




import argparse
from collections import defaultdict

def 			_SCREAMING_SNAKE_CASE			(							lowercase	:       Union[str, Any]	,							lowercase	:       int	,							lowercase	:       List[str]	,							lowercase	:       int	,							lowercase	:       Any     ):


      '''simple docstring'''



      lowerCamelCase_		     =    f"""{file}_{class_name}_{test_name}"""
      done_test[_id] += 1

      with open(lowercase	,							'r'     ) as f:
            lowerCamelCase_		     =    f.readlines()

      lowerCamelCase_		     =    f"""class {class_name}("""
      lowerCamelCase_		     =    f"""{4 * " "}def {test_name}("""
      lowerCamelCase_		     =    f"""{8 * " "}{correct_line.split()[0]}"""
      lowerCamelCase_		     =    f"""{16 * " "}{correct_line.split()[0]}"""
      lowerCamelCase_		     =    False
      lowerCamelCase_		     =    False
      lowerCamelCase_		     =    False
      lowerCamelCase_		     =    False
      lowerCamelCase_		     =    0
      lowerCamelCase_		     =    0

      lowerCamelCase_		     =    []
      for line in lines:
            if line.startswith(lowercase     ):
                  lowerCamelCase_		     =    True
            elif in_class and line.startswith(lowercase     ):
                  lowerCamelCase_		     =    True
            elif in_class and in_func and (line.startswith(lowercase     ) or line.startswith(lowercase     )):
                  lowerCamelCase_		     =    len(line.split(correct_line.split()[0]     )[0]     )
                  count += 1

                  if count == done_test[_id]:
                        lowerCamelCase_		     =    True

            if in_class and in_func and in_line:
                  if ")" not in line:
                        continue
                  else:
                        lowerCamelCase_		     =    True

            if in_class and in_func and in_line and insert_line:
                  new_lines.append(f"""{spaces * " "}{correct_line}"""     )
                  lowerCamelCase_		     =    lowerCamelCase_		     =    lowerCamelCase_		     =    lowerCamelCase_		     =    False
            else:
                  new_lines.append(lowercase     )

      with open(lowercase	,							'w'     ) as f:
            for line in new_lines:
                  f.write(lowercase     )

def 			_SCREAMING_SNAKE_CASE			(							lowercase	:       Union[str, Any]	,							lowercase	:       str=None     ):


      '''simple docstring'''



      if fail is not None:
            with open(lowercase	,							'r'     ) as f:
                  lowerCamelCase_		     =    {l.strip() for l in f.readlines()}
      else:
            lowerCamelCase_		     =    None

      with open(lowercase	,							'r'     ) as f:
            lowerCamelCase_		     =    f.readlines()

      lowerCamelCase_		     =    defaultdict(lowercase     )
      for line in correct_lines:
            lowerCamelCase_     ,				lowerCamelCase_     ,				lowerCamelCase_     ,				lowerCamelCase_		     =    line.split(';'     )
            if test_failures is None or "::".join([file, class_name, test_name]     ) in test_failures:
                  overwrite_file(lowercase	,							lowercase	,							lowercase	,							lowercase	,							lowercase     )


if __name__ == "__main__":
 lowerCamelCase				:		int     =   argparse.ArgumentParser()
 parser.add_argument("--correct_filename", help="filename of tests with expected result")
 parser.add_argument("--fail_filename", help="filename of test failures", type=str, default=None)
 lowerCamelCase				:		List[str]     =   parser.parse_args()

 main(args.correct_filename, args.fail_filename)









import warnings

from ...utils import logging
from .image_processing_donut import DonutImageProcessor


lowerCamelCase				:		Any     =   logging.get_logger(__name__)







class   A(						UpperCamelCase   ):



 '''simple docstring'''


 def __init__(				self					:  Dict						,							*A_					:  Optional[int]						,							**A_					:  int  )   ->	None:

       """simple docstring"""






       warnings.warn(
           'The class DonutFeatureExtractor is deprecated and will be removed in version 5 of Transformers. Please'
           ' use DonutImageProcessor instead.'						,							A_						,							)
       super().__init__(*A_						,							**A_  )



