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 __snake_case       (		lowerCamelCase_	):
			lowerCAmelCase_														=							["image_processor", "tokenizer"]
			lowerCAmelCase_														=							"BlipImageProcessor"
			lowerCAmelCase_														=							("BertTokenizer", "BertTokenizerFast")




			def __init__(					self    :       Any ,			_lowercase    :       Optional[Any] ,			_lowercase    :       Optional[Any]   ):



					"""simple docstring"""






					SCREAMING_SNAKE_CASE__    							=   False
					super().__init__(_lowercase ,			_lowercase   )
					SCREAMING_SNAKE_CASE__    							=   self.image_processor




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

					# add pixel_values
					SCREAMING_SNAKE_CASE__    							=   self.image_processor(_lowercase ,			return_tensors=_lowercase   )

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

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

					return encoding_image_processor




			def 			__a		(					self    :       str ,			*_lowercase    :       Optional[int] ,			**_lowercase    :       Tuple   ):



					"""simple docstring"""






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




			def 			__a		(					self    :       Any ,			*_lowercase    :       int ,			**_lowercase    :       str   ):



					"""simple docstring"""






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




			@property
			def 			__a		(					self    :       Optional[Any]   ):



					"""simple docstring"""






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

import os

__lowerCamelCase    :				Union[str, Any]							     =	{'''I''': 1, '''V''': 5, '''X''': 10, '''L''': 50, '''C''': 100, '''D''': 500, '''M''': 1000}



def 			__SCREAMING_SNAKE_CASE						(      __UpperCamelCase					: str			)							->      int:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__    							=   0

  SCREAMING_SNAKE_CASE__    							=   0
  while index < len(__UpperCamelCase			) - 1:
    SCREAMING_SNAKE_CASE__    							=   SYMBOLS[numerals[index]]
    SCREAMING_SNAKE_CASE__    							=   SYMBOLS[numerals[index + 1]]
    if current_value < next_value:
      total_value -= current_value
    else:
      total_value += current_value
    index += 1
  total_value += SYMBOLS[numerals[index]]

  return total_value



def 			__SCREAMING_SNAKE_CASE						(      __UpperCamelCase					: int			)							->      str:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__    							=   """"""

  SCREAMING_SNAKE_CASE__    							=   num // 10_00
  numerals += m_count * "M"
  num %= 10_00

  SCREAMING_SNAKE_CASE__    							=   num // 1_00
  if c_count == 9:
    numerals += "CM"
    c_count -= 9
  elif c_count == 4:
    numerals += "CD"
    c_count -= 4
  if c_count >= 5:
    numerals += "D"
    c_count -= 5
  numerals += c_count * "C"
  num %= 1_00

  SCREAMING_SNAKE_CASE__    							=   num // 10
  if x_count == 9:
    numerals += "XC"
    x_count -= 9
  elif x_count == 4:
    numerals += "XL"
    x_count -= 4
  if x_count >= 5:
    numerals += "L"
    x_count -= 5
  numerals += x_count * "X"
  num %= 10

  if num == 9:
    numerals += "IX"
    num -= 9
  elif num == 4:
    numerals += "IV"
    num -= 4
  if num >= 5:
    numerals += "V"
    num -= 5
  numerals += num * "I"

  return numerals



def 			__SCREAMING_SNAKE_CASE						(      __UpperCamelCase					: str = "/p089_roman.txt"			)							->      int:







  """simple docstring"""





  SCREAMING_SNAKE_CASE__    							=   0

  with open(os.path.dirname(__UpperCamelCase			) + roman_numerals_filename			) as filea:
    SCREAMING_SNAKE_CASE__    							=   filea.readlines()

  for line in lines:
    SCREAMING_SNAKE_CASE__    							=   line.strip()
    SCREAMING_SNAKE_CASE__    							=   parse_roman_numerals(__UpperCamelCase			)
    SCREAMING_SNAKE_CASE__    							=   generate_roman_numerals(__UpperCamelCase			)
    savings += len(__UpperCamelCase			) - len(__UpperCamelCase			)

  return savings


if __name__ == "__main__":
   print(F"""{solution() = }""")
