code: def forward(self, state_float_features: torch.Tensor):
      return self.model(
          rlt.FeatureData(float_features=state_float_features)
      )
  
imports: import logging
  import unittest
  from typing import Union
  import torch
  import torch.nn
  from reagent.core import types
  from reagent.models.dueling_q_network import DuelingQNetwork, ParametricDuelingQNetwork
  from reagent.test.models.test_utils import run_model_jit_trace
label_desc: Use image node_id 2 for calling the DuelingQNetworkTorchScriptWrapper obj's underlying member method code with example usage: obj.forward(state_float_features) and returns: self