


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    lowerCamelCase__						(		_a    ):
      a :     Optional[Any]											=		["""image_processor""", """tokenizer"""]
      a :     Tuple											=		"""BlipImageProcessor"""
      a :     List[Any]											=		("""BertTokenizer""", """BertTokenizerFast""")
      def __init__(		self	:	Dict      ,       A_	:	List[str]      ,       A_	:	Any							):






       '''simple docstring'''


       __lowercase									=	False
       super().__init__(A_      ,       A_							)
       __lowercase									=	self.image_processor
      def __call__(		self	:	int      ,       A_	:	ImageInput = None      ,       A_	:	Union[TextInput, PreTokenizedInput, List[TextInput], List[PreTokenizedInput]] = None      ,       A_	:	bool = True      ,       A_	:	Union[bool, str, PaddingStrategy] = False      ,       A_	:	Union[bool, str, TruncationStrategy] = None      ,       A_	:	Optional[int] = None      ,       A_	:	int = 0      ,       A_	:	Optional[int] = None      ,       A_	:	Optional[bool] = None      ,       A_	:	bool = False      ,       A_	:	bool = False      ,       A_	:	bool = False      ,       A_	:	bool = False      ,       A_	:	bool = False      ,       A_	:	bool = True      ,       A_	:	Optional[Union[str, TensorType]] = None      ,       **A_	:	List[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:
        __lowercase									=	self.tokenizer
        __lowercase									=	self.tokenizer(
            text=A_      ,       add_special_tokens=A_      ,       padding=A_      ,       truncation=A_      ,       max_length=A_      ,       stride=A_      ,       pad_to_multiple_of=A_      ,       return_attention_mask=A_      ,       return_overflowing_tokens=A_      ,       return_special_tokens_mask=A_      ,       return_offsets_mapping=A_      ,       return_token_type_ids=A_      ,       return_length=A_      ,       verbose=A_      ,       return_tensors=A_      ,       **A_      ,       )
        return text_encoding

       # add pixel_values
       __lowercase									=	self.image_processor(A_      ,       return_tensors=A_							)

       if text is not None:
        __lowercase									=	self.tokenizer(
            text=A_      ,       add_special_tokens=A_      ,       padding=A_      ,       truncation=A_      ,       max_length=A_      ,       stride=A_      ,       pad_to_multiple_of=A_      ,       return_attention_mask=A_      ,       return_overflowing_tokens=A_      ,       return_special_tokens_mask=A_      ,       return_offsets_mapping=A_      ,       return_token_type_ids=A_      ,       return_length=A_      ,       verbose=A_      ,       return_tensors=A_      ,       **A_      ,       )
       else:
        __lowercase									=	None

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

       return encoding_image_processor
      def SCREAMING_SNAKE_CASE_	(		self	:	Optional[int]      ,       *A_	:	Tuple      ,       **A_	:	Union[str, Any]							):






       '''simple docstring'''


       return self.tokenizer.batch_decode(*A_      ,       **A_							)
      def SCREAMING_SNAKE_CASE_	(		self	:	Optional[int]      ,       *A_	:	Optional[Any]      ,       **A_	:	Union[str, Any]							):






       '''simple docstring'''


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






      @property
      def SCREAMING_SNAKE_CASE_	(		self	:	List[str]							):






       '''simple docstring'''


       __lowercase									=	self.tokenizer.model_input_names
       __lowercase									=	self.image_processor.model_input_names
       return list(dict.fromkeys(tokenizer_input_names + image_processor_input_names							)							)




"""simple docstring"""

def lowerCAmelCase_      (				UpperCamelCase__	: int				,   UpperCamelCase__	: list ):






 """simple docstring"""







 _enforce_args(UpperCamelCase__				,   UpperCamelCase__ )
 if n == 0:
  return 0
 __lowercase									=	float("""-inf""" )
 for i in range(1				,   n + 1 ):
  __lowercase									=	max(
      UpperCamelCase__				,   prices[i - 1] + naive_cut_rod_recursive(n - i				,   UpperCamelCase__ ) )

 return max_revue


def lowerCAmelCase_      (				UpperCamelCase__	: int				,   UpperCamelCase__	: list ):






 """simple docstring"""







 _enforce_args(UpperCamelCase__				,   UpperCamelCase__ )
 __lowercase									=	[float("""-inf""" ) for _ in range(n + 1 )]
 return _top_down_cut_rod_recursive(UpperCamelCase__				,   UpperCamelCase__				,   UpperCamelCase__ )


def lowerCAmelCase_      (				UpperCamelCase__	: int				,   UpperCamelCase__	: list				,   UpperCamelCase__	: list ):






 """simple docstring"""







 if max_rev[n] >= 0:
  return max_rev[n]
 elif n == 0:
  return 0
 else:
  __lowercase									=	float("""-inf""" )
  for i in range(1				,   n + 1 ):
   __lowercase									=	max(
       UpperCamelCase__				,   prices[i - 1] + _top_down_cut_rod_recursive(n - i				,   UpperCamelCase__				,   UpperCamelCase__ )				,   )

  __lowercase									=	max_revenue

 return max_rev[n]


def lowerCAmelCase_      (				UpperCamelCase__	: int				,   UpperCamelCase__	: list ):






 """simple docstring"""







 _enforce_args(UpperCamelCase__				,   UpperCamelCase__ )

 # length(max_rev) = n + 1, to accommodate for the revenue obtainable from a rod of
 # length 0.
 __lowercase									=	[float("""-inf""" ) for _ in range(n + 1 )]
 __lowercase									=	0

 for i in range(1				,   n + 1 ):
  __lowercase									=	max_rev[i]
  for j in range(1				,   i + 1 ):
   __lowercase									=	max(UpperCamelCase__				,   prices[j - 1] + max_rev[i - j] )

  __lowercase									=	max_revenue_i

 return max_rev[n]


def lowerCAmelCase_      (				UpperCamelCase__	: int				,   UpperCamelCase__	: list ):






 """simple docstring"""







 if n < 0:
  __lowercase									=	f'''n must be greater than or equal to 0. Got n = {n}'''
  raise ValueError(UpperCamelCase__ )

 if n > len(UpperCamelCase__ ):
  __lowercase									=	(
      """Each integral piece of rod must have a corresponding price. """
      f'''Got n = {n} but length of prices = {len(UpperCamelCase__ )}'''
  )
  raise ValueError(UpperCamelCase__ )


def lowerCAmelCase_      (				):






 """simple docstring"""







 __lowercase									=	[6, 10, 12, 15, 20, 23]
 __lowercase									=	len(UpperCamelCase__ )

 # the best revenue comes from cutting the rod into 6 pieces, each
 # of length 1 resulting in a revenue of 6 * 6 = 36.
 __lowercase									=	36

 __lowercase									=	top_down_cut_rod(UpperCamelCase__				,   UpperCamelCase__ )
 __lowercase									=	bottom_up_cut_rod(UpperCamelCase__				,   UpperCamelCase__ )
 __lowercase									=	naive_cut_rod_recursive(UpperCamelCase__				,   UpperCamelCase__ )

 assert expected_max_revenue == max_rev_top_down
 assert max_rev_top_down == max_rev_bottom_up
 assert max_rev_bottom_up == max_rev_naive


if __name__ == "__main__":
       main()
