





__A							   =							256
# Modulus to hash a string
__A							   =							100_0003





def 	lowerCAmelCase_					(			__a      ,       __a						)	->						bool:







  """simple docstring"""





  lowerCamelCase__: str         =len(lowerCAmelCase__						)
  lowerCamelCase__: List[Any]         =len(lowerCAmelCase__						)
  if p_len > t_len:
    return False

  lowerCamelCase__: Tuple         =0
  lowerCamelCase__: Optional[Any]         =0
  lowerCamelCase__: Union[str, Any]         =1

  # Calculating the hash of pattern and substring of text
  for i in range(lowerCAmelCase__						):
    lowerCamelCase__: Optional[int]         =(ord(pattern[i]						) + p_hash * alphabet_size) % modulus
    lowerCamelCase__: Optional[Any]         =(ord(text[i]						) + text_hash * alphabet_size) % modulus
    if i == p_len - 1:
      continue
    lowerCamelCase__: List[str]         =(modulus_power * alphabet_size) % modulus

  for i in range(0      ,       t_len - p_len + 1						):
    if text_hash == p_hash and text[i : i + p_len] == pattern:
      return True
    if i == t_len - p_len:
      continue
    # Calculate the https://en.wikipedia.org/wiki/Rolling_hash
    lowerCamelCase__: Tuple         =(
        (text_hash - ord(text[i]						) * modulus_power) * alphabet_size
        + ord(text[i + p_len]						)
    ) % modulus
  return False





def 	lowerCAmelCase_					(			)	->						None:







  """simple docstring"""





  lowerCamelCase__: Tuple         ="abc1abc12"
  lowerCamelCase__: List[str]         ="alskfjaldsabc1abc1abc12k23adsfabcabc"
  lowerCamelCase__: Dict         ="alskfjaldsk23adsfabcabc"
  assert rabin_karp(lowerCAmelCase__      ,       lowerCAmelCase__						) and not rabin_karp(lowerCAmelCase__      ,       lowerCAmelCase__						)

  # Test 2)
  lowerCamelCase__: Tuple         ="ABABX"
  lowerCamelCase__: Optional[Any]         ="ABABZABABYABABX"
  assert rabin_karp(lowerCAmelCase__      ,       lowerCAmelCase__						)

  # Test 3)
  lowerCamelCase__: List[str]         ="AAAB"
  lowerCamelCase__: str         ="ABAAAAAB"
  assert rabin_karp(lowerCAmelCase__      ,       lowerCAmelCase__						)

  # Test 4)
  lowerCamelCase__: List[str]         ="abcdabcy"
  lowerCamelCase__: Optional[Any]         ="abcxabcdabxabcdabcdabcy"
  assert rabin_karp(lowerCAmelCase__      ,       lowerCAmelCase__						)

  # Test 5)
  lowerCamelCase__: Optional[int]         ="Lü"
  lowerCamelCase__: Optional[Any]         ="Lüsai"
  assert rabin_karp(lowerCAmelCase__      ,       lowerCAmelCase__						)
  lowerCamelCase__: int         ="Lue"
  assert not rabin_karp(lowerCAmelCase__      ,       lowerCAmelCase__						)
  print("Success."						)


if __name__ == "__main__":
     test_rabin_karp()






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