




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


UpperCAmelCase_									=	logging.get_logger(__name__)

UpperCAmelCase_									=	{'vocab_file': 'spiece.model'}

UpperCAmelCase_									=	{
    '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',
    }
}

UpperCAmelCase_									=	{
    'xlnet-base-cased': None,
    'xlnet-large-cased': None,
}

# Segments (not really needed)
UpperCAmelCase_									=	0
UpperCAmelCase_									=	1
UpperCAmelCase_									=	2
UpperCAmelCase_									=	3
UpperCAmelCase_									=	4





class     lowerCamelCase__(					__lowerCamelCase):
      UpperCAmelCase__      :	List[Any]    		=   VOCAB_FILES_NAMES
      UpperCAmelCase__      :	Optional[Any]    		=   PRETRAINED_VOCAB_FILES_MAP
      UpperCAmelCase__      :	Tuple    		=   PRETRAINED_POSITIONAL_EMBEDDINGS_SIZES
      UpperCAmelCase__      :	Any    		=   'left'
      def __init__(				self: str    ,       UpperCamelCase_: List[str]    ,       UpperCamelCase_: Tuple=False    ,       UpperCamelCase_: str=True    ,       UpperCamelCase_: Dict=False    ,       UpperCamelCase_: Any="<s>"    ,       UpperCamelCase_: Dict="</s>"    ,       UpperCamelCase_: Optional[Any]="<unk>"    ,       UpperCamelCase_: List[Any]="<sep>"    ,       UpperCamelCase_: Any="<pad>"    ,       UpperCamelCase_: str="<cls>"    ,       UpperCamelCase_: str="<mask>"    ,       UpperCamelCase_: Optional[int]=["<eop>", "<eod>"]    ,       UpperCamelCase_: Optional[Dict[str, Any]] = None    ,       **UpperCamelCase_: List[Any]    ,       ):
             # Mask token behave like a normal word, i.e. include the space before it
             __lowerCamelCase   =						AddedToken(UpperCamelCase_    ,       lstrip=UpperCamelCase_    ,       rstrip=UpperCamelCase_   ) if isinstance(UpperCamelCase_    ,       UpperCamelCase_   ) else mask_token

             __lowerCamelCase   =						{} 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   =						3

             __lowerCamelCase   =						do_lower_case
             __lowerCamelCase   =						remove_space
             __lowerCamelCase   =						keep_accents
             __lowerCamelCase   =						vocab_file

             __lowerCamelCase   =						spm.SentencePieceProcessor(**self.sp_model_kwargs   )
             self.sp_model.Load(UpperCamelCase_   )
      @property
      def 			lowerCAmelCase__						(				self: Union[str, Any]   ):
             return len(self.sp_model   )
      def 			lowerCAmelCase__						(				self: str   ):
             __lowerCamelCase   =						{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: Dict   ):
             __lowerCamelCase   =						self.__dict__.copy()
             __lowerCamelCase   =						None
             return state
      def __setstate__(				self: Optional[Any]    ,       UpperCamelCase_: int   ):
             __lowerCamelCase   =						d

             # for backward compatibility
             if not hasattr(self    ,       """sp_model_kwargs"""   ):
                    __lowerCamelCase   =						{}

             __lowerCamelCase   =						spm.SentencePieceProcessor(**self.sp_model_kwargs   )
             self.sp_model.Load(self.vocab_file   )
      def 			lowerCAmelCase__						(				self: List[Any]    ,       UpperCamelCase_: Optional[Any]   ):
             if self.remove_space:
                    __lowerCamelCase   =						""" """.join(inputs.strip().split()   )
             else:
                    __lowerCamelCase   =						inputs
             __lowerCamelCase   =						outputs.replace("""``"""    ,       """\""""   ).replace("""''"""    ,       """\""""   )

