code: def forward(
      self,
      data_feature,
      real_attribute_input_noise,
      addi_attribute_input_noise,
      feature_input_noise,
      data_attribute,
  ):
      return self.model(
          [data_feature],
          [real_attribute_input_noise],
          [addi_attribute_input_noise],
          [feature_input_noise],
          [data_attribute],
      )
  
imports: import os
  import numpy
  import sys
  from collections import OrderedDict
  import math
  import torch
  import torch.nn.functional
  from torch import nn
  from pytorch_lightning import LightningModule
  from pytorch_lightning import seed_everything
  from .doppelganger import DoppelGANger
  from .network import RNNInitialStateType
  from .loss import doppelganger_loss
  from .util import gen_attribute_input_noise, gen_feature_input_noise, gen_feature_input_data_free, renormalize_per_sample
label_desc: Use image node_id 2 for calling the DoppelGANger_pl obj's underlying member method code with example usage: obj.forward(data_feature, real_attribute_input_noise, addi_attribute_input_noise, feature_input_noise, data_attribute) and returns: self