import copy
import os
from typing import Union

from ...configuration_utils import PretrainedConfig
from ...utils import logging


__lowerCamelCase    :				Tuple							     =	logging.get_logger(__name__)

__lowerCamelCase    :				Optional[int]							     =	{
    '''google/pix2struct-textcaps-base''': (
        '''https://huggingface.co/google/pix2struct-textcaps-base/resolve/main/config.json'''
    ),
}







class __snake_case       (		lowerCamelCase_	):
   lowerCAmelCase_														=							"pix2struct_text_model"
   lowerCAmelCase_														=							["past_key_values"]
   lowerCAmelCase_														=							{
       "hidden_size": "hidden_size",
       "num_attention_heads": "num_heads",
       "num_hidden_layers": "num_layers",
   }




   def __init__(					self    :       List[Any] ,			_lowercase    :       Dict=5_02_44 ,			_lowercase    :       Optional[int]=7_68 ,			_lowercase    :       Dict=64 ,			_lowercase    :       str=20_48 ,			_lowercase    :       int=12 ,			_lowercase    :       Any=12 ,			_lowercase    :       Any=32 ,			_lowercase    :       Tuple=1_28 ,			_lowercase    :       List[str]=0.1 ,			_lowercase    :       Tuple=1E-6 ,			_lowercase    :       str=1.0 ,			_lowercase    :       Union[str, Any]="gelu_new" ,			_lowercase    :       int=0 ,			_lowercase    :       List[str]=False ,			_lowercase    :       List[Any]=0 ,			_lowercase    :       List[str]=1 ,			_lowercase    :       List[Any]=False ,			_lowercase    :       List[Any]=True ,			**_lowercase    :       Union[str, Any] ,			):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   vocab_size
     SCREAMING_SNAKE_CASE__    							=   hidden_size
     SCREAMING_SNAKE_CASE__    							=   d_kv
     SCREAMING_SNAKE_CASE__    							=   d_ff
     SCREAMING_SNAKE_CASE__    							=   num_layers
     SCREAMING_SNAKE_CASE__    							=   num_heads
     SCREAMING_SNAKE_CASE__    							=   relative_attention_num_buckets
     SCREAMING_SNAKE_CASE__    							=   relative_attention_max_distance
     SCREAMING_SNAKE_CASE__    							=   dropout_rate
     SCREAMING_SNAKE_CASE__    							=   layer_norm_epsilon
     SCREAMING_SNAKE_CASE__    							=   initializer_factor
     SCREAMING_SNAKE_CASE__    							=   use_cache

     SCREAMING_SNAKE_CASE__    							=   eos_token_id
     SCREAMING_SNAKE_CASE__    							=   decoder_start_token_id

     # for backwards compatibility
     SCREAMING_SNAKE_CASE__    							=   dense_act_fn

     super().__init__(
         pad_token_id=_lowercase ,			eos_token_id=_lowercase ,			decoder_start_token_id=_lowercase ,			tie_word_embeddings=_lowercase ,			is_decoder=_lowercase ,			**_lowercase ,			)




   @classmethod
   def 			__a		(					cls    :       Optional[Any] ,			_lowercase    :       Union[str, os.PathLike] ,			**_lowercase    :       Union[str, Any]   ):



     """simple docstring"""






     cls._set_token_in_kwargs(_lowercase   )

     SCREAMING_SNAKE_CASE__							,  SCREAMING_SNAKE_CASE__    							=   cls.get_config_dict(_lowercase ,			**_lowercase   )

     # get the text config dict if we are loading from Pix2StructConfig
     if config_dict.get("""model_type"""   ) == "pix2struct":
       SCREAMING_SNAKE_CASE__    							=   config_dict["""text_config"""]

     if "model_type" in config_dict and hasattr(cls ,			"""model_type"""   ) and config_dict["model_type"] != cls.model_type:
       logger.warning(
           f"""You are using a model of type {config_dict['model_type']} to instantiate a model of type """
           f"""{cls.model_type}. This is not supported for all configurations of models and can yield errors."""   )

     return cls.from_dict(_lowercase ,			**_lowercase   )







class __snake_case       (		lowerCamelCase_	):
   lowerCAmelCase_														=							"pix2struct_vision_model"




   def __init__(					self    :       List[str] ,			_lowercase    :       Tuple=7_68 ,			_lowercase    :       Any=7_68 ,			_lowercase    :       int=20_48 ,			_lowercase    :       int=64 ,			_lowercase    :       List[Any]=12 ,			_lowercase    :       Optional[int]=12 ,			_lowercase    :       Union[str, Any]="gelu_new" ,			_lowercase    :       str=1E-6 ,			_lowercase    :       Optional[int]=0.0 ,			_lowercase    :       List[Any]=0.0 ,			_lowercase    :       List[Any]=1E-10 ,			_lowercase    :       Union[str, Any]=1.0 ,			_lowercase    :       Optional[int]=40_96 ,			_lowercase    :       List[str]=32 ,			_lowercase    :       Optional[int]=1_28 ,			**_lowercase    :       Dict ,			):



