





from typing import List

import numpy as np


def        SCREAMING_SNAKE_CASE      (       _UpperCAmelCase )			->     int:
    lowerCamelCase__    :      Any					 =		{key: len(a_ ) for key, value in gen_kwargs.items() if isinstance(a_						,	a_ )}
    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.'
            ) )
    lowerCamelCase__    :      List[str]					 =		max(lists_lengths.values()						,	default=0 )
    return max(1						,	a_ )


def        SCREAMING_SNAKE_CASE      (       _UpperCAmelCase						,	_UpperCAmelCase )			->     List[range]:
    lowerCamelCase__    :      Any					 =		[]
    for group_idx in range(a_ ):
        lowerCamelCase__    :      Optional[int]					 =		num_shards // max_num_jobs + (group_idx < (num_shards % max_num_jobs))
        if num_shards_to_add == 0:
            break
        lowerCamelCase__    :      str					 =		shards_indices_per_group[-1].stop if shards_indices_per_group else 0
        lowerCamelCase__    :      int					 =		range(a_						,	start + num_shards_to_add )
        shards_indices_per_group.append(a_ )
    return shards_indices_per_group


def        SCREAMING_SNAKE_CASE      (       _UpperCAmelCase						,	_UpperCAmelCase )			->     List[dict]:
    lowerCamelCase__    :      Optional[Any]					 =		_number_of_shards_in_gen_kwargs(a_ )
    if num_shards == 1:
        return [dict(a_ )]
    else:
        lowerCamelCase__    :      Dict					 =		_distribute_shards(num_shards=a_						,	max_num_jobs=a_ )
        return [
            {
                key: [value[shard_idx] for shard_idx in shard_indices_per_group[group_idx]]
                if isinstance(a_						,	a_ )
                else value
                for key, value in gen_kwargs.items()
            }
            for group_idx in range(len(a_ ) )
        ]


def        SCREAMING_SNAKE_CASE      (       _UpperCAmelCase )			->     dict:
    return {
        key: [value for gen_kwargs in gen_kwargs_list for value in gen_kwargs[key]]
        if isinstance(gen_kwargs_list[0][key]						,	a_ )
        else gen_kwargs_list[0][key]
        for key in gen_kwargs_list[0]
    }


def        SCREAMING_SNAKE_CASE      (       _UpperCAmelCase						,	_UpperCAmelCase )			->     dict:
    lowerCamelCase__    :      Tuple					 =		{len(a_ ) for value in gen_kwargs.values() if isinstance(a_						,	a_ )}
    lowerCamelCase__    :      Any					 =		{}
    for size in list_sizes:
        lowerCamelCase__    :      Any					 =		list(range(a_ ) )
        rng.shuffle(indices_per_size[size] )
    # Now let's copy the gen_kwargs and shuffle the lists based on their sizes
    lowerCamelCase__    :      List[str]					 =		dict(a_ )
    for key, value in shuffled_kwargs.items():
        if isinstance(a_						,	a_ ):
            lowerCamelCase__    :      Union[str, Any]					 =		[value[i] for i in indices_per_size[len(a_ )]]
    return shuffled_kwargs







SCREAMING_SNAKE_CASE							:Any							 =				256
# Modulus to hash a string
SCREAMING_SNAKE_CASE							:Union[str, Any]							 =				100_0003


def 						UpperCAmelCase			(	a_		,   a_						)		->	bool:







				"""simple docstring"""



				__A   			= len(a_						)
				__A   			= len(a_						)
				if p_len > t_len:
								return False

				__A   			= 0
				__A   			= 0
				__A   			= 1

				# Calculating the hash of pattern and substring of text
				for i in range(a_						):
								__A   			= (ord(pattern[i]						) + p_hash * alphabet_size) % modulus
								__A   			= (ord(text[i]						) + text_hash * alphabet_size) % modulus
								if i == p_len - 1:
												continue
								__A   			= (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
								__A   			= (
								    (text_hash - ord(text[i]						) * modulus_power) * alphabet_size
								    + ord(text[i + p_len]						)
								) % modulus
				return False


def 						UpperCAmelCase			(	)		->	None:







				"""simple docstring"""



				__A   			= "abc1abc12"
				__A   			= "alskfjaldsabc1abc1abc12k23adsfabcabc"
				__A   			= "alskfjaldsk23adsfabcabc"
				assert rabin_karp(a_		,   a_						) and not rabin_karp(a_		,   a_						)

				# Test 2)
				__A   			= "ABABX"
				__A   			= "ABABZABABYABABX"
				assert rabin_karp(a_		,   a_						)

				# Test 3)
				__A   			= "AAAB"
				__A   			= "ABAAAAAB"
				assert rabin_karp(a_		,   a_						)

				# Test 4)
				__A   			= "abcdabcy"
				__A   			= "abcxabcdabxabcdabcdabcy"
				assert rabin_karp(a_		,   a_						)

				# Test 5)
				__A   			= "Lü"
				__A   			= "Lüsai"
				assert rabin_karp(a_		,   a_						)
				__A   			= "Lue"
				assert not rabin_karp(a_		,   a_						)
				print("Success."						)


if __name__ == "__main__":
					test_rabin_karp()
