


import shutil
import tempfile
import unittest

import numpy as np
import pytest

from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available


if is_vision_available():
   from PIL import Image

   from transformers import AutoProcessor, BlipaProcessor, BlipImageProcessor, GPTaTokenizer, PreTrainedTokenizerFast







@require_vision
class lowerCAmelCase_		(				unittest.TestCase ):

 '''simple docstring'''

 def 		UpperCamelCase__  (			self      ):
       snake_case_ =   tempfile.mkdtemp()

       snake_case_ =   BlipImageProcessor()
       snake_case_ =   GPTaTokenizer.from_pretrained('''hf-internal-testing/tiny-random-GPT2Model'''      )

       snake_case_ =   BlipaProcessor(_UpperCAmelCase	,   _UpperCAmelCase      )

       processor.save_pretrained(self.tmpdirname      )



 def 		UpperCamelCase__  (			self	,   **_UpperCAmelCase      ):
       return AutoProcessor.from_pretrained(self.tmpdirname	,   **_UpperCAmelCase      ).tokenizer



 def 		UpperCamelCase__  (			self	,   **_UpperCAmelCase      ):
       return AutoProcessor.from_pretrained(self.tmpdirname	,   **_UpperCAmelCase      ).image_processor



 def 		UpperCamelCase__  (			self      ):
       shutil.rmtree(self.tmpdirname      )



 def 		UpperCamelCase__  (			self      ):
       snake_case_ =   [np.random.randint(2_55	,   size=(3, 30, 4_00)	,   dtype=np.uinta      )]

       snake_case_ =   [Image.fromarray(np.moveaxis(_UpperCAmelCase	,   0	,   -1      )      ) for x in image_inputs]

       return image_inputs



 def 		UpperCamelCase__  (			self      ):
       snake_case_ =   BlipaProcessor(tokenizer=self.get_tokenizer()	,   image_processor=self.get_image_processor()      )
       processor.save_pretrained(self.tmpdirname      )

       snake_case_ =   self.get_tokenizer(bos_token='''(BOS)'''	,   eos_token='''(EOS)'''      )
       snake_case_ =   self.get_image_processor(do_normalize=_UpperCAmelCase	,   padding_value=1.0      )

       snake_case_ =   BlipaProcessor.from_pretrained(
           self.tmpdirname	,   bos_token='''(BOS)'''	,   eos_token='''(EOS)'''	,   do_normalize=_UpperCAmelCase	,   padding_value=1.0      )

       self.assertEqual(processor.tokenizer.get_vocab()	,   tokenizer_add_kwargs.get_vocab()      )
       self.assertIsInstance(processor.tokenizer	,   _UpperCAmelCase      )

       self.assertEqual(processor.image_processor.to_json_string()	,   image_processor_add_kwargs.to_json_string()      )
       self.assertIsInstance(processor.image_processor	,   _UpperCAmelCase      )



 def 		UpperCamelCase__  (			self      ):
       snake_case_ =   self.get_image_processor()
       snake_case_ =   self.get_tokenizer()

       snake_case_ =   BlipaProcessor(tokenizer=_UpperCAmelCase	,   image_processor=_UpperCAmelCase      )

       snake_case_ =   self.prepare_image_inputs()

       snake_case_ =   image_processor(_UpperCAmelCase	,   return_tensors='''np'''      )
       snake_case_ =   processor(images=_UpperCAmelCase	,   return_tensors='''np'''      )

       for key in input_feat_extract.keys():
             self.assertAlmostEqual(input_feat_extract[key].sum()	,   input_processor[key].sum()	,   delta=1E-2      )



 def 		UpperCamelCase__  (			self      ):
       snake_case_ =   self.get_image_processor()
       snake_case_ =   self.get_tokenizer()

       snake_case_ =   BlipaProcessor(tokenizer=_UpperCAmelCase	,   image_processor=_UpperCAmelCase      )

       snake_case_ =   '''lower newer'''

