
'''simple docstring'''
import io
import os
import unicodedata
from typing import Any, Dict, List, Optional, Tuple

import sentencepiece as spm

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


A__   :		Any 		=logging.get_logger(__name__)

A__   :		int 		='▁'

A__   :		Dict 		={'vocab_file': 'vocab.txt', 'sentencepiece_model_ckpt': 'sentencepiece.bpe.model'}

A__   :		List[str] 		={
    'sentencepiece_model_file': 'sentencepiece.bpe.model',
    'vocab_file': 'vocab.txt',
}

A__   :		Union[str, Any] 		={
    'vocab_file': {
        'ernie-m-base': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/vocab.txt',
        'ernie-m-large': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/vocab.txt',
    },
    'sentencepiece_model_file': {
        'ernie-m-base': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/sentencepiece.bpe.model',
        'ernie-m-large': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/sentencepiece.bpe.model',
    },
}

A__   :		Dict 		={
    'ernie-m-base': 514,
    'ernie-m-large': 514,
}

A__   :		List[Any] 		={
    'ernie-m-base': {'do_lower_case': False},
    'ernie-m-large': {'do_lower_case': False},
}







class  __A				( _SCREAMING_SNAKE_CASE			):
 lowerCamelCase				       =["input_ids"]

 lowerCamelCase				       =VOCAB_FILES_NAMES
 lowerCamelCase				       =PRETRAINED_INIT_CONFIGURATION
 lowerCamelCase				       =PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
 lowerCamelCase				       =PRETRAINED_VOCAB_FILES_MAP
 lowerCamelCase				       =RESOURCE_FILES_NAMES
 def __init__(   self			:    Optional[Any]				,   lowerCamelCase			:    Optional[int]				,   lowerCamelCase			:    Union[str, Any]=None				,   lowerCamelCase			:    Optional[Any]=False				,   lowerCamelCase			:    Optional[Any]="utf8"				,   lowerCamelCase			:    Union[str, Any]="[UNK]"				,   lowerCamelCase			:    str="[SEP]"				,   lowerCamelCase			:    Dict="[PAD]"				,   lowerCamelCase			:    List[str]="[CLS]"				,   lowerCamelCase			:    List[str]="[MASK]"				,   lowerCamelCase			:    Optional[Dict[str, Any]] = None				,   **lowerCamelCase			:    Union[str, Any]				,   ):



   """simple docstring"""





   __A		:     Optional[Any]												=		{} if sp_model_kwargs is None else sp_model_kwargs
   super().__init__(
       do_lower_case=lowerCamelCase				,   unk_token=lowerCamelCase				,   sep_token=lowerCamelCase				,   pad_token=lowerCamelCase				,   cls_token=lowerCamelCase				,   mask_token=lowerCamelCase				,   vocab_file=lowerCamelCase				,   encoding=lowerCamelCase				,   sp_model_kwargs=self.sp_model_kwargs				,   **lowerCamelCase				,   )
   __A		:     Union[str, Any]												=		do_lower_case
   __A		:     int												=		sentencepiece_model_ckpt
   __A		:     List[Any]												=		spm.SentencePieceProcessor(**self.sp_model_kwargs       )
   self.sp_model.Load(lowerCamelCase       )

   # to mimic paddlenlp.transformers.ernie_m.tokenizer.ErnieMTokenizer functioning
   if vocab_file is not None:
     __A		:     Dict												=		self.load_vocab(filepath=lowerCamelCase       )
   else:
     __A		:     List[Any]												=		{self.sp_model.id_to_piece(lowerCamelCase       ): id for id in range(self.sp_model.get_piece_size()       )}
   __A		:     Tuple												=		{v: k for k, v in self.vocab.items()}
 def 		lowercase_(   self			:    str				,   lowerCamelCase			:    str       ):



   """simple docstring"""





   if text is None:
     return None

   __A		:     List[str]												=		self.tokenize(lowerCamelCase       )
   __A							,					__A		:     Any												=		"""""", []

   for i, ch in enumerate(lowerCamelCase       ):
     if ch in self.SP_CHAR_MAPPING:
       __A		:     List[str]												=		self.SP_CHAR_MAPPING.get(lowerCamelCase       )
     else:
       __A		:     Tuple												=		unicodedata.normalize("""NFKC"""				,   lowerCamelCase       )
     if self.is_whitespace(lowerCamelCase       ):
       continue
     normalized_text += ch
     char_mapping.extend([i] * len(lowerCamelCase       )       )

