






from datetime import datetime as dt
import os

from github import Github


A        =			[
    'good first issue',
    'good second issue',
    'good difficult issue',
    'feature request',
    'new model',
    'wip',
]



def 					_lowerCamelCase(			):





				'''simple docstring'''







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

				for issue in open_issues:
								SCREAMING_SNAKE_CASE_   :	Tuple													=   sorted([comment for comment in issue.get_comments()]    ,    key=lambda lowerCAmelCase__      : i.created_at    ,    reverse=lowerCAmelCase__      )
								SCREAMING_SNAKE_CASE_   :	Tuple													=   comments[0] if len(lowerCAmelCase__      ) > 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()







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

import sentencepiece as spm

from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging


A        =			logging.get_logger(__name__)

A        =			{'vocab_file': 'spm_char.model'}

A        =			{
    'vocab_file': {
        'microsoft/speecht5_asr': 'https://huggingface.co/microsoft/speecht5_asr/resolve/main/spm_char.model',
        'microsoft/speecht5_tts': 'https://huggingface.co/microsoft/speecht5_tts/resolve/main/spm_char.model',
        'microsoft/speecht5_vc': 'https://huggingface.co/microsoft/speecht5_vc/resolve/main/spm_char.model',
    }
}

A        =			{
    'microsoft/speecht5_asr': 1024,
    'microsoft/speecht5_tts': 1024,
    'microsoft/speecht5_vc': 1024,
}


class 							__a							(  __A						):





		'''simple docstring'''



		UpperCAmelCase__      :				str				    =						VOCAB_FILES_NAMES
		UpperCAmelCase__      :				List[str]				    =						PRETRAINED_VOCAB_FILES_MAP
		UpperCAmelCase__      :				Optional[int]				    =						PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
		UpperCAmelCase__      :				Dict				    =						["""input_ids""", """attention_mask"""]


		def __init__(						self ,    UpperCamelCase__ ,    UpperCamelCase__="<s>" ,    UpperCamelCase__="</s>" ,    UpperCamelCase__="<unk>" ,    UpperCamelCase__="<pad>" ,    UpperCamelCase__ = None ,    **UpperCamelCase__ ,    ):
						SCREAMING_SNAKE_CASE_   :	Union[str, Any]													=   {} if sp_model_kwargs is None else sp_model_kwargs

						super().__init__(
						    bos_token=UpperCamelCase__ ,    eos_token=UpperCamelCase__ ,    unk_token=UpperCamelCase__ ,    pad_token=UpperCamelCase__ ,    sp_model_kwargs=self.sp_model_kwargs ,    **UpperCamelCase__ ,    )

						SCREAMING_SNAKE_CASE_   :	Optional[Any]													=   vocab_file

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


		@property
		def   __snake_case			(						self       ):
						return self.sp_model.get_piece_size()


		def   __snake_case			(						self       ):
						SCREAMING_SNAKE_CASE_   :	List[str]													=   {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       ):
						SCREAMING_SNAKE_CASE_   :	str													=   self.__dict__.copy()
						SCREAMING_SNAKE_CASE_   :	List[str]													=   None
						return state


		def __setstate__(						self ,    UpperCamelCase__       ):
						SCREAMING_SNAKE_CASE_   :	Union[str, Any]													=   d

						# for backward compatibility
						if not hasattr(self ,    'sp_model_kwargs'       ):
										SCREAMING_SNAKE_CASE_   :	Any													=   {}

						SCREAMING_SNAKE_CASE_   :	List[Any]													=   spm.SentencePieceProcessor(**self.sp_model_kwargs       )
						self.sp_model.Load(self.vocab_file       )


		def   __snake_case			(						self ,    UpperCamelCase__       ):
						return self.sp_model.encode(UpperCamelCase__ ,    out_type=UpperCamelCase__       )


		def   __snake_case			(						self ,    UpperCamelCase__       ):
						return self.sp_model.piece_to_id(UpperCamelCase__       )


		def   __snake_case			(						self ,    UpperCamelCase__       ):
						SCREAMING_SNAKE_CASE_   :	Union[str, Any]													=   self.sp_model.IdToPiece(UpperCamelCase__       )
						return token


		def   __snake_case			(						self ,    UpperCamelCase__       ):
						SCREAMING_SNAKE_CASE_   :	int													=   []
						SCREAMING_SNAKE_CASE_   :	int													=   ''
						for token in tokens:
										# make sure that special tokens are not decoded using sentencepiece model
										if token in self.all_special_tokens:
														out_string += self.sp_model.decode(UpperCamelCase__       ) + token
														SCREAMING_SNAKE_CASE_   :	Any													=   []
										else:
														current_sub_tokens.append(UpperCamelCase__       )
						out_string += self.sp_model.decode(UpperCamelCase__       )
						return out_string.strip()


		def   __snake_case			(						self ,    UpperCamelCase__ ,    UpperCamelCase__=None       ):
						if token_ids_a is None:
										return token_ids_a + [self.eos_token_id]
						# We don't expect to process pairs, but leave the pair logic for API consistency
						return token_ids_a + token_ids_a + [self.eos_token_id]


		def   __snake_case			(						self ,    UpperCamelCase__ ,    UpperCamelCase__ = None ,    UpperCamelCase__ = 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__       )

						SCREAMING_SNAKE_CASE_   :	Union[str, Any]													=   [1]
						if token_ids_a is None:
										return ([0] * len(UpperCamelCase__       )) + suffix_ones
						return ([0] * len(UpperCamelCase__       )) + ([0] * len(UpperCamelCase__       )) + suffix_ones






		def   __snake_case			(						self ,    UpperCamelCase__ ,    UpperCamelCase__ = None       ):
						if not os.path.isdir(UpperCamelCase__       ):
										logger.error(F'''Vocabulary path ({save_directory}) should be a directory'''       )
										return
						SCREAMING_SNAKE_CASE_   :	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:
														SCREAMING_SNAKE_CASE_   :	Tuple													=   self.sp_model.serialized_model_proto()
														fi.write(UpperCamelCase__       )

						return (out_vocab_file,)