


from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding



class 		snake_case_(       _snake_case			):
     __UpperCamelCase  =					['''image_processor''', '''tokenizer''']
     __UpperCamelCase  =					'''AutoImageProcessor'''
     __UpperCamelCase  =					'''AutoTokenizer'''






     def __init__(	self  :					Tuple					,				UpperCamelCase_  :					Tuple					,				UpperCamelCase_  :					str				):
           super().__init__(lowerCAmelCase__					,				lowerCAmelCase__				)
           lowerCAmelCase					:	Optional[Any]       =   self.image_processor






     def __call__(	self  :					List[Any]					,				UpperCamelCase_  :					int=None					,				UpperCamelCase_  :					Any=None					,				UpperCamelCase_  :					Optional[Any]=None					,				**UpperCamelCase_  :					int				):

           if text is None and images is None:
                 raise ValueError('''You have to specify either text or images. Both cannot be none.'''				)

           if text is not None:
                 lowerCAmelCase					:	List[Any]       =   self.tokenizer(lowerCAmelCase__					,				return_tensors=lowerCAmelCase__					,				**lowerCAmelCase__				)

           if images is not None:
                 lowerCAmelCase					:	Any       =   self.image_processor(lowerCAmelCase__					,				return_tensors=lowerCAmelCase__					,				**lowerCAmelCase__				)

           if text is not None and images is not None:
                 lowerCAmelCase					:	str       =   image_features.pixel_values
                 return encoding
           elif text is not None:
                 return encoding
           else:
                 return BatchEncoding(data=dict(**lowerCAmelCase__				)					,				tensor_type=lowerCAmelCase__				)






     def      lowerCamelCase__     (	self  :					Tuple					,				*UpperCamelCase_  :					int					,				**UpperCamelCase_  :					List[str]				):
           return self.tokenizer.batch_decode(*lowerCAmelCase__					,				**lowerCAmelCase__				)






     def      lowerCamelCase__     (	self  :					int					,				*UpperCamelCase_  :					Tuple					,				**UpperCamelCase_  :					Optional[Any]				):
           return self.tokenizer.decode(*lowerCAmelCase__					,				**lowerCAmelCase__				)






     @property
     def      lowerCamelCase__     (	self  :					List[str]				):
           return ["input_ids", "attention_mask", "pixel_values"]






"""simple docstring"""





from __future__ import annotations



class 		snake_case_:






     def __init__(	self  :					int					,				UpperCamelCase_  :					str					,				UpperCamelCase_  :					str				):
           lowerCAmelCase,      lowerCAmelCase					:	List[str]       =   text, pattern
           lowerCAmelCase,      lowerCAmelCase					:	Union[str, Any]       =   len(UpperCamelCase_				), len(UpperCamelCase_				)






     def      lowerCamelCase__     (	self  :					List[Any]					,				UpperCamelCase_  :					str				):

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






     def      lowerCamelCase__     (	self  :					Optional[Any]					,				UpperCamelCase_  :					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      lowerCamelCase__     (	self  :					Dict				):
           # searches pattern in text and returns index positions
           lowerCAmelCase					:	Union[str, Any]       =   []
           for i in range(self.textLen - self.patLen + 1				):
                 lowerCAmelCase					:	str       =   self.mismatch_in_text(UpperCamelCase_				)
                 if mismatch_index == -1:
                       positions.append(UpperCamelCase_				)
                 else:
                       lowerCAmelCase					:	Optional[Any]       =   self.match_in_pattern(self.text[mismatch_index]				)
                       lowerCAmelCase					:	int       =   (
                           mismatch_index - match_index
                       )  # shifting index lgtm [py/multiple-definition]
           return positions



snake_case__		:     str    				=				'''ABAABA'''
snake_case__		:     List[str]    				=				'''AB'''
snake_case__		:     Union[str, Any]    				=				BoyerMooreSearch(text, pattern)
snake_case__		:     Optional[Any]    				=				bms.bad_character_heuristic()

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