   __A							,					__A							,					__A		:     int												=		normalized_text, [], 0

   if self.do_lower_case:
     __A		:     Optional[Any]												=		text.lower()

   for token in split_tokens:
     if token[:1] == "▁":
       __A		:     List[str]												=		token[1:]
     __A		:     str												=		text[offset:].index(lowerCamelCase       ) + offset
     __A		:     int												=		start + len(lowerCamelCase       )

     token_mapping.append((char_mapping[start], char_mapping[end - 1] + 1)       )
     __A		:     Optional[int]												=		end
   return token_mapping
 @property
 def 		lowercase_(   self			:    str       ):



   """simple docstring"""





   return len(self.vocab       )
 def 		lowercase_(   self			:    Dict       ):



   """simple docstring"""





   return dict(self.vocab				,   **self.added_tokens_encoder       )
 def __getstate__(   self			:    List[str]       ):



   """simple docstring"""





   __A		:     Optional[Any]												=		self.__dict__.copy()
   __A		:     str												=		None
   return state
 def __setstate__(   self			:    int				,   lowerCamelCase			:    Union[str, Any]       ):



   """simple docstring"""





   __A		:     str												=		d

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

   __A		:     Any												=		spm.SentencePieceProcessor(**self.sp_model_kwargs       )
   self.sp_model.Load(self.sentencepiece_model_ckpt       )
 def 		lowercase_(   self			:    int				,   lowerCamelCase			:    List[Any]       ):



   """simple docstring"""





   return "".join((self.SP_CHAR_MAPPING.get(lowerCamelCase				,   lowerCamelCase       ) for c in text)       )
 def 		lowercase_(   self			:    List[Any]				,   lowerCamelCase			:    str				,   lowerCamelCase			:    Union[str, Any]=False				,   lowerCamelCase			:    Dict=64				,   lowerCamelCase			:    str=0.1       ):



   """simple docstring"""





   if self.sp_model_kwargs.get("""enable_sampling"""       ) is True:
     __A		:     List[Any]												=		True
   if self.sp_model_kwargs.get("""alpha"""       ) is not None:
     __A		:     Dict												=		self.sp_model_kwargs.get("""alpha"""       )
   if self.sp_model_kwargs.get("""nbest_size"""       ) is not None:
     __A		:     Union[str, Any]												=		self.sp_model_kwargs.get("""nbest_size"""       )

   if not enable_sampling:
     __A		:     List[str]												=		self.sp_model.EncodeAsPieces(lowerCamelCase       )
   else:
     __A		:     Optional[int]												=		self.sp_model.SampleEncodeAsPieces(lowerCamelCase				,   lowerCamelCase				,   lowerCamelCase       )
   __A		:     List[str]												=		[]
   for pi, piece in enumerate(lowerCamelCase       ):
     if piece == SPIECE_UNDERLINE:
       if not pieces[pi + 1].startswith(lowerCamelCase       ) and pi != 0:
         new_pieces.append(lowerCamelCase       )
         continue
       else:
         continue
     __A		:     List[Any]												=		0
     for i, chunk in enumerate(lowerCamelCase       ):
       if chunk == SPIECE_UNDERLINE:
         continue
       if self.is_ch_char(lowerCamelCase       ) or self.is_punct(lowerCamelCase       ):
         if i > lst_i and piece[lst_i:i] != SPIECE_UNDERLINE:
           new_pieces.append(piece[lst_i:i]       )
         new_pieces.append(lowerCamelCase       )
         __A		:     int												=		i + 1
       elif chunk.isdigit() and i > 0 and not piece[i - 1].isdigit():
         if i > lst_i and piece[lst_i:i] != SPIECE_UNDERLINE:
           new_pieces.append(piece[lst_i:i]       )
         __A		:     Dict												=		i
       elif not chunk.isdigit() and i > 0 and piece[i - 1].isdigit():
         if i > lst_i and piece[lst_i:i] != SPIECE_UNDERLINE:
           new_pieces.append(piece[lst_i:i]       )
         __A		:     Tuple												=		i
     if len(lowerCamelCase       ) > lst_i:
       new_pieces.append(piece[lst_i:]       )
   return new_pieces
 def 		lowercase_(   self			:    Any				,   lowerCamelCase			:    Tuple       ):



