






"""simple docstring"""



import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging


A__       :				List[Any] 					=					logging.get_logger(__name__)

A__       :				Dict 					=					{'vocab_file': 'spiece.model'}

A__       :				Tuple 					=					{
    'vocab_file': {
        'xlnet-base-cased': 'https://huggingface.co/xlnet-base-cased/resolve/main/spiece.model',
        'xlnet-large-cased': 'https://huggingface.co/xlnet-large-cased/resolve/main/spiece.model',
    }
}

A__       :				Optional[int] 					=					{
    'xlnet-base-cased': None,
    'xlnet-large-cased': None,
}

# Segments (not really needed)
A__       :				Union[str, Any] 					=					0
A__       :				Dict 					=					1
A__       :				List[Any] 					=					2
A__       :				str 					=					3
A__       :				str 					=					4







class    lowercase__			(							A__   ):
			_UpperCAmelCase		:List[str]   			= VOCAB_FILES_NAMES
			_UpperCAmelCase		:Tuple   			= PRETRAINED_VOCAB_FILES_MAP
			_UpperCAmelCase		:int   			= PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
			_UpperCAmelCase		:List[str]   			= "left"


			def __init__(      self     :  Union[str, Any]   ,       snake_case__     :  Dict   ,       snake_case__     :  int=False   ,       snake_case__     :  Tuple=True   ,       snake_case__     :  List[Any]=False   ,       snake_case__     :  Any="<s>"   ,       snake_case__     :  Optional[Any]="</s>"   ,       snake_case__     :  int="<unk>"   ,       snake_case__     :  Optional[Any]="<sep>"   ,       snake_case__     :  Any="<pad>"   ,       snake_case__     :  List[str]="<cls>"   ,       snake_case__     :  str="<mask>"   ,       snake_case__     :  Tuple=["<eop>", "<eod>"]   ,       snake_case__     :  Optional[int] = None   ,       **snake_case__     :  Dict   ,       ):
										lowerCamelCase_       :							Dict									=AddedToken(UpperCamelCase_   ,       lstrip=UpperCamelCase_   ,       rstrip=UpperCamelCase_					) if isinstance(UpperCamelCase_   ,       UpperCamelCase_					) else mask_token

										lowerCamelCase_       :							int									={} if sp_model_kwargs is None else sp_model_kwargs

										super().__init__(
										    do_lower_case=UpperCamelCase_   ,       remove_space=UpperCamelCase_   ,       keep_accents=UpperCamelCase_   ,       bos_token=UpperCamelCase_   ,       eos_token=UpperCamelCase_   ,       unk_token=UpperCamelCase_   ,       sep_token=UpperCamelCase_   ,       pad_token=UpperCamelCase_   ,       cls_token=UpperCamelCase_   ,       mask_token=UpperCamelCase_   ,       additional_special_tokens=UpperCamelCase_   ,       sp_model_kwargs=self.sp_model_kwargs   ,       **UpperCamelCase_   ,       )

										lowerCamelCase_       :							List[Any]									=3

										lowerCamelCase_       :							Any									=do_lower_case
										lowerCamelCase_       :							int									=remove_space
										lowerCamelCase_       :							List[Any]									=keep_accents
										lowerCamelCase_       :							Optional[int]									=vocab_file

										lowerCamelCase_       :							str									=spm.SentencePieceProcessor(**self.sp_model_kwargs					)
										self.sp_model.Load(UpperCamelCase_					)


			@property
			def 	UpperCAmelCase__						(      self     :  Any					):
										return len(self.sp_model					)


			def 	UpperCAmelCase__						(      self     :  Any					):
										lowerCamelCase_       :							Dict									={self.convert_ids_to_tokens(UpperCamelCase_					): i for i in range(self.vocab_size					)}
										vocab.update(self.added_tokens_encoder					)
										return vocab


			def __getstate__(      self     :  str					):
										lowerCamelCase_       :							Optional[Any]									=self.__dict__.copy()
										lowerCamelCase_       :							List[Any]									=None
										return state


			def __setstate__(      self     :  Tuple   ,       snake_case__     :  Optional[int]					):
										lowerCamelCase_       :							str									=d

