code: def testDense(self):
      parameters = [tf.Variable([1.0, 2.0]), tf.Variable([3.0, 4.0])]
      updates = [tf.constant([5.0, 5.0]), tf.constant([3.0, 3.0])]
      optimizer = self.make_optimizer(learning_rate=0.1)
      # Step 1 of RMSProp
      optimizer.apply(updates, parameters)
      self.assertAllClose(
          [[0.683772, 1.683772], [2.683772, 3.683772]],
          [x.numpy() for x in parameters],
      )
      # Step 2 of RMSProp
      optimizer.apply(updates, parameters)
      self.assertAllClose(
          [[0.454357, 1.454357], [2.454357, 3.454357]],
          [x.numpy() for x in parameters],
      )
      # Step 3 of RMSProp
      optimizer.apply(updates, parameters)
      self.assertAllClose(
          [[0.262262, 1.262262], [2.262262, 3.262262]],
          [x.numpy() for x in parameters],
      )
  
imports: from sonnet.src import test_utils
  from sonnet.src.optimizers import optimizer_tests
  from sonnet.src.optimizers import rmsprop
  import tensorflow
label_desc: Use image node_id 2 for calling the RMSPropTest obj's underlying member method code with example usage: obj.testDense() without return types