



import os
import zipfile

import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links






def 				A				(					_lowerCamelCase				, _lowerCamelCase=7  ):





							'''simple docstring'''




							_lowerCAmelCase     :							Any    =    None
							if token is not None:
														_lowerCAmelCase     :							Tuple    =    {"Accept": "application/vnd.github+json", "Authorization": F"Bearer {token}"}

							# The id of a workflow (not of a workflow run)
							_lowerCAmelCase     :							Any    =    "636036"

							_lowerCAmelCase     :							List[Any]    =    F"https://api.github.com/repos/huggingface/transformers/actions/workflows/{workflow_id}/runs"
							# On `main` branch + event being `schedule` + not returning PRs + only `num_runs` results
							url += F"?branch=main&event=schedule&exclude_pull_requests=true&per_page={num_runs}"

							_lowerCAmelCase     :							Optional[int]    =    requests.get(_lowerCamelCase				, headers=_lowerCamelCase  ).json()

							return result["workflow_runs"]






def 				A				(					_lowerCamelCase  ):





							'''simple docstring'''




							_lowerCAmelCase     :							str    =    get_daily_ci_runs(_lowerCamelCase  )
							_lowerCAmelCase     :							List[Any]    =    None
							for workflow_run in workflow_runs:
														if workflow_run["status"] == "completed":
																					_lowerCAmelCase     :							str    =    workflow_run["id"]
																					break

							return workflow_run_id






def 				A				(					_lowerCamelCase				, _lowerCamelCase				, _lowerCamelCase  ):





							'''simple docstring'''




							_lowerCAmelCase     :							Any    =    get_last_daily_ci_runs(_lowerCamelCase  )
							if workflow_run_id is not None:
														_lowerCAmelCase     :							int    =    get_artifacts_links(worflow_run_id=_lowerCamelCase				, token=_lowerCamelCase  )
														for artifact_name in artifact_names:
																					if artifact_name in artifacts_links:
																												_lowerCAmelCase     :							Optional[int]    =    artifacts_links[artifact_name]
																												download_artifact(
																												    artifact_name=_lowerCamelCase				, artifact_url=_lowerCamelCase				, output_dir=_lowerCamelCase				, token=_lowerCamelCase  )






def 				A				(					_lowerCamelCase				, _lowerCamelCase				, _lowerCamelCase  ):





							'''simple docstring'''




							get_last_daily_ci_artifacts(_lowerCamelCase				, _lowerCamelCase				, _lowerCamelCase  )

							_lowerCAmelCase     :							str    =    {}
							for artifact_name in artifact_names:
														_lowerCAmelCase     :							Optional[int]    =    os.path.join(_lowerCamelCase				, F"{artifact_name}.zip"  )
														if os.path.isfile(_lowerCamelCase  ):
																					_lowerCAmelCase     :							Dict    =    {}
																					with zipfile.ZipFile(_lowerCamelCase  ) as z:
																												for filename in z.namelist():
																																			if not os.path.isdir(_lowerCamelCase  ):
																																										# read the file
																																										with z.open(_lowerCamelCase  ) as f:
																																																	_lowerCAmelCase     :							str    =    f.read().decode("UTF-8"  )

							return results


'''simple docstring'''




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

from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging


if is_sentencepiece_available():
      from .tokenization_rembert import RemBertTokenizer
else:
      lowercase			:				Optional[Any]    		=			None

lowercase			:				Tuple    		=			logging.get_logger(__name__)
lowercase			:				Dict    		=			{'vocab_file': 'sentencepiece.model', 'tokenizer_file': 'tokenizer.json'}

lowercase			:				Tuple    		=			{
    'vocab_file': {
        'google/rembert': 'https://huggingface.co/google/rembert/resolve/main/sentencepiece.model',
    },
    'tokenizer_file': {
        'google/rembert': 'https://huggingface.co/google/rembert/resolve/main/tokenizer.json',
    },
}

lowercase			:				List[str]    		=			{
    'google/rembert': 2_56,
}

lowercase			:				Dict    		=			'▁'





class  A				(							__snake_case						):
     __magic_name__						=		VOCAB_FILES_NAMES
     __magic_name__						=		PRETRAINED_VOCAB_FILES_MAP
     __magic_name__						=		PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
     __magic_name__						=		RemBertTokenizer





