


'''simple docstring'''







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


SCREAMING_SNAKE_CASE_      =			logging.get_logger(__name__)




def        __lowercase						(      __SCREAMING_SNAKE_CASE				,  __SCREAMING_SNAKE_CASE		)				->					Optional[Any]:
     """simple docstring"""




     __a       =   set()
     __a       =   []

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

     if from_gh:
          for filename in os.listdir(__SCREAMING_SNAKE_CASE		):
               __a       =   os.path.join(__SCREAMING_SNAKE_CASE				,  __SCREAMING_SNAKE_CASE		)
               if not os.path.isdir(__SCREAMING_SNAKE_CASE		):
                    # read the file
                    if filename != "warnings.txt":
                         continue
                    with open(__SCREAMING_SNAKE_CASE		) as fp:
                         parse_line(__SCREAMING_SNAKE_CASE		)
     else:
          try:
               with zipfile.ZipFile(__SCREAMING_SNAKE_CASE		) as z:
                    for filename in z.namelist():
                         if not os.path.isdir(__SCREAMING_SNAKE_CASE		):
                              # read the file
                              if filename != "warnings.txt":
                                   continue
                              with z.open(__SCREAMING_SNAKE_CASE		) as fp:
                                   parse_line(__SCREAMING_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        __lowercase						(      __SCREAMING_SNAKE_CASE				,  __SCREAMING_SNAKE_CASE		)				->					Any:
     """simple docstring"""




     __a       =   set()

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

     return selected_warnings


if __name__ == "__main__":




 def        __lowercase						(      __SCREAMING_SNAKE_CASE		)				->					Dict:
      """simple docstring"""




      return values.split(""","""		)

 SCREAMING_SNAKE_CASE_      =			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.',
 )

 SCREAMING_SNAKE_CASE_      =			parser.parse_args()

 SCREAMING_SNAKE_CASE_      =			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
  SCREAMING_SNAKE_CASE_      =			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
 SCREAMING_SNAKE_CASE_      =			extract_warnings(args.output_dir, args.targets)
 SCREAMING_SNAKE_CASE_      =			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 typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available


SCREAMING_SNAKE_CASE_      =			{
    'configuration_rag': ['RagConfig'],
    'retrieval_rag': ['RagRetriever'],
    'tokenization_rag': ['RagTokenizer'],
}

try:
 if not is_torch_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE_      =			[
     'RagModel',
     'RagPreTrainedModel',
     'RagSequenceForGeneration',
     'RagTokenForGeneration',
 ]

try:
 if not is_tf_available():
  raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
 pass
else:
 SCREAMING_SNAKE_CASE_      =			[
     'TFRagModel',
     'TFRagPreTrainedModel',
     'TFRagSequenceForGeneration',
     'TFRagTokenForGeneration',
 ]


if TYPE_CHECKING:
 from .configuration_rag import RagConfig
 from .retrieval_rag import RagRetriever
 from .tokenization_rag import RagTokenizer

 try:
  if not is_torch_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_rag import RagModel, RagPreTrainedModel, RagSequenceForGeneration, RagTokenForGeneration

 try:
  if not is_tf_available():
   raise OptionalDependencyNotAvailable()
 except OptionalDependencyNotAvailable:
  pass
 else:
  from .modeling_tf_rag import (
      TFRagModel,
      TFRagPreTrainedModel,
      TFRagSequenceForGeneration,
      TFRagTokenForGeneration,
  )

else:
 import sys

 SCREAMING_SNAKE_CASE_      =			_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)