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

             return outputs
      def 			lowerCAmelCase__						(				self: Any    ,       UpperCamelCase_: str   ):
             __lowerCamelCase   =						self.preprocess_text(UpperCamelCase_   )
             __lowerCamelCase   =						self.sp_model.encode(UpperCamelCase_    ,       out_type=UpperCamelCase_   )
             __lowerCamelCase   =						[]
             for piece in pieces:
                    if len(UpperCamelCase_   ) > 1 and piece[-1] == str(""","""   ) and piece[-2].isdigit():
                           __lowerCamelCase   =						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   =						cur_pieces[1:]
                                  else:
                                         __lowerCamelCase   =						cur_pieces[0][1:]
                           cur_pieces.append(piece[-1]   )
                           new_pieces.extend(UpperCamelCase_   )
                    else:
                           new_pieces.append(UpperCamelCase_   )

             return new_pieces
      def 			lowerCAmelCase__						(				self: Optional[Any]    ,       UpperCamelCase_: Union[str, Any]   ):
             return self.sp_model.PieceToId(UpperCamelCase_   )
      def 			lowerCAmelCase__						(				self: List[Any]    ,       UpperCamelCase_: int   ):
             return self.sp_model.IdToPiece(UpperCamelCase_   )
      def 			lowerCAmelCase__						(				self: Dict    ,       UpperCamelCase_: Dict   ):
             __lowerCamelCase   =						"""""".join(UpperCamelCase_   ).replace(UpperCamelCase_    ,       """ """   ).strip()
             return out_string
      def 			lowerCAmelCase__						(				self: Optional[Any]    ,       UpperCamelCase_: List[int]    ,       UpperCamelCase_: bool = False    ,       UpperCamelCase_: bool = None    ,       UpperCamelCase_: bool = True    ,       **UpperCamelCase_: List[Any]    ,       ):
             __lowerCamelCase   =						kwargs.pop("""use_source_tokenizer"""    ,       UpperCamelCase_   )

             __lowerCamelCase   =						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   =						[]
             __lowerCamelCase   =						[]
             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   =						[]
                           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   =						"""""".join(UpperCamelCase_   )

             __lowerCamelCase   =						(
                 clean_up_tokenization_spaces
                 if clean_up_tokenization_spaces is not None
                 else self.clean_up_tokenization_spaces
             )
             if clean_up_tokenization_spaces:
                    __lowerCamelCase   =						self.clean_up_tokenization(UpperCamelCase_   )
                    return clean_text
             else:
                    return text
      def 			lowerCAmelCase__						(				self: Dict    ,       UpperCamelCase_: List[int]    ,       UpperCamelCase_: Optional[List[int]] = None   ):
             __lowerCamelCase   =						[self.sep_token_id]
             __lowerCamelCase   =						[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 			lowerCAmelCase__						(				self: List[Any]    ,       UpperCamelCase_: List[int]    ,       UpperCamelCase_: Optional[List[int]] = None    ,       UpperCamelCase_: bool = 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 			lowerCAmelCase__						(				self: List[str]    ,       UpperCamelCase_: List[int]    ,       UpperCamelCase_: Optional[List[int]] = None   ):
             __lowerCamelCase   =						[self.sep_token_id]
             __lowerCamelCase   =						[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 			lowerCAmelCase__						(				self: str    ,       UpperCamelCase_: str    ,       UpperCamelCase_: Optional[str] = None   ):
             if not os.path.isdir(UpperCamelCase_   ):
                    logger.error(F'Vocabulary path ({save_directory}) should be a directory'   )
                    return
             __lowerCamelCase   =						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   =						self.sp_model.serialized_model_proto()
                           fi.write(UpperCamelCase_   )

             return (out_vocab_file,)





import argparse
import json
import os
import time
import zipfile

from get_ci_error_statistics import download_artifact, get_artifacts_links

from transformers import logging


__lowerCAmelCase		       =							logging.get_logger(__name__)




def    snake_case_     (  snake_case			,							snake_case     )  ->				List[str]:
       lowercase__:   List[str]  			=   set()
       lowercase__:   List[Any]  			=   []