   """simple docstring"""





   __A		:     Optional[int]												=		"""""".join(lowerCamelCase       ).replace(lowerCamelCase				,   """ """       ).strip()
   return out_string
 def 		lowercase_(   self			:    str				,   lowerCamelCase			:    Tuple       ):



   """simple docstring"""





   __A		:     Optional[int]												=		self.convert_ids_to_tokens(lowerCamelCase       )
   __A		:     Optional[int]												=		"""""".join(lowerCamelCase       ).replace(lowerCamelCase				,   """ """       ).strip()
   return out_string
 def 		lowercase_(   self			:    Any				,   lowerCamelCase			:    List[Any]       ):



   """simple docstring"""





   return self.vocab.get(lowerCamelCase				,   self.vocab.get(self.unk_token       )       )
 def 		lowercase_(   self			:    Dict				,   lowerCamelCase			:    int       ):



   """simple docstring"""





   return self.reverse_vocab.get(lowerCamelCase				,   self.unk_token       )
 def 		lowercase_(   self			:    int				,   lowerCamelCase			:    List[Any]				,   lowerCamelCase			:    Optional[int]=None       ):



   """simple docstring"""





   if token_ids_a is None:
     return [self.cls_token_id] + token_ids_a + [self.sep_token_id]
   __A		:     Any												=		[self.cls_token_id]
   __A		:     str												=		[self.sep_token_id]
   return _cls + token_ids_a + _sep + _sep + token_ids_a + _sep
 def 		lowercase_(   self			:    Dict				,   lowerCamelCase			:    Tuple				,   lowerCamelCase			:    List[str]=None       ):



   """simple docstring"""





   if offset_mapping_a is None:
     return [(0, 0)] + offset_mapping_a + [(0, 0)]

   return [(0, 0)] + offset_mapping_a + [(0, 0), (0, 0)] + offset_mapping_a + [(0, 0)]
 def 		lowercase_(   self			:    int				,   lowerCamelCase			:    int				,   lowerCamelCase			:    List[Any]=None				,   lowerCamelCase			:    Dict=False       ):



   """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(lowerCamelCase       )) + [1, 1] + ([0] * len(lowerCamelCase       )) + [1]
   return [1] + ([0] * len(lowerCamelCase       )) + [1]
 def 		lowercase_(   self			:    Union[str, Any]				,   lowerCamelCase			:    List[int]				,   lowerCamelCase			:    Optional[List[int]] = None       ):



   """simple docstring"""





   if token_ids_a is None:
     # [CLS] X [SEP]
     return (len(lowerCamelCase       ) + 2) * [0]

   # [CLS] A [SEP] [SEP] B [SEP]
   return [0] * (len(lowerCamelCase       ) + 1) + [1] * (len(lowerCamelCase       ) + 3)
 def 		lowercase_(   self			:    Union[str, Any]				,   lowerCamelCase			:    int       ):



   """simple docstring"""





   if "\u4e00" <= char <= "\u9fff":
     return True
   return False
 def 		lowercase_(   self			:    str				,   lowerCamelCase			:    str       ):



   """simple docstring"""





   if ("a" <= char <= "z") or ("A" <= char <= "Z"):
     return True
   return False
 def 		lowercase_(   self			:    Optional[Any]				,   lowerCamelCase			:    Optional[Any]       ):



   """simple docstring"""





   if char in ",;:.?!~，；：。？！《》【】":
     return True
   return False
 def 		lowercase_(   self			:    Dict				,   lowerCamelCase			:    Union[str, Any]       ):



   """simple docstring"""





   if char == " " or char == "\t" or char == "\n" or char == "\r":
     return True
   if len(lowerCamelCase       ) == 1:
     __A		:     Any												=		unicodedata.category(lowerCamelCase       )
     if cat == "Zs":
       return True
   return False
 def 		lowercase_(   self			:    Dict				,   lowerCamelCase			:    Dict       ):



   """simple docstring"""





