

from __future__ import annotations


class 			A						:







    """simple docstring"""





    def __init__(				self			:	List[str],lowercase_			:	str,lowercase_			:	str		)->   Union[str, Any]:





        '''simple docstring'''







        A__   				=       text, pattern
        A__   				=       len(lowercase_		), len(lowercase_		)


    def 						snake_case__					(				self			:	Any,lowercase_			:	str		)->   Union[str, Any]:





        '''simple docstring'''







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


    def 						snake_case__					(				self			:	Optional[int],lowercase_			:	int		)->   str:





        '''simple docstring'''







        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 						snake_case__					(				self			:	List[Any]		)->   int:





        '''simple docstring'''







        A__   				=       []
        for i in range(self.textLen - self.patLen + 1		):
            A__   				=       self.mismatch_in_text(lowercase_		)
            if mismatch_index == -1:
                positions.append(lowercase_		)
            else:
                A__   				=       self.match_in_pattern(self.text[mismatch_index]		)
                A__   				=       (
                    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)





from ...utils import (
    OptionalDependencyNotAvailable,
    is_torch_available,
    is_transformers_available,
    is_transformers_version,
)


try:
     if not (is_transformers_available() and is_torch_available()):
          raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
     from ...utils.dummy_torch_and_transformers_objects import (
         ImageTextPipelineOutput,
         UniDiffuserPipeline,
     )
else:
     from .modeling_text_decoder import UniDiffuserTextDecoder
     from .modeling_uvit import UniDiffuserModel, UTransformeraDModel
     from .pipeline_unidiffuser import ImageTextPipelineOutput, UniDiffuserPipeline

