code: def test_set_weights_between_different_models(self):
      model1 = TestModel()
      model2 = TestModel()
  
      N = 10
      random_obs = np.random.randn(N, 4).astype(np.float32)
      for i in range(N):
          x = paddle.to_tensor(random_obs[i])
          model1_output = model1.predict(x).numpy().sum()
          model2_output = model2.predict(x).numpy().sum()
          self.assertNotEqual(model1_output, model2_output)
  
      params = model1.get_weights()
      model2.set_weights(params)
  
      random_obs = np.random.randn(N, 4).astype(np.float32)
      for i in range(N):
          x = paddle.to_tensor(random_obs[i])
          model1_output = model1.predict(x).numpy().sum()
          model2_output = model2.predict(x).numpy().sum()
          self.assertEqual(model1_output, model2_output)
  
imports: import numpy
  import paddle
  import paddle.nn
  import parl
  import unittest
  from copy import deepcopy
  from parl.core.paddle.model import Model
label_desc: Use image node_id 10 for calling the ModelBaseTest obj's underlying member method code with example usage: obj.test_set_weights_between_different_models() without return types