     def __init__(							self						,			SCREAMING_SNAKE_CASE=None						,			SCREAMING_SNAKE_CASE=None						,			SCREAMING_SNAKE_CASE=True						,			SCREAMING_SNAKE_CASE=True						,			SCREAMING_SNAKE_CASE=False						,			SCREAMING_SNAKE_CASE="[CLS]"						,			SCREAMING_SNAKE_CASE="[SEP]"						,			SCREAMING_SNAKE_CASE="<unk>"						,			SCREAMING_SNAKE_CASE="[SEP]"						,			SCREAMING_SNAKE_CASE="<pad>"						,			SCREAMING_SNAKE_CASE="[CLS]"						,			SCREAMING_SNAKE_CASE="[MASK]"						,			**SCREAMING_SNAKE_CASE						,			) ->				List[str]:






         """simple docstring"""






         A       :   Optional[Any]					=						AddedToken(SCREAMING_SNAKE_CASE						,			lstrip=SCREAMING_SNAKE_CASE						,			rstrip=SCREAMING_SNAKE_CASE	) if isinstance(SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE	) else mask_token

         super().__init__(
             SCREAMING_SNAKE_CASE						,			tokenizer_file=SCREAMING_SNAKE_CASE						,			do_lower_case=SCREAMING_SNAKE_CASE						,			remove_space=SCREAMING_SNAKE_CASE						,			keep_accents=SCREAMING_SNAKE_CASE						,			bos_token=SCREAMING_SNAKE_CASE						,			eos_token=SCREAMING_SNAKE_CASE						,			unk_token=SCREAMING_SNAKE_CASE						,			sep_token=SCREAMING_SNAKE_CASE						,			pad_token=SCREAMING_SNAKE_CASE						,			cls_token=SCREAMING_SNAKE_CASE						,			mask_token=SCREAMING_SNAKE_CASE						,			**SCREAMING_SNAKE_CASE						,			)

         A       :   List[Any]					=						do_lower_case
         A       :   str					=						remove_space
         A       :   int					=						keep_accents
         A       :   Union[str, Any]					=						vocab_file
         A       :   List[Any]					=						False if not self.vocab_file else True





     def 				__lowerCAmelCase							(							self						,			SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE = None	) ->				List[int]:






         """simple docstring"""






         A       :   List[Any]					=						[self.sep_token_id]
         A       :   Tuple					=						[self.cls_token_id]
         if token_ids_a is None:
             return cls + token_ids_a + sep
         return cls + token_ids_a + sep + token_ids_a + sep





     def 				__lowerCAmelCase							(							self						,			SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE = None						,			SCREAMING_SNAKE_CASE = False	) ->				List[int]:






         """simple docstring"""






         if already_has_special_tokens:
             if token_ids_a is not None:
                 raise ValueError(
                     '''You should not supply a second sequence if the provided sequence of '''
                     '''ids is already formatted with special tokens for the model.'''	)
             return [1 if x in [self.sep_token_id, self.cls_token_id] else 0 for x in token_ids_a]

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





     def 				__lowerCAmelCase							(							self						,			SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE = None	) ->				List[int]:






         """simple docstring"""






         A       :   Tuple					=						[self.sep_token_id]
         A       :   Dict					=						[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	) * [0] + len(token_ids_a + sep	) * [1]





     def 				__lowerCAmelCase							(							self						,			SCREAMING_SNAKE_CASE						,			SCREAMING_SNAKE_CASE = None	) ->				Tuple[str]:






         """simple docstring"""






         if not os.path.isdir(SCREAMING_SNAKE_CASE	):
             logger.error('''Vocabulary path ({}) should be a directory'''.format(SCREAMING_SNAKE_CASE	)	)
             return
         A       :   Any					=						os.path.join(
             SCREAMING_SNAKE_CASE						,			(filename_prefix + '''-''' if filename_prefix else '''''') + VOCAB_FILES_NAMES['''vocab_file''']	)

         if os.path.abspath(self.vocab_file	) != os.path.abspath(SCREAMING_SNAKE_CASE	):
             copyfile(self.vocab_file						,			SCREAMING_SNAKE_CASE	)

         return (out_vocab_file,)




