





import argparse
from collections import defaultdict





def 	lowerCAmelCase_					(			__a      ,       __a      ,       __a      ,       __a      ,       __a						)	->						Union[str, Any]:







  """simple docstring"""





  lowerCamelCase__: Union[str, Any]         =F"""{file}_{class_name}_{test_name}"""
  done_test[_id] += 1

  with open(lowerCAmelCase__      ,       "r"						) as f:
    lowerCamelCase__: List[str]         =f.readlines()

  lowerCamelCase__: List[str]         =F"""class {class_name}("""
  lowerCamelCase__: Any         =F"""{4 * " "}def {test_name}("""
  lowerCamelCase__: Optional[Any]         =F"""{8 * " "}{correct_line.split()[0]}"""
  lowerCamelCase__: Dict         =F"""{16 * " "}{correct_line.split()[0]}"""
  lowerCamelCase__: Optional[Any]         =False
  lowerCamelCase__: Dict         =False
  lowerCamelCase__: List[str]         =False
  lowerCamelCase__: Dict         =False
  lowerCamelCase__: str         =0
  lowerCamelCase__: Optional[int]         =0

  lowerCamelCase__: List[str]         =[]
  for line in lines:
    if line.startswith(lowerCAmelCase__						):
      lowerCamelCase__: Any         =True
    elif in_class and line.startswith(lowerCAmelCase__						):
      lowerCamelCase__: Optional[Any]         =True
    elif in_class and in_func and (line.startswith(lowerCAmelCase__						) or line.startswith(lowerCAmelCase__						)):
      lowerCamelCase__: Dict         =len(line.split(correct_line.split()[0]						)[0]						)
      count += 1

      if count == done_test[_id]:
        lowerCamelCase__: int         =True

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

    if in_class and in_func and in_line and insert_line:
      new_lines.append(F"""{spaces * " "}{correct_line}"""						)
      lowerCamelCase__: Any         =False
    else:
      new_lines.append(lowerCAmelCase__						)

  with open(lowerCAmelCase__      ,       "w"						) as f:
    for line in new_lines:
      f.write(lowerCAmelCase__						)





def 	lowerCAmelCase_					(			__a      ,       __a=None						)	->						Union[str, Any]:







  """simple docstring"""





  if fail is not None:
    with open(lowerCAmelCase__      ,       "r"						) as f:
      lowerCamelCase__: Optional[Any]         ={l.strip() for l in f.readlines()}
  else:
    lowerCamelCase__: Union[str, Any]         =None

  with open(lowerCAmelCase__      ,       "r"						) as f:
    lowerCamelCase__: int         =f.readlines()

  lowerCamelCase__: List[str]         =defaultdict(lowerCAmelCase__						)
  for line in correct_lines:
    lowerCamelCase__    ,   lowerCamelCase__    ,   lowerCamelCase__    ,   lowerCamelCase__: Tuple         =line.split(";"						)
    if test_failures is None or "::".join([file, class_name, test_name]						) in test_failures:
      overwrite_file(lowerCAmelCase__      ,       lowerCAmelCase__      ,       lowerCAmelCase__      ,       lowerCAmelCase__      ,       lowerCAmelCase__						)


if __name__ == "__main__":
     __A							   =							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)
     __A							   =							parser.parse_args()

     main(args.correct_filename, args.fail_filename)






from typing import List

import numpy as np






def  lowerCamelCase_	(      lowerCAmelCase__	:	dict				)       ->							int:

							'''simple docstring'''






							A      						=    {key: len(lowerCAmelCase__				) for key, value in gen_kwargs.items() if isinstance(lowerCAmelCase__			,	lowerCAmelCase__				)}
							if len(set(lists_lengths.values()				)				) > 1:
														raise RuntimeError(
														    (
														        'Sharding is ambiguous for this dataset: '
														        + 'we found several data sources lists of different lengths, and we don\'t know over which list we should parallelize:\n'
														        + '\n'.join(F'''\t- key {key} has length {length}''' for key, length in lists_lengths.items()				)
														        + '\nTo fix this, check the \'gen_kwargs\' and make sure to use lists only for data sources, '
														        + 'and use tuples otherwise. In the end there should only be one single list, or several lists with the same length.'
														    )				)
							A      						=    max(lists_lengths.values()			,	default=0				)
							return max(1			,	lowerCAmelCase__				)






def  lowerCamelCase_	(      lowerCAmelCase__	:	int			,	lowerCAmelCase__	:	int				)       ->							List[range]:

							'''simple docstring'''






							A      						=    []
							for group_idx in range(lowerCAmelCase__				):
														A      						=    num_shards // max_num_jobs + (group_idx < (num_shards % max_num_jobs))
														if num_shards_to_add == 0:
																					break
														A      						=    shards_indices_per_group[-1].stop if shards_indices_per_group else 0
														A      						=    range(lowerCAmelCase__			,	start + num_shards_to_add				)
														shards_indices_per_group.append(lowerCAmelCase__				)
							return shards_indices_per_group






def  lowerCamelCase_	(      lowerCAmelCase__	:	dict			,	lowerCAmelCase__	:	int				)       ->							List[dict]:

							'''simple docstring'''






							A      						=    _number_of_shards_in_gen_kwargs(lowerCAmelCase__				)
							if num_shards == 1:
														return [dict(lowerCAmelCase__				)]
							else:
														A      						=    _distribute_shards(num_shards=lowerCAmelCase__			,	max_num_jobs=lowerCAmelCase__				)
														return [
														    {
														        key: [value[shard_idx] for shard_idx in shard_indices_per_group[group_idx]]
														        if isinstance(lowerCAmelCase__			,	lowerCAmelCase__				)
														        else value
														        for key, value in gen_kwargs.items()
														    }
														    for group_idx in range(len(lowerCAmelCase__				)				)
														]






def  lowerCamelCase_	(      lowerCAmelCase__	:	List[dict]				)       ->							dict:

							'''simple docstring'''






							return {
							    key: [value for gen_kwargs in gen_kwargs_list for value in gen_kwargs[key]]
							    if isinstance(gen_kwargs_list[0][key]			,	lowerCAmelCase__				)
							    else gen_kwargs_list[0][key]
							    for key in gen_kwargs_list[0]
							}






def  lowerCamelCase_	(      lowerCAmelCase__	:	np.random.Generator			,	lowerCAmelCase__	:	dict				)       ->							dict:

							'''simple docstring'''






							A      						=    {len(lowerCAmelCase__				) for value in gen_kwargs.values() if isinstance(lowerCAmelCase__			,	lowerCAmelCase__				)}
							A      						=    {}
							for size in list_sizes:
														A      						=    list(range(lowerCAmelCase__				)				)
														rng.shuffle(indices_per_size[size]				)
							# Now let's copy the gen_kwargs and shuffle the lists based on their sizes
							A      						=    dict(lowerCAmelCase__				)
							for key, value in shuffled_kwargs.items():
														if isinstance(lowerCAmelCase__			,	lowerCAmelCase__				):
																					A      						=    [value[i] for i in indices_per_size[len(lowerCAmelCase__				)]]
							return shuffled_kwargs