






"""simple docstring"""



from typing import List, Optional, Union

from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType






class 							__SCREAMING_SNAKE_CASE						(				UpperCamelCase		):
							snake_case_     =							['image_processor', 'tokenizer']
							snake_case_     =							'BlipImageProcessor'
							snake_case_     =							('BertTokenizer', 'BertTokenizerFast')


							def __init__(			self      :						int			,    snake_case      :						List[Any]			,    snake_case      :						int							):
									'''simple docstring'''





									A__						:  Optional[Any]		  =  False
									super().__init__(snake_case			,    snake_case							)
									A__						:  Optional[int]		  =  self.image_processor


							def __call__(			self      :						Optional[Any]			,    snake_case      :						ImageInput = None			,    snake_case      :						Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None			,    snake_case      :						bool = True			,    snake_case      :						Union[bool, str, PaddingStrategy] = False			,    snake_case      :						Union[bool, str, TruncationStrategy] = None			,    snake_case      :						Optional[int] = None			,    snake_case      :						int = 0			,    snake_case      :						Optional[int] = None			,    snake_case      :						Optional[bool] = None			,    snake_case      :						bool = False			,    snake_case      :						bool = False			,    snake_case      :						bool = False			,    snake_case      :						bool = False			,    snake_case      :						bool = False			,    snake_case      :						bool = True			,    snake_case      :						Optional[Union[str, TensorType]] = None			,    **snake_case      :						Union[str, Any]			,    ):
									'''simple docstring'''





									if images is None and text is None:
											raise ValueError("""You have to specify either images or text."""							)

									# Get only text
									if images is None:
											A__						:  Optional[int]		  =  self.tokenizer
											A__						:  int		  =  self.tokenizer(
											    text=snake_case			,    add_special_tokens=snake_case			,    padding=snake_case			,    truncation=snake_case			,    max_length=snake_case			,    stride=snake_case			,    pad_to_multiple_of=snake_case			,    return_attention_mask=snake_case			,    return_overflowing_tokens=snake_case			,    return_special_tokens_mask=snake_case			,    return_offsets_mapping=snake_case			,    return_token_type_ids=snake_case			,    return_length=snake_case			,    verbose=snake_case			,    return_tensors=snake_case			,    **snake_case			,    )
											return text_encoding

									# add pixel_values
									A__						:  int		  =  self.image_processor(snake_case			,    return_tensors=snake_case							)

									if text is not None:
											A__						:  Optional[int]		  =  self.tokenizer(
											    text=snake_case			,    add_special_tokens=snake_case			,    padding=snake_case			,    truncation=snake_case			,    max_length=snake_case			,    stride=snake_case			,    pad_to_multiple_of=snake_case			,    return_attention_mask=snake_case			,    return_overflowing_tokens=snake_case			,    return_special_tokens_mask=snake_case			,    return_offsets_mapping=snake_case			,    return_token_type_ids=snake_case			,    return_length=snake_case			,    verbose=snake_case			,    return_tensors=snake_case			,    **snake_case			,    )
									else:
											A__						:  str		  =  None

									if text_encoding is not None:
											encoding_image_processor.update(snake_case							)

									return encoding_image_processor


							def 						_UpperCamelCase       (			self      :						Any			,    *snake_case      :						Tuple			,    **snake_case      :						Tuple							):
									'''simple docstring'''





									return self.tokenizer.batch_decode(*snake_case			,    **snake_case							)


							def 						_UpperCamelCase       (			self      :						List[str]			,    *snake_case      :						Any			,    **snake_case      :						List[str]							):
									'''simple docstring'''





									return self.tokenizer.decode(*snake_case			,    **snake_case							)


							@property
							def 						_UpperCamelCase       (			self      :						List[Any]							):
									'''simple docstring'''





									A__						:  Optional[Any]		  =  self.tokenizer.model_input_names
									A__						:  Union[str, Any]		  =  self.image_processor.model_input_names
									return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names							)							)














"""simple docstring"""



import baseaa




def      _lowerCAmelCase		(							UpperCAmelCase__       :					str      )		->bytes:
						return baseaa.baaencode(string.encode("""utf-8"""      )      )




def      _lowerCAmelCase		(							UpperCAmelCase__       :					bytes      )		->str:
						return baseaa.baadecode(UpperCAmelCase__      ).decode("""utf-8"""      )


if __name__ == "__main__":
						A_    =							'''Hello World!'''
						A_    =							baseaa_encode(test)
						print(encoded)

						A_    =							baseaa_decode(encoded)
						print(decoded)






