code: def test_sync_weights_with_different_decay(self):
      decay_list = [0.0, 0.47, 0.9, 1.0]
      for decay in decay_list:
          updated_parameters = self._numpy_update(
              self.target_model, decay
          )
          (
              target_model_fc1_w,
              target_model_fc1_b,
              target_model_fc2_w,
              target_model_fc2_b,
              target_model_fc3_w,
              target_model_fc3_b,
          ) = (
              updated_parameters["fc1.weight"],
              updated_parameters["fc1.bias"],
              updated_parameters["fc2.weight"],
              updated_parameters["fc2.bias"],
              updated_parameters["fc3.weight"],
              updated_parameters["fc3.bias"],
          )
  
          self.model.sync_weights_to(self.target_model, decay)
          N = 10
          random_obs = np.random.randn(N, 4).astype(np.float32)
          for i in range(N):
              obs = random_obs[i]
              real_target_outputs = (
                  self.target_model.predict(paddle.to_tensor(obs))
                  .numpy()
                  .sum()
              )
              out_np = (
                  np.dot(obs, target_model_fc1_w) + target_model_fc1_b
              )
              out_np = (
                  np.dot(out_np, target_model_fc2_w)
                  + target_model_fc2_b
              )
              out_np = (
                  np.dot(out_np, target_model_fc3_w)
                  + target_model_fc3_b
              )
              out_np = out_np.sum()
  
              self.assertLess(
                  float(np.abs(real_target_outputs - out_np)), 1e-5
              )
  
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 6 for calling the ModelBaseTest obj's underlying member method code with example usage: obj.test_sync_weights_with_different_decay() without return types