


from math import factorial
class _lowerCamelCase	:



		'''simple docstring'''







		def __init__( self		:						Tuple  ,					_A		:						List[str]  ,					_A		:						int      )  ->			Union[str, Any]:
			__magic_name__	:   Union[str, Any]					     =					real
			if isinstance(_A  ,					_A      ):
				__magic_name__	:   Optional[Any]					     =					[1] * rank
			else:
				__magic_name__	:   Optional[int]					     =					rank







		def __repr__( self		:						Optional[Any]      )  ->			str:
			return (
			    F'{self.real}+'
			    F'{"+".join(str(_A      )+"E"+str(n+1      )for n,dual in enumerate(self.duals      )      )}'
			)







		def        __lowerCAmelCase		( self		:						Union[str, Any]      )  ->			Any:
			__magic_name__	:   List[str]					     =					self.duals.copy()
			while cur[-1] == 0:
				cur.pop(-1      )
			return Dual(self.real  ,					_A      )







		def __add__( self		:						List[str]  ,					_A		:						List[Any]      )  ->			Tuple:
			if not isinstance(_A  ,					_A      ):
				return Dual(self.real + other  ,					self.duals      )
			__magic_name__	:   List[str]					     =					self.duals.copy()
			__magic_name__	:   int					     =					other.duals.copy()
			if len(_A      ) > len(_A      ):
				o_dual.extend([1] * (len(_A      ) - len(_A      ))      )
			elif len(_A      ) < len(_A      ):
				s_dual.extend([1] * (len(_A      ) - len(_A      ))      )
			__magic_name__	:   int					     =					[]
			for i in range(len(_A      )      ):
				new_duals.append(s_dual[i] + o_dual[i]      )
			return Dual(self.real + other.real  ,					_A      )

		A_     :      List[str]				   =    __add__







		def __sub__( self		:						Any  ,					_A		:						Any      )  ->			Optional[Any]:
			return self + other * -1







		def __mul__( self		:						int  ,					_A		:						Union[str, Any]      )  ->			int:
			if not isinstance(_A  ,					_A      ):
				__magic_name__	:   Optional[int]					     =					[]
				for i in self.duals:
					new_duals.append(i * other      )
				return Dual(self.real * other  ,					_A      )
			__magic_name__	:   Optional[Any]					     =					[0] * (len(self.duals      ) + len(other.duals      ) + 1)
			for i, item in enumerate(self.duals      ):
				for j, jtem in enumerate(other.duals      ):
					new_duals[i + j + 1] += item * jtem
			for k in range(len(self.duals      )      ):
				new_duals[k] += self.duals[k] * other.real
			for index in range(len(other.duals      )      ):
				new_duals[index] += other.duals[index] * self.real
			return Dual(self.real * other.real  ,					_A      )

		A_     :      Optional[Any]				   =    __mul__







		def __truediv__( self		:						Optional[int]  ,					_A		:						Any      )  ->			Optional[int]:
			if not isinstance(_A  ,					_A      ):
				__magic_name__	:   Tuple					     =					[]
				for i in self.duals:
					new_duals.append(i / other      )
				return Dual(self.real / other  ,					_A      )
			raise ValueError







		def __floordiv__( self		:						Dict  ,					_A		:						List[Any]      )  ->			Dict:
			if not isinstance(_A  ,					_A      ):
				__magic_name__	:   str					     =					[]
				for i in self.duals:
					new_duals.append(i // other      )
				return Dual(self.real // other  ,					_A      )
			raise ValueError







		def __pow__( self		:						List[str]  ,					_A		:						int      )  ->			Tuple:
			if n < 0 or isinstance(_A  ,					_A      ):
				raise ValueError('power must be a positive integer'      )
			if n == 0:
				return 1
			if n == 1:
				return self
			__magic_name__	:   int					     =					self
			for _ in range(n - 1      ):
				x *= self
			return x







def lowerCamelCase      (      lowerCAmelCase    :     List[str]		,		lowerCAmelCase    :     Optional[int]		,		lowerCAmelCase    :     Dict		):