       def parse_line(snake_case     ):
              for line in fp:
                     if isinstance(snake_case			,							snake_case     ):
                            lowercase__:   Optional[Any]  			=   line.decode('UTF-8'     )
                     if "warnings summary (final)" in line:
                            continue
                     # This means we are outside the body of a warning
                     elif not line.startswith(' '     ):
                            # process a single warning and move it to `selected_warnings`.
                            if len(snake_case     ) > 0:
                                   lowercase__:   List[str]  			=   '\n'.join(snake_case     )
                                   # Only keep the warnings specified in `targets`
                                   if any(f': {x}: ' in warning for x in targets     ):
                                          selected_warnings.add(snake_case     )
                                   buffer.clear()
                            continue
                     else:
                            lowercase__:   Union[str, Any]  			=   line.strip()
                            buffer.append(snake_case     )

       if from_gh:
              for filename in os.listdir(snake_case     ):
                     lowercase__:   Dict  			=   os.path.join(snake_case			,							snake_case     )
                     if not os.path.isdir(snake_case     ):
                            # read the file
                            if filename != "warnings.txt":
                                   continue
                            with open(snake_case     ) as fp:
                                   parse_line(snake_case     )
       else:
              try:
                     with zipfile.ZipFile(snake_case     ) as z:
                            for filename in z.namelist():
                                   if not os.path.isdir(snake_case     ):
                                          # read the file
                                          if filename != "warnings.txt":
                                                 continue
                                          with z.open(snake_case     ) as fp:
                                                 parse_line(snake_case     )
              except Exception:
                     logger.warning(
                         f'{artifact_path} is either an invalid zip file or something else wrong. This file is skipped.'     )

       return selected_warnings




def    snake_case_     (  snake_case			,							snake_case     )  ->				Any:
       lowercase__:   Optional[Any]  			=   set()

       lowercase__:   int  			=   [os.path.join(snake_case			,							snake_case     ) for p in os.listdir(snake_case     ) if (p.endswith('.zip'     ) or from_gh)]
       for p in paths:
              selected_warnings.update(extract_warnings_from_single_artifact(snake_case			,							snake_case     )     )

       return selected_warnings


if __name__ == "__main__":




 def    snake_case_     (  snake_case     )  ->				str:
        return values.split(','     )

 __lowerCAmelCase		       =							argparse.ArgumentParser()
 # Required parameters
 parser.add_argument('''--workflow_run_id''', type=str, required=True, help='''A GitHub Actions workflow run id.''')
 parser.add_argument(
     '''--output_dir''',
     type=str,
     required=True,
     help='''Where to store the downloaded artifacts and other result files.''',
 )
 parser.add_argument('''--token''', default=None, type=str, help='''A token that has actions:read permission.''')
 # optional parameters
 parser.add_argument(
     '''--targets''',
     default='''DeprecationWarning,UserWarning,FutureWarning''',
     type=list_str,
     help='''Comma-separated list of target warning(s) which we want to extract.''',
 )
 parser.add_argument(
     '''--from_gh''',
     action='''store_true''',
     help='''If running from a GitHub action workflow and collecting warnings from its artifacts.''',
 )

 __lowerCAmelCase		       =							parser.parse_args()

 __lowerCAmelCase		       =							args.from_gh
 if from_gh:
  # The artifacts have to be downloaded using `actions/download-artifact@v3`
  pass
 else:
  os.makedirs(args.output_dir, exist_ok=True)

  # get download links
  __lowerCAmelCase		       =							get_artifacts_links(args.workflow_run_id, token=args.token)
  with open(os.path.join(args.output_dir, '''artifacts.json'''), '''w''', encoding='''UTF-8''') as fp:
   json.dump(artifacts, fp, ensure_ascii=False, indent=4)

  # download artifacts
  for idx, (name, url) in enumerate(artifacts.items()):
   print(name)
   print(url)
   print('''=''' * 80)
   download_artifact(name, url, args.output_dir, args.token)
   # Be gentle to GitHub
   time.sleep(1)

    # extract warnings from artifacts
 __lowerCAmelCase		       =							extract_warnings(args.output_dir, args.targets)
 __lowerCAmelCase		       =							sorted(selected_warnings)
 with open(os.path.join(args.output_dir, '''selected_warnings.json'''), '''w''', encoding='''UTF-8''') as fp:
  json.dump(selected_warnings, fp, ensure_ascii=False, indent=4)