       snake_case_ =   processor(text=_UpperCAmelCase      )

       snake_case_ =   tokenizer(_UpperCAmelCase	,   return_token_type_ids=_UpperCAmelCase      )

       for key in encoded_tok.keys():
             self.assertListEqual(encoded_tok[key]	,   encoded_processor[key]      )



 def 		UpperCamelCase__  (			self      ):
       snake_case_ =   self.get_image_processor()
       snake_case_ =   self.get_tokenizer()

       snake_case_ =   BlipaProcessor(tokenizer=_UpperCAmelCase	,   image_processor=_UpperCAmelCase      )

       snake_case_ =   '''lower newer'''
       snake_case_ =   self.prepare_image_inputs()

       snake_case_ =   processor(text=_UpperCAmelCase	,   images=_UpperCAmelCase      )

       self.assertListEqual(list(inputs.keys()      )	,   ['''pixel_values''', '''input_ids''', '''attention_mask''']      )

       # test if it raises when no input is passed
       with pytest.raises(_UpperCAmelCase      ):
             processor()



 def 		UpperCamelCase__  (			self      ):
       snake_case_ =   self.get_image_processor()
       snake_case_ =   self.get_tokenizer()

       snake_case_ =   BlipaProcessor(tokenizer=_UpperCAmelCase	,   image_processor=_UpperCAmelCase      )

       snake_case_ =   [[1, 4, 5, 8, 1, 0, 8], [3, 4, 3, 1, 1, 8, 9]]

       snake_case_ =   processor.batch_decode(_UpperCAmelCase      )
       snake_case_ =   tokenizer.batch_decode(_UpperCAmelCase      )

       self.assertListEqual(_UpperCAmelCase	,   _UpperCAmelCase      )





 def 		UpperCamelCase__  (			self      ):
       snake_case_ =   self.get_image_processor()
       snake_case_ =   self.get_tokenizer()

       snake_case_ =   BlipaProcessor(tokenizer=_UpperCAmelCase	,   image_processor=_UpperCAmelCase      )

       snake_case_ =   '''lower newer'''
       snake_case_ =   self.prepare_image_inputs()

       snake_case_ =   processor(text=_UpperCAmelCase	,   images=_UpperCAmelCase      )

       # For now the processor supports only ['pixel_values', 'input_ids', 'attention_mask']
       self.assertListEqual(list(inputs.keys()      )	,   ['''pixel_values''', '''input_ids''', '''attention_mask''']      )



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


UpperCAmelCase    =					logging.get_logger(__name__)






def  __lowerCAmelCase					(SCREAMING_SNAKE_CASE      ,      SCREAMING_SNAKE_CASE      )->						List[str]:




      """simple docstring"""

      snake_case_ =   set()
      snake_case_ =   []

      def parse_line(SCREAMING_SNAKE_CASE      ):
            for line in fp:
                  if isinstance(SCREAMING_SNAKE_CASE      ,      SCREAMING_SNAKE_CASE      ):
                        snake_case_ =   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:
                              snake_case_ =   '''\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:
                        snake_case_ =   line.strip()
                        buffer.append(SCREAMING_SNAKE_CASE      )

      if from_gh:
            for filename in os.listdir(SCREAMING_SNAKE_CASE      ):
                  snake_case_ =   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  __lowerCAmelCase					(SCREAMING_SNAKE_CASE      ,      SCREAMING_SNAKE_CASE      )->						str:




      """simple docstring"""

      snake_case_ =   set()

      snake_case_ =   [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  __lowerCAmelCase					(SCREAMING_SNAKE_CASE      )->						List[str]:




         """simple docstring"""

         return values.split(''','''      )

   UpperCAmelCase    =					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.""",
   )

   UpperCAmelCase    =					parser.parse_args()

   UpperCAmelCase    =					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
      UpperCAmelCase    =					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
   UpperCAmelCase    =					extract_warnings(args.output_dir, args.targets)
   UpperCAmelCase    =					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)