED models at https://huggingface.co/models?filter=LED
_snake_case            = {
    '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',
    },
}

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







@lru_cache()
# Copied from transformers.models.bart.tokenization_bart.bytes_to_unicode
def        lowerCAmelCase_			(  ):
      _A							:  Dict    =		(
          list(range(ord("""!"""  ),ord("""~"""  ) + 1  )  ) + list(range(ord("""¡"""  ),ord("""¬"""  ) + 1  )  ) + list(range(ord("""®"""  ),ord("""ÿ"""  ) + 1  )  )
      )
      _A							:  int    =		bs[:]
      _A							:  Optional[Any]    =		0
      for b in range(2**8  ):
            if b not in bs:
                  bs.append(lowerCAmelCase_  )
                  cs.append(2**8 + n  )
                  n += 1
      _A							:  int    =		[chr(lowerCAmelCase_  ) for n in cs]
      return dict(zip(lowerCAmelCase_,lowerCAmelCase_  )  )







def        lowerCAmelCase_			(  snake_case_  ):
      _A							:  Dict    =		set()
      _A							:  Tuple    =		word[0]
      for char in word[1:]:
            pairs.add((prev_char, char)  )
            _A							:  Tuple    =		char
      return pairs







class 		lowercase							(     a__	):
     _a											=		VOCAB_FILES_NAMES
     _a											=		PRETRAINED_VOCAB_FILES_MAP
     _a											=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     _a											=		["""input_ids""", """attention_mask"""]

     def __init__(						self	,  _a	,  _a	,  _a="replace"	,  _a="<s>"	,  _a="</s>"	,  _a="</s>"	,  _a="<s>"	,  _a="<unk>"	,  _a="<pad>"	,  _a="<mask>"	,  _a=False	,  **_a	,  )		->							List[str]:
           _A							:  Tuple    =		AddedToken(lowercase__	,  lstrip=lowercase__	,  rstrip=lowercase__       ) if isinstance(lowercase__	,  lowercase__       ) else bos_token
           _A							:  Dict    =		AddedToken(lowercase__	,  lstrip=lowercase__	,  rstrip=lowercase__       ) if isinstance(lowercase__	,  lowercase__       ) else eos_token
           _A							:  Union[str, Any]    =		AddedToken(lowercase__	,  lstrip=lowercase__	,  rstrip=lowercase__       ) if isinstance(lowercase__	,  lowercase__       ) else sep_token
           _A							:  Optional[int]    =		AddedToken(lowercase__	,  lstrip=lowercase__	,  rstrip=lowercase__       ) if isinstance(lowercase__	,  lowercase__       ) else cls_token
           _A							:  Tuple    =		AddedToken(lowercase__	,  lstrip=lowercase__	,  rstrip=lowercase__       ) if isinstance(lowercase__	,  lowercase__       ) else unk_token
           _A							:  Any    =		AddedToken(lowercase__	,  lstrip=lowercase__	,  rstrip=lowercase__       ) if isinstance(lowercase__	,  lowercase__       ) else pad_token

           # Mask token behave like a normal word, i.e. include the space before it
           _A							:  str    =		AddedToken(lowercase__	,  lstrip=lowercase__	,  rstrip=lowercase__       ) if isinstance(lowercase__	,  lowercase__       ) else mask_token

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

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

           # Should have added re.IGNORECASE so BPE merges can happen for capitalized versions of contractions
           _A							:  Optional[int]    =		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       a__			(						self       )		->							Optional[int]:
           return len(self.encoder       )

     def       a__			(						self       )		->							Any:
           return dict(self.encoder	,  **self.added_tokens_encoder       )

     def       a__			(						self	,  _a       )		->							List[Any]:





           if token in self.cache:
                 return self.cache[token]
           _A							:  Optional[int]    =		tuple(lowercase__       )
           _A							:  List[str]    =		get_pairs(lowercase__       )

           if not pairs:
                 return token

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

                       if word[i] == first and i < len(lowercase__       ) - 1 and word[i + 1] == second:
                             new_word.append(first + second       )
                             i += 2
                       else:
                             new_word.append(word[i]       )
                             i += 1
                 _A							:  str    =		tuple(lowercase__       )
                 _A							:  Any    =		new_word
                 if len(lowercase__       ) == 1:
                       break
                 else:
                       _A							:  str    =		get_pairs(lowercase__       )
           _A							:  Union[str, Any]    =		''' '''.join(lowercase__       )
           _A							:  Optional[int]    =		word
           return word

