code: def test_mul(self, T, n, d):
      model = ModelHelper(name="external")
  
      input_blob, initial_input_blob = model.net.AddExternalInputs(
          "input", "initial_input"
      )
  
      step = ModelHelper(name="step", param_model=model)
      input_t, output_t_prev = step.net.AddExternalInput(
          "input_t", "output_t_prev"
      )
      output_t = step.net.Mul([input_t, output_t_prev])
      step.net.AddExternalOutput(output_t)
  
      self.simple_rnn(
          T,
          n,
          d,
          model,
          step,
          input_t,
          output_t,
          output_t_prev,
          input_blob,
          initial_input_blob,
      )
  
file_path: pytorch/caffe2/python/operator_test/recurrent_network_test.py
imports: from caffe2.python import recurrent, workspace
  from caffe2.python.model_helper import ModelHelper
  from hypothesis import given, settings
  import caffe2.python.hypothesis_test_util
  import caffe2.python.serialized_test.serialized_test_util
  import hypothesis.strategies
  import numpy
label_desc: Use image node_id 2 for calling the RecurrentNetworkTest obj's underlying member method code with example usage: obj.test_mul(T, n, d) without return types