   __A		:     Optional[Any]												=		{}
   with io.open(lowerCamelCase				,   """r"""				,   encoding="""utf-8"""       ) as f:
     for index, line in enumerate(lowerCamelCase       ):
       __A		:     Optional[Any]												=		line.rstrip("""\n"""       )
       __A		:     List[str]												=		int(lowerCamelCase       )

   return token_to_idx






 def 		lowercase_(   self			:    int				,   lowerCamelCase			:    str				,   lowerCamelCase			:    Optional[str] = None       ):



   """simple docstring"""





   __A		:     Union[str, Any]												=		0
   if os.path.isdir(lowerCamelCase       ):
     __A		:     Dict												=		os.path.join(
         lowerCamelCase				,   (filename_prefix + """-""" if filename_prefix else """""") + VOCAB_FILES_NAMES["""vocab_file"""]       )
   else:
     __A		:     Optional[Any]												=		(filename_prefix + """-""" if filename_prefix else """""") + save_directory
   with open(lowerCamelCase				,   """w"""				,   encoding="""utf-8"""       ) as writer:
     for token, token_index in sorted(self.vocab.items()				,   key=lambda lowerCamelCase       : kv[1]       ):
       if index != token_index:
         logger.warning(
             f"Saving vocabulary to {vocab_file}: vocabulary indices are not consecutive."
             """ Please check that the vocabulary is not corrupted!"""       )
         __A		:     Optional[int]												=		token_index
       writer.write(token + """\n"""       )
       index += 1

   __A		:     Dict												=		os.path.join(lowerCamelCase				,   """sentencepiece.bpe.model"""       )
   with open(lowerCamelCase				,   """wb"""       ) as fi:
     __A		:     Optional[int]												=		self.sp_model.serialized_model_proto()
     fi.write(lowerCamelCase       )

   return (vocab_file,)





'''simple docstring'''
import os
import zipfile

import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links







def        A_     (						__SCREAMING_SNAKE_CASE						:  List[str]			,     __SCREAMING_SNAKE_CASE						:  Optional[int]=7 )				->       List[Any]:





  """simple docstring"""

  __A		:     Optional[int]												=		None
  if token is not None:
    __A		:     str												=		{"""Accept""": """application/vnd.github+json""", """Authorization""": F"Bearer {token}"}

  # The id of a workflow (not of a workflow run)
  __A		:     Union[str, Any]												=		"""636036"""

  __A		:     Optional[int]												=		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}"

  __A		:     int												=		requests.get(__SCREAMING_SNAKE_CASE			,     headers=__SCREAMING_SNAKE_CASE ).json()

  return result["workflow_runs"]







def        A_     (						__SCREAMING_SNAKE_CASE						:  Union[str, Any] )				->       Tuple:





  """simple docstring"""

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

  return workflow_run_id







def        A_     (						__SCREAMING_SNAKE_CASE						:  List[Any]			,     __SCREAMING_SNAKE_CASE						:  Any			,     __SCREAMING_SNAKE_CASE						:  Tuple )				->       Tuple:





  """simple docstring"""

  __A		:     Dict												=		get_last_daily_ci_runs(__SCREAMING_SNAKE_CASE )
  if workflow_run_id is not None:
    __A		:     str												=		get_artifacts_links(worflow_run_id=__SCREAMING_SNAKE_CASE			,     token=__SCREAMING_SNAKE_CASE )
    for artifact_name in artifact_names:
      if artifact_name in artifacts_links:
        __A		:     List[Any]												=		artifacts_links[artifact_name]
        download_artifact(
            artifact_name=__SCREAMING_SNAKE_CASE			,     artifact_url=__SCREAMING_SNAKE_CASE			,     output_dir=__SCREAMING_SNAKE_CASE			,     token=__SCREAMING_SNAKE_CASE )







def        A_     (						__SCREAMING_SNAKE_CASE						:  List[Any]			,     __SCREAMING_SNAKE_CASE						:  Optional[int]			,     __SCREAMING_SNAKE_CASE						:  Optional[Any] )				->       Union[str, Any]:





  """simple docstring"""

  get_last_daily_ci_artifacts(__SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE			,     __SCREAMING_SNAKE_CASE )

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

  return results