										# for backward compatibility
										if not hasattr(self   ,       "sp_model_kwargs"					):
																	lowerCamelCase_       :							Optional[int]									={}

										lowerCamelCase_       :							Union[str, Any]									=spm.SentencePieceProcessor(**self.sp_model_kwargs					)
										self.sp_model.Load(self.vocab_file					)


			def 	UpperCAmelCase__						(      self     :  Optional[int]   ,       snake_case__     :  Union[str, Any]					):


										if self.remove_space:
																	lowerCamelCase_       :							Tuple									=''' '''.join(inputs.strip().split()					)
										else:
																	lowerCamelCase_       :							Tuple									=inputs
										lowerCamelCase_       :							str									=outputs.replace("``"   ,       "\""					).replace("\'\'"   ,       "\""					)

										if not self.keep_accents:
																	lowerCamelCase_       :							Optional[Any]									=unicodedata.normalize("NFKD"   ,       UpperCamelCase_					)
																	lowerCamelCase_       :							Any									=''''''.join([c for c in outputs if not unicodedata.combining(UpperCamelCase_					)]					)
										if self.do_lower_case:
																	lowerCamelCase_       :							List[Any]									=outputs.lower()

										return outputs


			def 	UpperCAmelCase__						(      self     :  Tuple   ,       snake_case__     :  List[Any]					):
										lowerCamelCase_       :							List[str]									=self.preprocess_text(UpperCamelCase_					)
										lowerCamelCase_       :							str									=self.sp_model.encode(UpperCamelCase_   ,       out_type=UpperCamelCase_					)
										lowerCamelCase_       :							Optional[int]									=[]
										for piece in pieces:
																	if len(UpperCamelCase_					) > 1 and piece[-1] == str(","					) and piece[-2].isdigit():
																								lowerCamelCase_       :							str									=self.sp_model.EncodeAsPieces(piece[:-1].replace(UpperCamelCase_   ,       ""					)					)
																								if piece[0] != SPIECE_UNDERLINE and cur_pieces[0][0] == SPIECE_UNDERLINE:
																															if len(cur_pieces[0]					) == 1:
																																						lowerCamelCase_       :							Union[str, Any]									=cur_pieces[1:]
																															else:
																																						lowerCamelCase_       :							Optional[Any]									=cur_pieces[0][1:]
																								cur_pieces.append(piece[-1]					)
																								new_pieces.extend(UpperCamelCase_					)
																	else:
																								new_pieces.append(UpperCamelCase_					)

										return new_pieces


			def 	UpperCAmelCase__						(      self     :  Tuple   ,       snake_case__     :  Union[str, Any]					):
										return self.sp_model.PieceToId(UpperCamelCase_					)


			def 	UpperCAmelCase__						(      self     :  Dict   ,       snake_case__     :  Union[str, Any]					):
										return self.sp_model.IdToPiece(UpperCamelCase_					)


			def 	UpperCAmelCase__						(      self     :  Any   ,       snake_case__     :  str					):
										lowerCamelCase_       :							str									=''''''.join(UpperCamelCase_					).replace(UpperCamelCase_   ,       " "					).strip()
										return out_string


			def 	UpperCAmelCase__						(      self     :  List[str]   ,       snake_case__     :  List[Any]   ,       snake_case__     :  str = False   ,       snake_case__     :  Optional[int] = None   ,       snake_case__     :  List[Any] = True   ,       **snake_case__     :  List[str]   ,       ):
										lowerCamelCase_       :							Optional[Any]									=kwargs.pop("use_source_tokenizer"   ,       UpperCamelCase_					)

										lowerCamelCase_       :							List[Any]									=self.convert_ids_to_tokens(UpperCamelCase_   ,       skip_special_tokens=UpperCamelCase_					)

