code: def __init__(
      self,
      state_dimension1: int,
      state_dimension2: int,
      target_state_size: int,
      dropout_rate: float = 0.0,
  ):
      super().__init__()
      self.__input_dim1 = state_dimension1
      self.__input_dim2 = state_dimension2
  
      self.__linear_combination = nn.Linear(
          in_features=state_dimension1 + state_dimension2,
          out_features=target_state_size,
          bias=False,
      )
      self._original_input = None
      self.__dropout = nn.Dropout(p=dropout_rate)
  
imports: import torch
  from torch import nn
  from typing import Dict, List, Tuple
  from ptgnn.neuralmodels.gnn.messagepassing.abstractmessagepassing import AbstractMessagePassingLayer
label_desc: Use image node_id 1 to create a new LinearResidualLayer object from inherited base classes: AbstractMessagePassingLayer with example: obj = LinearResidualLayer(state_dimension1, state_dimension2, target_state_size, dropout_rate)