code: def test_fx_script_Perceptron(self) -> None:
      batch_size = 1
      in_features = 3
      out_features = 5
      m = Perceptron(in_features, out_features)
  
      # Dry-run to initialize lazy module.
      m(torch.randn(batch_size, in_features))
  
      gm = symbolic_trace(m)
      torch.jit.script(gm)
  
file_path: torchrec/torchrec/modules/tests/test_mlp.py
imports: import unittest
  from typing import Callable, List, Union
  import hypothesis.strategies
  import torch
  from hypothesis import given, settings
  from torch import nn
  from torchrec.fx import symbolic_trace
  from torchrec.modules.mlp import MLP, Perceptron
label_desc: Use image node_id 2 for calling the TestMLP obj's underlying member method code with example usage: obj.test_fx_script_Perceptron() without return types