     def       a__			(						self	,  _a       )		->							Tuple:
           _A							:  List[str]    =		[]
           for token in re.findall(self.pat	,  lowercase__       ):
                 _A							:  Optional[int]    =		''''''.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(lowercase__       ).split(""" """       )       )
           return bpe_tokens

     def       a__			(						self	,  _a       )		->							List[str]:
           return self.encoder.get(lowercase__	,  self.encoder.get(self.unk_token       )       )

     def       a__			(						self	,  _a       )		->							Tuple:
           return self.decoder.get(lowercase__       )

     def       a__			(						self	,  _a       )		->							Optional[Any]:
           _A							:  Any    =		''''''.join(lowercase__       )
           _A							:  List[Any]    =		bytearray([self.byte_decoder[c] for c in text]       ).decode("""utf-8"""	,  errors=self.errors       )
           return text

     def       a__			(						self	,  _a	,  _a = None       )		->							Tuple[str]:





           if not os.path.isdir(lowercase__       ):
                 logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''       )
                 return
           _A							:  Tuple    =		os.path.join(
               lowercase__	,  (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]       )
           _A							:  List[str]    =		os.path.join(
               lowercase__	,  (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""merges_file"""]       )

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

           _A							:  Dict    =		0
           with open(lowercase__	,  """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!"""       )
                             _A							:  Optional[Any]    =		token_index
                       writer.write(""" """.join(lowercase__       ) + """\n"""       )
                       index += 1

           return vocab_file, merge_file

     def       a__			(						self	,  _a	,  _a = None       )		->							List[int]:





           if token_ids_a is None:
                 return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
           _A							:  str    =		[self.cls_token_id]
           _A							:  Tuple    =		[self.sep_token_id]
           return cls + token_ids_a + sep + sep + token_ids_a + sep

     def       a__			(						self	,  _a	,  _a = None	,  _a = False       )		->							List[int]:





           if already_has_special_tokens:
                 return super().get_special_tokens_mask(
                     token_ids_a=lowercase__	,  token_ids_a=lowercase__	,  already_has_special_tokens=lowercase__       )

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

     def       a__			(						self	,  _a	,  _a = None       )		->							List[int]:
           _A							:  Optional[Any]    =		[self.sep_token_id]
           _A							:  int    =		[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       a__			(						self	,  _a	,  _a=False	,  **_a       )		->							List[Any]:
           _A							:  Union[str, Any]    =		kwargs.pop("""add_prefix_space"""	,  self.add_prefix_space       )
           if (is_split_into_words or add_prefix_space) and (len(lowercase__       ) > 0 and not text[0].isspace()):
                 _A							:  Dict    =		''' ''' + text
           return (text, kwargs)



     def       a__			(						self	,  _a	,  _a = None	,  _a = PaddingStrategy.DO_NOT_PAD	,  _a = None	,  _a = None	,  )		->							dict:
           _A							:  int    =		super()._pad(
               encoded_inputs=lowercase__	,  max_length=lowercase__	,  padding_strategy=lowercase__	,  pad_to_multiple_of=lowercase__	,  return_attention_mask=lowercase__	,  )

           # Load from model defaults
           if return_attention_mask is None:
                 _A							:  Optional[Any]    =		'''attention_mask''' in self.model_input_names

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

                 if needs_to_be_padded:
                       _A							:  Any    =		len(lowercase__       ) - 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`
                             _A							:  Any    =		(
                                 encoded_inputs['''global_attention_mask'''] + [-1] * difference
                             )
                       elif self.padding_side == "left":
                             _A							:  Optional[Any]    =		[-1] * difference + encoded_inputs[
                                 '''global_attention_mask'''
                             ]
                       else:
                             raise ValueError("""Invalid padding strategy:""" + str(self.padding_side       )       )

           return encoded_inputs







from datetime import datetime as dt
import os

from github import Github


_snake_case            = [
    "good first issue",
    "good second issue",
    "good difficult issue",
    "feature request",
    "new model",
    "wip",
]







def        lowerCAmelCase_			(  ):
      _A							:  int    =		Github(os.environ["""GITHUB_TOKEN"""]  )
      _A							:  Tuple    =		g.get_repo("""huggingface/transformers"""  )
      _A							:  Dict    =		repo.get_issues(state="""open"""  )

      for issue in open_issues:
            _A							:  Optional[Any]    =		sorted([comment for comment in issue.get_comments()],key=lambda snake_case_  : i.created_at,reverse=snake_case_  )
            _A							:  Dict    =		comments[0] if len(snake_case_  ) > 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()

