






'''simple docstring'''



import os
from datetime import datetime as dt

from github import Github


__A		=[
    'good first issue',
    'good second issue',
    'good difficult issue',
    'enhancement',
    'new pipeline/model',
    'new scheduler',
    'wip',
]







def       _UpperCamelCase (						):
			UpperCAmelCase__					:   List[Any]       				=       Github(os.environ["""GITHUB_TOKEN"""]   )
			UpperCAmelCase__					:   Tuple       				=       g.get_repo("""huggingface/diffusers"""   )
			UpperCAmelCase__					:   List[str]       				=       repo.get_issues(state="""open"""   )

			for issue in open_issues:
						UpperCAmelCase__					:   int       				=       sorted(issue.get_comments()	, key=lambda UpperCamelCase__   : i.created_at	, reverse=SCREAMING_SNAKE_CASE__   )
						UpperCAmelCase__					:   List[Any]       				=       comments[0] if len(SCREAMING_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 >= 3_0
						    and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()   )
						):
									# Closes the issue after 7 days of inactivity since the Stalebot notification.
									issue.edit(state="""closed"""   )
						elif (
						    "stale" in issue.get_labels()
						    and last_comment is not None
						    and last_comment.user.login != "github-actions[bot]"
						):
									# Opens the issue if someone other than Stalebot commented.
									issue.edit(state="""open"""   )
									issue.remove_from_labels("""stale"""   )
						elif (
						    (dt.utcnow() - issue.updated_at).days > 2_3
						    and (dt.utcnow() - issue.created_at).days >= 3_0
						    and not any(label.name.lower() in LABELS_TO_EXEMPT for label in issue.get_labels()   )
						):
									# Post a Stalebot notification after 23 days of inactivity.
									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/diffusers/blob/main/CONTRIBUTING.md) """
									    """are likely to be ignored."""   )
									issue.add_to_labels("""stale"""   )


if __name__ == "__main__":
		main()



'''simple docstring'''



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

import sentencepiece as spm

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


__A		=logging.get_logger(__name__)

__A		='▁'

__A		={'vocab_file': 'sentencepiece.bpe.model'}

__A		={
    'vocab_file': {
        'facebook/mbart-large-50-one-to-many-mmt': (
            'https://huggingface.co/facebook/mbart-large-50-one-to-many-mmt/resolve/main/sentencepiece.bpe.model'
        ),
    }
}

__A		={
    'facebook/mbart-large-50-one-to-many-mmt': 10_24,
}

# fmt: off
__A		=['ar_AR', 'cs_CZ', 'de_DE', 'en_XX', 'es_XX', 'et_EE', 'fi_FI', 'fr_XX', 'gu_IN', 'hi_IN', 'it_IT', 'ja_XX', 'kk_KZ', 'ko_KR', 'lt_LT', 'lv_LV', 'my_MM', 'ne_NP', 'nl_XX', 'ro_RO', 'ru_RU', 'si_LK', 'tr_TR', 'vi_VN', 'zh_CN', 'af_ZA', 'az_AZ', 'bn_IN', 'fa_IR', 'he_IL', 'hr_HR', 'id_ID', 'ka_GE', 'km_KH', 'mk_MK', 'ml_IN', 'mn_MN', 'mr_IN', 'pl_PL', 'ps_AF', 'pt_XX', 'sv_SE', 'sw_KE', 'ta_IN', 'te_IN', 'th_TH', 'tl_XX', 'uk_UA', 'ur_PK', 'xh_ZA', 'gl_ES', 'sl_SI']


class 						_snake_case   (       a__		):
					lowerCAmelCase :int						=   VOCAB_FILES_NAMES
					lowerCAmelCase :Dict						=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
					lowerCAmelCase :str						=   PRETRAINED_VOCAB_FILES_MAP
					lowerCAmelCase :List[str]						=   ['''input_ids''', '''attention_mask''']

					lowerCAmelCase :List[int]						=   []
					lowerCAmelCase :List[int]						=   []




					def __init__( self							,							_lowerCamelCase							,							_lowerCamelCase=None							,							_lowerCamelCase=None							,							_lowerCamelCase="</s>"							,							_lowerCamelCase="</s>"							,							_lowerCamelCase="<s>"							,							_lowerCamelCase="<unk>"							,							_lowerCamelCase="<pad>"							,							_lowerCamelCase="<mask>"							,							_lowerCamelCase = None							,							**_lowerCamelCase							,							):
								# Mask token behave like a normal word, i.e. include the space before it
								UpperCAmelCase__					:   List[str]       				=       AddedToken(_lowerCamelCase							,							lstrip=_lowerCamelCase							,							rstrip=_lowerCamelCase) if isinstance(_lowerCamelCase							,							_lowerCamelCase) else mask_token

								UpperCAmelCase__					:   Dict       				=       {} if sp_model_kwargs is None else sp_model_kwargs

