





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


_snake_case    :       int		       =    logging.get_logger(__name__)

def     a_       (					lowerCAmelCase_ :     Optional[Any],      lowerCAmelCase_ :     Any      ):
   __lowerCAmelCase				      =      set()
   __lowerCAmelCase				      =      []

   def parse_line(lowerCAmelCase_ :     str      ):
      for line in fp:
         if isinstance(lowerCAmelCase_,      lowerCAmelCase_      ):
            __lowerCAmelCase				      =      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(lowerCAmelCase_      ) > 0:
               __lowerCAmelCase				      =      '\n'.join(lowerCAmelCase_      )
               # Only keep the warnings specified in `targets`
               if any(F""": {x}: """ in warning for x in targets      ):
                  selected_warnings.add(lowerCAmelCase_      )
               buffer.clear()
            continue
         else:
            __lowerCAmelCase				      =      line.strip()
            buffer.append(lowerCAmelCase_      )

   if from_gh:
      for filename in os.listdir(lowerCAmelCase_      ):
         __lowerCAmelCase				      =      os.path.join(lowerCAmelCase_,      lowerCAmelCase_      )
         if not os.path.isdir(lowerCAmelCase_      ):
            # read the file
            if filename != "warnings.txt":
               continue
            with open(lowerCAmelCase_      ) as fp:
               parse_line(lowerCAmelCase_      )
   else:
      try:
         with zipfile.ZipFile(lowerCAmelCase_      ) as z:
            for filename in z.namelist():
               if not os.path.isdir(lowerCAmelCase_      ):
                  # read the file
                  if filename != "warnings.txt":
                     continue
                  with z.open(lowerCAmelCase_      ) as fp:
                     parse_line(lowerCAmelCase_      )
      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     a_       (					lowerCAmelCase_ :     Dict,      lowerCAmelCase_ :     int      ):
   __lowerCAmelCase				      =      set()

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

   return selected_warnings


if __name__ == "__main__":

     def     a_       (					lowerCAmelCase_ :     str      ):
        return values.split(','      )

     _snake_case    :       int		       =    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.',
     )

     _snake_case    :       List[Any]		       =    parser.parse_args()

     _snake_case    :       List[Any]		       =    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
          _snake_case    :       List[str]		       =    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
     _snake_case    :       List[str]		       =    extract_warnings(args.output_dir, args.targets)
     _snake_case    :       int		       =    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)





'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging


UpperCAmelCase_			:  Optional[int]										=   logging.get_logger(__name__)

UpperCAmelCase_			:  List[str]										=   {
    'google/fnet-base': 'https://huggingface.co/google/fnet-base/resolve/main/config.json',
    'google/fnet-large': 'https://huggingface.co/google/fnet-large/resolve/main/config.json'
    # See all FNet models at https://huggingface.co/models?filter=fnet
}

class     _lowerCamelCase       (     snake_case_					):




 '''simple docstring'''
 __lowercase					:		List[Any]     				=    '''fnet'''


 def __init__(   self   ,   __lowercase=32_000   ,   __lowercase=768   ,   __lowercase=12   ,   __lowercase=3_072   ,   __lowercase="gelu_new"   ,   __lowercase=0.1   ,   __lowercase=512   ,   __lowercase=4   ,   __lowercase=0.0_2   ,   __lowercase=1E-12   ,   __lowercase=False   ,   __lowercase=512   ,   __lowercase=3   ,   __lowercase=1   ,   __lowercase=2   ,   **__lowercase   ,   ):

  """simple docstring"""







  super().__init__(pad_token_id=__lowercase   ,   bos_token_id=__lowercase   ,   eos_token_id=__lowercase   ,   **__lowercase    )

  __A	:		Union[str, Any]	  =      vocab_size
  __A	:		Dict	  =      max_position_embeddings
  __A	:		List[str]	  =      hidden_size
  __A	:		Tuple	  =      num_hidden_layers
  __A	:		Optional[int]	  =      intermediate_size
  __A	:		Dict	  =      hidden_act
  __A	:		List[str]	  =      hidden_dropout_prob
  __A	:		str	  =      initializer_range
  __A	:		Dict	  =      type_vocab_size
  __A	:		int	  =      layer_norm_eps
  __A	:		Tuple	  =      use_tpu_fourier_optimizations
  __A	:		Optional[Any]	  =      tpu_short_seq_length






