

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


A__						=							logging.get_logger(__name__)

A__						=							{
    "unc-nlp/lxmert-base-uncased": "https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json",
}

class 				__UpperCamelCase				(					SCREAMING_SNAKE_CASE			):
	_lowercase  :   Tuple       				=  "lxmert"
	_lowercase  :   int       				=  {}







	def __init__(   self: Optional[Any]  , __UpperCamelCase: Dict=3_05_22  , __UpperCamelCase: List[str]=7_68  , __UpperCamelCase: List[str]=12  , __UpperCamelCase: str=95_00  , __UpperCamelCase: Any=16_00  , __UpperCamelCase: Dict=4_00  , __UpperCamelCase: int=30_72  , __UpperCamelCase: Optional[Any]="gelu"  , __UpperCamelCase: Tuple=0.1  , __UpperCamelCase: Dict=0.1  , __UpperCamelCase: Dict=5_12  , __UpperCamelCase: Dict=2  , __UpperCamelCase: Optional[Any]=0.02  , __UpperCamelCase: List[str]=1E-12  , __UpperCamelCase: List[Any]=9  , __UpperCamelCase: List[Any]=5  , __UpperCamelCase: Tuple=5  , __UpperCamelCase: Dict=20_48  , __UpperCamelCase: List[str]=4  , __UpperCamelCase: str=6.67  , __UpperCamelCase: Optional[Any]=True  , __UpperCamelCase: Tuple=True  , __UpperCamelCase: List[str]=True  , __UpperCamelCase: List[Any]=True  , __UpperCamelCase: int=True  , __UpperCamelCase: Dict=True  , __UpperCamelCase: str=True  , **__UpperCamelCase: List[str]  , ):

						'''simple docstring'''





						__magic_name__							=    vocab_size
						__magic_name__							=    hidden_size
						__magic_name__							=    num_attention_heads
						__magic_name__							=    hidden_act
						__magic_name__							=    intermediate_size
						__magic_name__							=    hidden_dropout_prob
						__magic_name__							=    attention_probs_dropout_prob
						__magic_name__							=    max_position_embeddings
						__magic_name__							=    type_vocab_size
						__magic_name__							=    initializer_range
						__magic_name__							=    layer_norm_eps
						__magic_name__							=    num_qa_labels
						__magic_name__							=    num_object_labels
						__magic_name__							=    num_attr_labels
						__magic_name__							=    l_layers
						__magic_name__							=    x_layers
						__magic_name__							=    r_layers
						__magic_name__							=    visual_feat_dim
						__magic_name__							=    visual_pos_dim
						__magic_name__							=    visual_loss_normalizer
						__magic_name__							=    task_matched
						__magic_name__							=    task_mask_lm
						__magic_name__							=    task_obj_predict
						__magic_name__							=    task_qa
						__magic_name__							=    visual_obj_loss
						__magic_name__							=    visual_attr_loss
						__magic_name__							=    visual_feat_loss
						__magic_name__							=    {'vision': r_layers, 'cross_encoder': x_layers, 'language': l_layers}
						super().__init__(**__UpperCamelCase      )







import os

A__						=							{"I": 1, "V": 5, "X": 10, "L": 50, "C": 100, "D": 500, "M": 1000}




def 					_lowercase     (				a_				:					str				)				->	int:




					'''simple docstring'''







					__magic_name__							=    0

					__magic_name__							=    0
					while index < len(a_				) - 1:
										__magic_name__							=    SYMBOLS[numerals[index]]
										__magic_name__							=    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 					_lowercase     (				a_				:					int				)				->	str:




					'''simple docstring'''







					__magic_name__							=    ''

					__magic_name__							=    num // 1_0_0_0
					numerals += m_count * "M"
					num %= 1_0_0_0

					__magic_name__							=    num // 1_0_0
					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_0_0

					__magic_name__							=    num // 1_0
					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 %= 1_0

					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 					_lowercase     (				a_				:					str = "/p089_roman.txt"				)				->	int:




					'''simple docstring'''







					__magic_name__							=    0

					with open(os.path.dirname(a_				) + roman_numerals_filename				) as filea:
										__magic_name__							=    filea.readlines()

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

					return savings


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