								UpperCAmelCase__					:   Dict       				=       kwargs.get("""additional_special_tokens"""							,							[])
								kwargs["additional_special_tokens"] += [
								    code for code in FAIRSEQ_LANGUAGE_CODES if code not in kwargs["additional_special_tokens"]
								]

								super().__init__(
								    src_lang=_lowerCamelCase							,							tgt_lang=_lowerCamelCase							,							eos_token=_lowerCamelCase							,							unk_token=_lowerCamelCase							,							sep_token=_lowerCamelCase							,							cls_token=_lowerCamelCase							,							pad_token=_lowerCamelCase							,							mask_token=_lowerCamelCase							,							sp_model_kwargs=self.sp_model_kwargs							,							**_lowerCamelCase							,							)

								UpperCAmelCase__					:   str       				=       spm.SentencePieceProcessor(**self.sp_model_kwargs)
								self.sp_model.Load(str(_lowerCamelCase))
								UpperCAmelCase__					:   int       				=       vocab_file

								# Original fairseq vocab and spm vocab must be "aligned":
								# Vocab    |    0    |    1    |   2    |    3    |  4  |  5  |  6  |   7   |   8   |  9
								# -------- | ------- | ------- | ------ | ------- | --- | --- | --- | ----- | ----- | ----
								# fairseq  | '<s>'   | '<pad>' | '</s>' | '<unk>' | ',' | '.' | '▁' | 's'   | '▁de' | '-'
								# spm      | '<unk>' | '<s>'   | '</s>' | ','     | '.' | '▁' | 's' | '▁de' | '-'   | '▁a'

								# Mimic fairseq token-to-id alignment for the first 4 token
								UpperCAmelCase__					:   Union[str, Any]       				=       {"""<s>""": 0, """<pad>""": 1, """</s>""": 2, """<unk>""": 3}

								# The first "real" token "," has position 4 in the original fairseq vocab and position 3 in the spm vocab
								UpperCAmelCase__					:   List[str]       				=       1

								UpperCAmelCase__					:   Optional[int]       				=       len(self.sp_model)
								UpperCAmelCase__					:   List[str]       				=       {
								    code: self.sp_model_size + i + self.fairseq_offset for i, code in enumerate(_lowerCamelCase)
								}
								UpperCAmelCase__					:   Optional[int]       				=       {v: k for k, v in self.lang_code_to_id.items()}
								UpperCAmelCase__					:   Optional[int]       				=       len(self.sp_model) + len(self.lang_code_to_id) + self.fairseq_offset

								self.fairseq_tokens_to_ids.update(self.lang_code_to_id)
								UpperCAmelCase__					:   Union[str, Any]       				=       {v: k for k, v in self.fairseq_tokens_to_ids.items()}

								UpperCAmelCase__					:   Dict       				=       src_lang if src_lang is not None else """en_XX"""
								UpperCAmelCase__					:   str       				=       self.lang_code_to_id[self._src_lang]
								UpperCAmelCase__					:   Tuple       				=       tgt_lang
								self.set_src_lang_special_tokens(self._src_lang)




					@property
					def 			snake_case__  ( self):
								return len(self.sp_model) + len(self.lang_code_to_id) + self.fairseq_offset + 1  # Plus 1 for the mask token




					@property
					def 			snake_case__  ( self):
								return self._src_lang




					@src_lang.setter
					def 			snake_case__  ( self							,							_lowerCamelCase):
								UpperCAmelCase__					:   str       				=       new_src_lang
								self.set_src_lang_special_tokens(self._src_lang)




					def __getstate__( self):
								UpperCAmelCase__					:   int       				=       self.__dict__.copy()
								UpperCAmelCase__					:   Tuple       				=       None
								return state




					def __setstate__( self							,							_lowerCamelCase):
								UpperCAmelCase__					:   Union[str, Any]       				=       d

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

								UpperCAmelCase__					:   Any       				=       spm.SentencePieceProcessor(**self.sp_model_kwargs)
								self.sp_model.Load(self.vocab_file)




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




					def 			snake_case__  ( self							,							_lowerCamelCase):
								return self.sp_model.encode(_lowerCamelCase							,							out_type=_lowerCamelCase)




					def 			snake_case__  ( self							,							_lowerCamelCase):
								if token in self.fairseq_tokens_to_ids:
											return self.fairseq_tokens_to_ids[token]
								UpperCAmelCase__					:   Dict       				=       self.sp_model.PieceToId(_lowerCamelCase)

