





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   a_ (			__a      ):
			A__      :			Any       	=  ['image_processor', 'tokenizer']
			A__      :			Tuple       	=  'BlipImageProcessor'
			A__      :			Union[str, Any]       	=  ('BertTokenizer', 'BertTokenizerFast')

			def __init__(   self   :  List[Any]     , UpperCAmelCase__   :  Any     , UpperCAmelCase__   :  Union[str, Any]						):






							"""simple docstring"""
							snake_case   :					Optional[int]    						=				False
							super().__init__(_UpperCamelCase     , _UpperCamelCase						)
							snake_case   :					Union[str, Any]    						=				self.image_processor

			def __call__(   self   :  str     , UpperCAmelCase__   :  Dict = None     , UpperCAmelCase__   :  str = None     , UpperCAmelCase__   :  Tuple = True     , UpperCAmelCase__   :  str = False     , UpperCAmelCase__   :  Union[str, Any] = None     , UpperCAmelCase__   :  str = None     , UpperCAmelCase__   :  Tuple = 0     , UpperCAmelCase__   :  Union[str, Any] = None     , UpperCAmelCase__   :  Dict = None     , UpperCAmelCase__   :  Any = False     , UpperCAmelCase__   :  List[str] = False     , UpperCAmelCase__   :  str = False     , UpperCAmelCase__   :  Optional[Any] = False     , UpperCAmelCase__   :  Optional[Any] = False     , UpperCAmelCase__   :  int = True     , UpperCAmelCase__   :  List[str] = None     , **UpperCAmelCase__   :  Optional[int]     , ):






							"""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:
											snake_case   :					str    						=				self.tokenizer
											snake_case   :					int    						=				self.tokenizer(
											    text=_UpperCamelCase     , add_special_tokens=_UpperCamelCase     , padding=_UpperCamelCase     , truncation=_UpperCamelCase     , max_length=_UpperCamelCase     , stride=_UpperCamelCase     , pad_to_multiple_of=_UpperCamelCase     , return_attention_mask=_UpperCamelCase     , return_overflowing_tokens=_UpperCamelCase     , return_special_tokens_mask=_UpperCamelCase     , return_offsets_mapping=_UpperCamelCase     , return_token_type_ids=_UpperCamelCase     , return_length=_UpperCamelCase     , verbose=_UpperCamelCase     , return_tensors=_UpperCamelCase     , **_UpperCamelCase     , )
											return text_encoding

							# add pixel_values
							snake_case   :					Union[str, Any]    						=				self.image_processor(_UpperCamelCase     , return_tensors=_UpperCamelCase						)

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

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

							return encoding_image_processor

			def      lowerCAmelCase(   self   :  Union[str, Any]     , *UpperCAmelCase__   :  Any     , **UpperCAmelCase__   :  List[str]						):






							"""simple docstring"""
							return self.tokenizer.batch_decode(*_UpperCamelCase     , **_UpperCamelCase						)

			def      lowerCAmelCase(   self   :  Any     , *UpperCAmelCase__   :  Dict     , **UpperCAmelCase__   :  Dict						):






							"""simple docstring"""
							return self.tokenizer.decode(*_UpperCamelCase     , **_UpperCamelCase						)



			@property
			def      lowerCAmelCase(   self   :  Union[str, Any]						):






							"""simple docstring"""
							snake_case   :					str    						=				self.tokenizer.model_input_names
							snake_case   :					Dict    						=				self.image_processor.model_input_names
							return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names						)						)


from math import loga






def   lowerCamelCase__							(							__lowerCAmelCase    :    int							):




			"""simple docstring"""


			if a < 0:
						raise ValueError("Input value must be a positive integer"							)
			elif isinstance(__lowerCAmelCase       ,				__lowerCAmelCase							):
						raise TypeError("Input value must be a 'int' type"							)
			return 0 if (a == 0) else int(loga(a & -a							)							)


if __name__ == "__main__":
			import doctest

			doctest.testmod()



