code: def test_set_weights_between_different_models(self):
      model1 = TestModel4()
      model2 = TestModel4()
  
      pred_program = fluid.Program()
      with fluid.program_guard(pred_program):
          obs = layers.data(name="obs", shape=[4], dtype="float32")
          model1_output = model1.predict(obs)
          model2_output = model2.predict(obs)
  
      self.executor.run(fluid.default_startup_program())
  
      N = 10
      random_obs = np.random.random(size=(N, 4)).astype("float32")
      for i in range(N):
          x = np.expand_dims(random_obs[i], axis=0)
          outputs = self.executor.run(
              pred_program,
              feed={"obs": x},
              fetch_list=[model1_output, model2_output],
          )
          self.assertNotEqual(
              outputs[0].flatten(), outputs[1].flatten()
          )
  
      # pass parameters of self.model to model2
      params = model1.get_weights()
      model2.set_weights(params)
  
      random_obs = np.random.random(size=(N, 4)).astype("float32")
      for i in range(N):
          x = np.expand_dims(random_obs[i], axis=0)
          outputs = self.executor.run(
              pred_program,
              feed={"obs": x},
              fetch_list=[model1_output, model2_output],
          )
          self.assertEqual(outputs[0].flatten(), outputs[1].flatten())
  
imports: import numpy
  import paddle.fluid
  import parl
  import unittest
  from copy import deepcopy
  from paddle.fluid import ParamAttr
  from parl import layers
  from parl.utils import get_gpu_count
  from parl.core.fluid.plutils import fetch_value
label_desc: Use image node_id 17 for calling the ModelBaseTest obj's underlying member method code with example usage: obj.test_set_weights_between_different_models() without return types