
__lowerCAmelCase					   =       2_5_6
# Modulus to hash a string
__lowerCAmelCase					   =       1_0_0_0_0_0_3


def    a      ( a		,						a	)     ->bool:




			'''simple docstring'''


			SCREAMING_SNAKE_CASE     						= len(a	)
			SCREAMING_SNAKE_CASE     						= len(a	)
			if p_len > t_len:
						return False

			SCREAMING_SNAKE_CASE     						= 0
			SCREAMING_SNAKE_CASE     						= 0
			SCREAMING_SNAKE_CASE     						= 1

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


def    a      ( )     ->None:




			'''simple docstring'''


			SCREAMING_SNAKE_CASE     						= '''abc1abc12'''
			SCREAMING_SNAKE_CASE     						= '''alskfjaldsabc1abc1abc12k23adsfabcabc'''
			SCREAMING_SNAKE_CASE     						= '''alskfjaldsk23adsfabcabc'''
			assert rabin_karp(a		,						a	) and not rabin_karp(a		,						a	)

			# Test 2)
			SCREAMING_SNAKE_CASE     						= '''ABABX'''
			SCREAMING_SNAKE_CASE     						= '''ABABZABABYABABX'''
			assert rabin_karp(a		,						a	)

			# Test 3)
			SCREAMING_SNAKE_CASE     						= '''AAAB'''
			SCREAMING_SNAKE_CASE     						= '''ABAAAAAB'''
			assert rabin_karp(a		,						a	)

			# Test 4)
			SCREAMING_SNAKE_CASE     						= '''abcdabcy'''
			SCREAMING_SNAKE_CASE     						= '''abcxabcdabxabcdabcdabcy'''
			assert rabin_karp(a		,						a	)

			# Test 5)
			SCREAMING_SNAKE_CASE     						= '''Lü'''
			SCREAMING_SNAKE_CASE     						= '''Lüsai'''
			assert rabin_karp(a		,						a	)
			SCREAMING_SNAKE_CASE     						= '''Lue'''
			assert not rabin_karp(a		,						a	)
			print('''Success.'''	)


if __name__ == "__main__":
							test_rabin_karp()

from typing import TYPE_CHECKING

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available


__lowerCAmelCase					   =       {
    'configuration_bloom': ['BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BloomConfig', 'BloomOnnxConfig'],
}
try:
							if not is_tokenizers_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase					   =       ['BloomTokenizerFast']

try:
							if not is_torch_available():
														raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
							pass
else:
							__lowerCAmelCase					   =       [
							    'BLOOM_PRETRAINED_MODEL_ARCHIVE_LIST',
							    'BloomForCausalLM',
							    'BloomModel',
							    'BloomPreTrainedModel',
							    'BloomForSequenceClassification',
							    'BloomForTokenClassification',
							    'BloomForQuestionAnswering',
							]

if TYPE_CHECKING:
							from .configuration_bloom import BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP, BloomConfig, BloomOnnxConfig

							try:
														if not is_tokenizers_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .tokenization_bloom_fast import BloomTokenizerFast

							try:
														if not is_torch_available():
																					raise OptionalDependencyNotAvailable()
							except OptionalDependencyNotAvailable:
														pass
							else:
														from .modeling_bloom import (
														    BLOOM_PRETRAINED_MODEL_ARCHIVE_LIST,
														    BloomForCausalLM,
														    BloomForQuestionAnswering,
														    BloomForSequenceClassification,
														    BloomForTokenClassification,
														    BloomModel,
														    BloomPreTrainedModel,
														)

else:
							import sys

							__lowerCAmelCase					   =       _LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)