
from typing import Dict

from .base import GenericTensor, Pipeline





class 							UpperCAmelCase      (  __SCREAMING_SNAKE_CASE  ):




	'''simple docstring'''





	def 				UpperCamelCase_  (       self					: int							,A					: Optional[int]=None							,A					: Tuple=None							,A					: List[str]=None							,**A					: List[str] ):
					if tokenize_kwargs is None:
									__A   			= {}

					if truncation is not None:
									if "truncation" in tokenize_kwargs:
													raise ValueError(
													    "truncation parameter defined twice (given as keyword argument as well as in tokenize_kwargs)" )
									__A   			= truncation

					__A   			= tokenize_kwargs

					__A   			= {}
					if return_tensors is not None:
									__A   			= return_tensors

					return preprocess_params, {}, postprocess_params






	def 				UpperCamelCase_  (       self					: List[str]							,A					: str							,**A					: str ):
					__A   			= self.framework
					__A   			= self.tokenizer(A							,return_tensors=A							,**A )
					return model_inputs






	def 				UpperCamelCase_  (       self					: Any							,A					: Dict ):
					__A   			= self.model(**A )
					return model_outputs






	def 				UpperCamelCase_  (       self					: str							,A					: List[str]							,A					: int=False ):
					# [0] is the first available tensor, logits or last_hidden_state.
					if return_tensors:
									return model_outputs[0]
					if self.framework == "pt":
									return model_outputs[0].tolist()
					elif self.framework == "tf":
									return model_outputs[0].numpy().tolist()







	def __call__(       self					: int							,*A					: Tuple							,**A					: Optional[Any] ):
					return super().__call__(*A							,**A )


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()