     """simple docstring"""






     super().__init__(**_lowercase   )

     SCREAMING_SNAKE_CASE__    							=   hidden_size
     SCREAMING_SNAKE_CASE__    							=   patch_embed_hidden_size
     SCREAMING_SNAKE_CASE__    							=   d_ff
     SCREAMING_SNAKE_CASE__    							=   dropout_rate
     SCREAMING_SNAKE_CASE__    							=   num_hidden_layers
     SCREAMING_SNAKE_CASE__    							=   num_attention_heads
     SCREAMING_SNAKE_CASE__    							=   initializer_range
     SCREAMING_SNAKE_CASE__    							=   initializer_factor
     SCREAMING_SNAKE_CASE__    							=   attention_dropout
     SCREAMING_SNAKE_CASE__    							=   layer_norm_eps
     SCREAMING_SNAKE_CASE__    							=   dense_act_fn
     SCREAMING_SNAKE_CASE__    							=   seq_len
     SCREAMING_SNAKE_CASE__    							=   relative_attention_num_buckets
     SCREAMING_SNAKE_CASE__    							=   relative_attention_max_distance
     SCREAMING_SNAKE_CASE__    							=   d_kv




   @classmethod
   def 			__a		(					cls    :       Dict ,			_lowercase    :       Union[str, os.PathLike] ,			**_lowercase    :       Dict   ):



     """simple docstring"""






     cls._set_token_in_kwargs(_lowercase   )

     SCREAMING_SNAKE_CASE__							,  SCREAMING_SNAKE_CASE__    							=   cls.get_config_dict(_lowercase ,			**_lowercase   )

     # get the vision config dict if we are loading from Pix2StructConfig
     if config_dict.get("""model_type"""   ) == "pix2struct":
       SCREAMING_SNAKE_CASE__    							=   config_dict["""vision_config"""]

     if "model_type" in config_dict and hasattr(cls ,			"""model_type"""   ) and config_dict["model_type"] != cls.model_type:
       logger.warning(
           f"""You are using a model of type {config_dict['model_type']} to instantiate a model of type """
           f"""{cls.model_type}. This is not supported for all configurations of models and can yield errors."""   )

     return cls.from_dict(_lowercase ,			**_lowercase   )







class __snake_case       (		lowerCamelCase_	):
   lowerCAmelCase_														=							"pix2struct"
   lowerCAmelCase_														=							True




   def __init__(					self    :       Optional[int] ,			_lowercase    :       List[str]=None ,			_lowercase    :       Any=None ,			_lowercase    :       Any=1.0 ,			_lowercase    :       Tuple=0.02 ,			_lowercase    :       str=False ,			_lowercase    :       List[Any]=False ,			_lowercase    :       List[Any]=True ,			**_lowercase    :       Optional[Any] ,			):



     """simple docstring"""






     super().__init__(tie_word_embeddings=_lowercase ,			is_encoder_decoder=_lowercase ,			**_lowercase   )

     if text_config is None:
       SCREAMING_SNAKE_CASE__    							=   {}
       logger.info("""text_config is None. Initializing the Pix2StructTextConfig with default values."""   )

     if vision_config is None:
       SCREAMING_SNAKE_CASE__    							=   {}
       logger.info("""vision_config is None. Initializing the Pix2StructVisionConfig with default values."""   )

     SCREAMING_SNAKE_CASE__    							=   PixaStructTextConfig(**_lowercase   )
     SCREAMING_SNAKE_CASE__    							=   PixaStructVisionConfig(**_lowercase   )

     SCREAMING_SNAKE_CASE__    							=   self.text_config.decoder_start_token_id
     SCREAMING_SNAKE_CASE__    							=   self.text_config.pad_token_id
     SCREAMING_SNAKE_CASE__    							=   self.text_config.eos_token_id

     SCREAMING_SNAKE_CASE__    							=   initializer_factor
     SCREAMING_SNAKE_CASE__    							=   initializer_range

     SCREAMING_SNAKE_CASE__    							=   self.initializer_range
     SCREAMING_SNAKE_CASE__    							=   self.initializer_range

     SCREAMING_SNAKE_CASE__    							=   is_vqa




   @classmethod
   def 			__a		(					cls    :       Optional[Any] ,			_lowercase    :       PixaStructTextConfig ,			_lowercase    :       PixaStructVisionConfig ,			**_lowercase    :       List[Any]   ):



     """simple docstring"""






     return cls(text_config=text_config.to_dict() ,			vision_config=vision_config.to_dict() ,			**_lowercase   )




   def 			__a		(					self    :       List[str]   ):



     """simple docstring"""






     SCREAMING_SNAKE_CASE__    							=   copy.deepcopy(self.__dict__   )
     SCREAMING_SNAKE_CASE__    							=   self.text_config.to_dict()
     SCREAMING_SNAKE_CASE__    							=   self.vision_config.to_dict()
     SCREAMING_SNAKE_CASE__    							=   self.__class__.model_type
     return output

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() = }""")
