



from typing import Dict

from .base import GenericTensor, Pipeline






class     __a			(  SCREAMING_SNAKE_CASE					):



	def 		UpperCamelCase				(    self				:     List[str]					,						snake_case_				:     Union[str, Any]=None					,						snake_case_				:     Optional[int]=None					,						snake_case_				:     Union[str, Any]=None					,						**snake_case_				:     Optional[int])->				int:
						if tokenize_kwargs is None:
											__lowerCAmelCase						 ={}

						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)""")
											__lowerCAmelCase						 =truncation

						__lowerCAmelCase						 =tokenize_kwargs

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

						return preprocess_params, {}, postprocess_params



	def 		UpperCamelCase				(    self				:     str					,						snake_case_				:     Tuple					,						**snake_case_				:     Optional[int])->				Dict[str, GenericTensor]:
						__lowerCAmelCase						 =self.framework
						__lowerCAmelCase						 =self.tokenizer(snake_case_					,						return_tensors=snake_case_					,						**snake_case_)
						return model_inputs



	def 		UpperCamelCase				(    self				:     Tuple					,						snake_case_				:     Any)->				Union[str, Any]:
						__lowerCAmelCase						 =self.model(**snake_case_)
						return model_outputs



	def 		UpperCamelCase				(    self				:     Any					,						snake_case_				:     Tuple					,						snake_case_				:     str=False)->				Tuple:
						# [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				:     List[str]					,						*snake_case_				:     Union[str, Any]					,						**snake_case_				:     Any)->				Tuple:
						return super().__call__(*snake_case_					,						**snake_case_)









from __future__ import annotations






class     __a			:



	def __init__(    self				:     List[Any]					,						snake_case_				:     str					,						snake_case_				:     str)->				Optional[int]:
						__lowerCAmelCase ,						__lowerCAmelCase						 =text, pattern
						__lowerCAmelCase ,						__lowerCAmelCase						 =len(snake_case_), len(snake_case_)



	def 		UpperCamelCase				(    self				:     List[Any]					,						snake_case_				:     str)->				int:

						for i in range(self.patLen - 1					,						-1					,						-1):
											if char == self.pattern[i]:
																return i
						return -1



	def 		UpperCamelCase				(    self				:     List[str]					,						snake_case_				:     int)->				int:

						for i in range(self.patLen - 1					,						-1					,						-1):
											if self.pattern[i] != self.text[current_pos + i]:
																return current_pos + i
						return -1



	def 		UpperCamelCase				(    self				:     Dict)->				list[int]:
						# searches pattern in text and returns index positions
						__lowerCAmelCase						 =[]
						for i in range(self.textLen - self.patLen + 1):
											__lowerCAmelCase						 =self.mismatch_in_text(snake_case_)
											if mismatch_index == -1:
																positions.append(snake_case_)
											else:
																__lowerCAmelCase						 =self.match_in_pattern(self.text[mismatch_index])
																__lowerCAmelCase						 =(
																    mismatch_index - match_index
																)  # shifting index lgtm [py/multiple-definition]
						return positions


lowercase_													=      '''ABAABA'''
lowercase_													=      '''AB'''
lowercase_													=      BoyerMooreSearch(text, pattern)
lowercase_													=      bms.bad_character_heuristic()

if len(positions) == 0:
				print('''No match found''')
else:
				print('''Pattern found in following positions: ''')
				print(positions)




