code: def __init__(self, d_model=64, dim_feedforward=128):
      super(ResidualBlock, self).__init__()
      self.relu = nn.ReLU()
      self.fc_residual = nn.Sequential(
          nn.Linear(d_model, dim_feedforward),
          nn.ReLU(),
          nn.Linear(dim_feedforward, d_model),
      )
      self.relu = nn.ReLU()
  
imports: import logging
  import math
  from typing import List
  import torch
  import torch.nn
  import torch.nn.functional
  from reagent.core import parameters, types
  from reagent.models import convolutional_network, fully_connected_network
  from reagent.models.base import ModelBase
  from reagent.models.fully_connected_network import ACTIVATION_MAP
label_desc: Use image node_id 1 to create a new ResidualBlock object from inherited base classes: nn with example: obj = ResidualBlock(d_model, dim_feedforward)