




'''simple docstring'''

import json
import os
import shutil
import tempfile
from unittest import TestCase

from transformers import BartTokenizer, BartTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES as DPR_VOCAB_FILES_NAMES
from transformers.models.dpr.configuration_dpr import DPRConfig
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES as BART_VOCAB_FILES_NAMES
from transformers.testing_utils import require_faiss, require_tokenizers, require_torch, slow
from transformers.utils import is_datasets_available, is_faiss_available, is_torch_available


if is_torch_available() and is_datasets_available() and is_faiss_available():
							from transformers.models.rag.configuration_rag import RagConfig
							from transformers.models.rag.tokenization_rag import RagTokenizer






@require_faiss
@require_torch
class 						a				(   _lowerCamelCase     ):


				def   A_ (		self    :					Union[str, Any]					):
									snake_case_									=				tempfile.mkdtemp()
									snake_case_									=				8

									# DPR tok
									snake_case_									=				[
									    '''[UNK]''',
									    '''[CLS]''',
									    '''[SEP]''',
									    '''[PAD]''',
									    '''[MASK]''',
									    '''want''',
									    '''##want''',
									    '''##ed''',
									    '''wa''',
									    '''un''',
									    '''runn''',
									    '''##ing''',
									    ''',''',
									    '''low''',
									    '''lowest''',
									]
									snake_case_									=				os.path.join(self.tmpdirname       ,				'''dpr_tokenizer'''					)
									os.makedirs(lowercase_       ,				exist_ok=lowercase_					)
									snake_case_									=				os.path.join(lowercase_       ,				DPR_VOCAB_FILES_NAMES['''vocab_file''']					)
									with open(self.vocab_file       ,				'''w'''       ,				encoding='''utf-8'''					) as vocab_writer:
														vocab_writer.write(''''''.join([x + '''\n''' for x in vocab_tokens]					)					)

									# BART tok
									snake_case_									=				[
									    '''l''',
									    '''o''',
									    '''w''',
									    '''e''',
									    '''r''',
									    '''s''',
									    '''t''',
									    '''i''',
									    '''d''',
									    '''n''',
									    '''\u0120''',
									    '''\u0120l''',
									    '''\u0120n''',
									    '''\u0120lo''',
									    '''\u0120low''',
									    '''er''',
									    '''\u0120lowest''',
									    '''\u0120newer''',
									    '''\u0120wider''',
									    '''<unk>''',
									]
									snake_case_									=				dict(zip(lowercase_       ,				range(len(lowercase_					)					)					)					)
									snake_case_									=				['''#version: 0.2''', '''\u0120 l''', '''\u0120l o''', '''\u0120lo w''', '''e r''', '''''']
									snake_case_									=				{'''unk_token''': '''<unk>'''}

									snake_case_									=				os.path.join(self.tmpdirname       ,				'''bart_tokenizer'''					)
									os.makedirs(lowercase_       ,				exist_ok=lowercase_					)
									snake_case_									=				os.path.join(lowercase_       ,				BART_VOCAB_FILES_NAMES['''vocab_file''']					)
									snake_case_									=				os.path.join(lowercase_       ,				BART_VOCAB_FILES_NAMES['''merges_file''']					)
									with open(self.vocab_file       ,				'''w'''       ,				encoding='''utf-8'''					) as fp:
														fp.write(json.dumps(lowercase_					) + '''\n'''					)
									with open(self.merges_file       ,				'''w'''       ,				encoding='''utf-8'''					) as fp:
														fp.write('''\n'''.join(lowercase_					)					)


				def   A_ (		self    :					Any					):
									return DPRQuestionEncoderTokenizer.from_pretrained(os.path.join(self.tmpdirname       ,				'''dpr_tokenizer'''					)					)


				def   A_ (		self    :					Dict					):
									return BartTokenizer.from_pretrained(os.path.join(self.tmpdirname       ,				'''bart_tokenizer'''					)					)


				def   A_ (		self    :					Optional[Any]					):
									shutil.rmtree(self.tmpdirname					)


				@require_tokenizers
				def   A_ (		self    :					Union[str, Any]					):
									snake_case_									=				os.path.join(self.tmpdirname       ,				'''rag_tokenizer'''					)
									snake_case_									=				RagConfig(question_encoder=DPRConfig().to_dict()       ,				generator=BartConfig().to_dict()					)
									snake_case_									=				RagTokenizer(question_encoder=self.get_dpr_tokenizer()       ,				generator=self.get_bart_tokenizer()					)
									rag_config.save_pretrained(lowercase_					)
									rag_tokenizer.save_pretrained(lowercase_					)
									snake_case_									=				RagTokenizer.from_pretrained(lowercase_       ,				config=lowercase_					)
									self.assertIsInstance(new_rag_tokenizer.question_encoder       ,				lowercase_					)
									self.assertEqual(new_rag_tokenizer.question_encoder.get_vocab()       ,				rag_tokenizer.question_encoder.get_vocab()					)
									self.assertIsInstance(new_rag_tokenizer.generator       ,				lowercase_					)
									self.assertEqual(new_rag_tokenizer.generator.get_vocab()       ,				rag_tokenizer.generator.get_vocab()					)


				@slow
				def   A_ (		self    :					List[Any]					):
									snake_case_									=				RagTokenizer.from_pretrained('''facebook/rag-token-nq'''					)
									snake_case_									=				[
									    '''who got the first nobel prize in physics''',
									    '''when is the next deadpool movie being released''',
									    '''which mode is used for short wave broadcast service''',
									    '''who is the owner of reading football club''',
									    '''when is the next scandal episode coming out''',
									    '''when is the last time the philadelphia won the superbowl''',
									    '''what is the most current adobe flash player version''',
									    '''how many episodes are there in dragon ball z''',
									    '''what is the first step in the evolution of the eye''',
									    '''where is gall bladder situated in human body''',
									    '''what is the main mineral in lithium batteries''',
									    '''who is the president of usa right now''',
									    '''where do the greasers live in the outsiders''',
									    '''panda is a national animal of which country''',
									    '''what is the name of manchester united stadium''',
									]
									snake_case_									=				tokenizer(lowercase_					)
									self.assertIsNotNone(lowercase_					)


				@slow
				def   A_ (		self    :					Dict					):
									snake_case_									=				RagTokenizer.from_pretrained('''facebook/rag-sequence-nq'''					)
									snake_case_									=				[
									    '''who got the first nobel prize in physics''',
									    '''when is the next deadpool movie being released''',
									    '''which mode is used for short wave broadcast service''',
									    '''who is the owner of reading football club''',
									    '''when is the next scandal episode coming out''',
									    '''when is the last time the philadelphia won the superbowl''',
									    '''what is the most current adobe flash player version''',
									    '''how many episodes are there in dragon ball z''',
									    '''what is the first step in the evolution of the eye''',
									    '''where is gall bladder situated in human body''',
									    '''what is the main mineral in lithium batteries''',
									    '''who is the president of usa right now''',
									    '''where do the greasers live in the outsiders''',
									    '''panda is a national animal of which country''',
									    '''what is the name of manchester united stadium''',
									]
									snake_case_									=				tokenizer(lowercase_					)
									self.assertIsNotNone(lowercase_					)





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)