								# Need to return unknown token if the SP model returned 0
								return spm_id + self.fairseq_offset if spm_id else self.unk_token_id




					def 			snake_case__  ( self							,							_lowerCamelCase):
								if index in self.fairseq_ids_to_tokens:
											return self.fairseq_ids_to_tokens[index]
								return self.sp_model.IdToPiece(index - self.fairseq_offset)




					def 			snake_case__  ( self							,							_lowerCamelCase):
								UpperCAmelCase__					:   Optional[Any]       				=       []
								UpperCAmelCase__					:   List[Any]       				=       """"""
								UpperCAmelCase__					:   Optional[int]       				=       False
								for token in tokens:
											# make sure that special tokens are not decoded using sentencepiece model
											if token in self.all_special_tokens:
														if not prev_is_special:
																	out_string += " "
														out_string += self.sp_model.decode(_lowerCamelCase) + token
														UpperCAmelCase__					:   Tuple       				=       True
														UpperCAmelCase__					:   List[str]       				=       []
											else:
														current_sub_tokens.append(_lowerCamelCase)
														UpperCAmelCase__					:   Dict       				=       False
								out_string += self.sp_model.decode(_lowerCamelCase)
								return out_string.strip()




					def 			snake_case__  ( self							,							_lowerCamelCase							,							_lowerCamelCase = None):
								if not os.path.isdir(_lowerCamelCase):
											logger.error(f'''Vocabulary path ({save_directory}) should be a directory''')
											return
								UpperCAmelCase__					:   Any       				=       os.path.join(
								    _lowerCamelCase							,							(filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""])

								if os.path.abspath(self.vocab_file) != os.path.abspath(_lowerCamelCase) and os.path.isfile(self.vocab_file):
											copyfile(self.vocab_file							,							_lowerCamelCase)
								elif not os.path.isfile(self.vocab_file):
											with open(_lowerCamelCase							,							"""wb""") as fi:
														UpperCAmelCase__					:   List[str]       				=       self.sp_model.serialized_model_proto()
														fi.write(_lowerCamelCase)

								return (out_vocab_file,)




					def 			snake_case__  ( self							,							_lowerCamelCase							,							_lowerCamelCase = None							,							_lowerCamelCase = False):

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

								UpperCAmelCase__					:   Tuple       				=       [1] * len(self.prefix_tokens)
								UpperCAmelCase__					:   Dict       				=       [1] * len(self.suffix_tokens)
								if token_ids_a is None:
											return prefix_ones + ([0] * len(_lowerCamelCase)) + suffix_ones
								return prefix_ones + ([0] * len(_lowerCamelCase)) + ([0] * len(_lowerCamelCase)) + suffix_ones




					def 			snake_case__  ( self							,							_lowerCamelCase							,							_lowerCamelCase = None):
								if token_ids_a is None:
											return self.prefix_tokens + token_ids_a + self.suffix_tokens
								# We don't expect to process pairs, but leave the pair logic for API consistency
								return self.prefix_tokens + token_ids_a + token_ids_a + self.suffix_tokens




					def 			snake_case__  ( self							,							_lowerCamelCase							,							_lowerCamelCase							,							_lowerCamelCase							,							_lowerCamelCase							,							**_lowerCamelCase):
								if src_lang is None or tgt_lang is None:
											raise ValueError("""Translation requires a `src_lang` and a `tgt_lang` for this model""")
								UpperCAmelCase__					:   Any       				=       src_lang
								UpperCAmelCase__					:   Dict       				=       self(_lowerCamelCase							,							add_special_tokens=_lowerCamelCase							,							return_tensors=_lowerCamelCase							,							**_lowerCamelCase)
								UpperCAmelCase__					:   List[Any]       				=       self.convert_tokens_to_ids(_lowerCamelCase)
								UpperCAmelCase__					:   List[str]       				=       tgt_lang_id
								return inputs




					def 			snake_case__  ( self							,							_lowerCamelCase							,							_lowerCamelCase = "en_XX"							,							_lowerCamelCase = None							,							_lowerCamelCase = "ro_RO"							,							**_lowerCamelCase							,							):
								UpperCAmelCase__					:   Tuple       				=       src_lang
								UpperCAmelCase__					:   Optional[Any]       				=       tgt_lang
								return super().prepare_seqaseq_batch(_lowerCamelCase							,							_lowerCamelCase							,							**_lowerCamelCase)




					def 			snake_case__  ( self):
								return self.set_src_lang_special_tokens(self.src_lang)




					def 			snake_case__  ( self):
								return self.set_tgt_lang_special_tokens(self.tgt_lang)




					def 			snake_case__  ( self							,							_lowerCamelCase):
								UpperCAmelCase__					:   Tuple       				=       self.lang_code_to_id[src_lang]
								UpperCAmelCase__					:   Optional[int]       				=       [self.cur_lang_code_id]
								UpperCAmelCase__					:   Optional[int]       				=       [self.eos_token_id]




					def 			snake_case__  ( self							,							_lowerCamelCase):
								UpperCAmelCase__					:   List[Any]       				=       self.lang_code_to_id[tgt_lang]
								UpperCAmelCase__					:   Dict       				=       [self.cur_lang_code_id]
								UpperCAmelCase__					:   Optional[int]       				=       [self.eos_token_id]