										# To avoid mixing byte-level and unicode for byte-level BPT
										# we need to build string separately for added tokens and byte-level tokens
										# cf. https://github.com/huggingface/transformers/issues/1133
										lowerCamelCase_       :							Union[str, Any]									=[]
										lowerCamelCase_       :							List[str]									=[]
										for token in filtered_tokens:
																	if skip_special_tokens and token in self.all_special_ids:
																								continue
																	if token in self.added_tokens_encoder:
																								if current_sub_text:
																															sub_texts.append(self.convert_tokens_to_string(UpperCamelCase_					)					)
																															lowerCamelCase_       :							List[str]									=[]
																								sub_texts.append(UpperCamelCase_					)
																	else:
																								current_sub_text.append(UpperCamelCase_					)
										if current_sub_text:
																	sub_texts.append(self.convert_tokens_to_string(UpperCamelCase_					)					)

										# Mimic the behavior of the Rust tokenizer:
										# By default, there are no spaces between special tokens
										lowerCamelCase_       :							str									=''''''.join(UpperCamelCase_					)

										lowerCamelCase_       :							int									=(
										    clean_up_tokenization_spaces
										    if clean_up_tokenization_spaces is not None
										    else self.clean_up_tokenization_spaces
										)
										if clean_up_tokenization_spaces:
																	lowerCamelCase_       :							List[Any]									=self.clean_up_tokenization(UpperCamelCase_					)
																	return clean_text
										else:
																	return text


			def 	UpperCAmelCase__						(      self     :  int   ,       snake_case__     :  Dict   ,       snake_case__     :  str = None					):
										lowerCamelCase_       :							str									=[self.sep_token_id]
										lowerCamelCase_       :							Any									=[self.cls_token_id]
										if token_ids_a is None:
																	return token_ids_a + sep + cls
										return token_ids_a + sep + token_ids_a + sep + cls


			def 	UpperCAmelCase__						(      self     :  Any   ,       snake_case__     :  List[str]   ,       snake_case__     :  Tuple = None   ,       snake_case__     :  str = False					):


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

										if token_ids_a is not None:
																	return ([0] * len(UpperCamelCase_					)) + [1] + ([0] * len(UpperCamelCase_					)) + [1, 1]
										return ([0] * len(UpperCamelCase_					)) + [1, 1]


			def 	UpperCAmelCase__						(      self     :  Any   ,       snake_case__     :  List[str]   ,       snake_case__     :  str = None					):
										lowerCamelCase_       :							Optional[int]									=[self.sep_token_id]
										lowerCamelCase_       :							List[str]									=[2]

										if token_ids_a is None:
																	return len(token_ids_a + sep					) * [0] + cls_segment_id
										return len(token_ids_a + sep					) * [0] + len(token_ids_a + sep					) * [1] + cls_segment_id


			def 	UpperCAmelCase__						(      self     :  List[str]   ,       snake_case__     :  List[Any]   ,       snake_case__     :  str = None					):


										if not os.path.isdir(UpperCamelCase_					):
																	logger.error(F"""Vocabulary path ({save_directory}) should be a directory"""					)
																	return
										lowerCamelCase_       :							Optional[int]									=os.path.join(
										    UpperCamelCase_   ,       (filename_prefix + "-" if filename_prefix else "") + VOCAB_FILES_NAMES["vocab_file"]					)

										if os.path.abspath(self.vocab_file					) != os.path.abspath(UpperCamelCase_					) and os.path.isfile(self.vocab_file					):
																	copyfile(self.vocab_file   ,       UpperCamelCase_					)
										elif not os.path.isfile(self.vocab_file					):
																	with open(UpperCamelCase_   ,       "wb"					) as fi:
																								lowerCamelCase_       :							Dict									=self.sp_model.serialized_model_proto()
																								fi.write(UpperCamelCase_					)

										return (out_vocab_file,)







'''simple docstring'''
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 			a      (			)  ->	List[str]:



					'''simple docstring'''






					UpperCamelCase__   :List[str]												= Github(os.environ['''GITHUB_TOKEN''']   )
					UpperCamelCase__   :Tuple												= g.get_repo('''huggingface/transformers'''   )
					UpperCamelCase__   :Union[str, Any]												= repo.get_issues(state='''open'''   )

					for issue in open_issues:
										UpperCamelCase__   :List[Any]												= sorted([comment for comment in issue.get_comments()] ,					key=lambda __a   : i.created_at ,					reverse=__a   )
										UpperCamelCase__   :List[Any]												= comments[0] if len(__a   ) > 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()