	"""simple docstring"""







	if not callable(lowerCAmelCase		):
		raise ValueError('differentiate() requires a function as input for func'		)
	if not isinstance(lowerCAmelCase		,		(float, int)		):
		raise ValueError('differentiate() requires a float as input for position'		)
	if not isinstance(lowerCAmelCase		,		lowerCAmelCase		):
		raise ValueError('differentiate() requires an int as input for order'		)
	__magic_name__	:   Tuple					     =					Dual(lowerCAmelCase		,		1		)
	__magic_name__	:   Union[str, Any]					     =					func(lowerCAmelCase		)
	if order == 0:
		return result.real
	return result.duals[order - 1] * factorial(lowerCAmelCase		)


if __name__ == "__main__":
							import doctest

							doctest.testmod()





							def lowerCamelCase      (      lowerCAmelCase    :     Union[str, Any]		):





								"""simple docstring"""







								return y**2 * y**4





							print(differentiate(f, 9, 2))



'''simple docstring'''

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


lowerCAmelCase				:Any        =      logging.get_logger(__name__)

lowerCAmelCase				:int        =      {
    '''unc-nlp/lxmert-base-uncased''': '''https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json''',
}
class _lowerCamelCase	(						lowercase__							):



		'''simple docstring'''







		A_     :      List[str]				   =    """lxmert"""
		A_     :      int				   =    {}







		def __init__( self		:						int  ,					_A		:						List[Any]=30522  ,					_A		:						int=768  ,					_A		:						Any=12  ,					_A		:						Optional[Any]=9500  ,					_A		:						Any=1600  ,					_A		:						Tuple=400  ,					_A		:						str=3072  ,					_A		:						Tuple="gelu"  ,					_A		:						int=0.1  ,					_A		:						List[Any]=0.1  ,					_A		:						Dict=512  ,					_A		:						Dict=2  ,					_A		:						Tuple=0.02  ,					_A		:						List[Any]=1E-12  ,					_A		:						Optional[Any]=9  ,					_A		:						List[Any]=5  ,					_A		:						str=5  ,					_A		:						int=2048  ,					_A		:						Tuple=4  ,					_A		:						Tuple=6.67  ,					_A		:						Dict=True  ,					_A		:						str=True  ,					_A		:						str=True  ,					_A		:						Dict=True  ,					_A		:						str=True  ,					_A		:						int=True  ,					_A		:						Tuple=True  ,					**_A		:						int  ,					)  ->			str:
			__magic_name__	:   List[Any]					     =					vocab_size
			__magic_name__	:   List[Any]					     =					hidden_size
			__magic_name__	:   Optional[int]					     =					num_attention_heads
			__magic_name__	:   Dict					     =					hidden_act
			__magic_name__	:   Optional[Any]					     =					intermediate_size
			__magic_name__	:   str					     =					hidden_dropout_prob
			__magic_name__	:   List[str]					     =					attention_probs_dropout_prob
			__magic_name__	:   Tuple					     =					max_position_embeddings
			__magic_name__	:   Dict					     =					type_vocab_size
			__magic_name__	:   str					     =					initializer_range
			__magic_name__	:   str					     =					layer_norm_eps
			__magic_name__	:   Union[str, Any]					     =					num_qa_labels
			__magic_name__	:   str					     =					num_object_labels
			__magic_name__	:   List[str]					     =					num_attr_labels
			__magic_name__	:   Tuple					     =					l_layers
			__magic_name__	:   List[Any]					     =					x_layers
			__magic_name__	:   Optional[int]					     =					r_layers
			__magic_name__	:   Dict					     =					visual_feat_dim
			__magic_name__	:   Optional[int]					     =					visual_pos_dim
			__magic_name__	:   Optional[int]					     =					visual_loss_normalizer
			__magic_name__	:   int					     =					task_matched
			__magic_name__	:   Dict					     =					task_mask_lm
			__magic_name__	:   List[Any]					     =					task_obj_predict
			__magic_name__	:   str					     =					task_qa
			__magic_name__	:   List[Any]					     =					visual_obj_loss
			__magic_name__	:   Dict					     =					visual_attr_loss
			__magic_name__	:   int					     =					visual_feat_loss
			__magic_name__	:   Tuple					     =					{'vision': r_layers, 'cross_encoder': x_layers, 'language': l_layers}
			super().__init__(**_A      )