code: def __init__(self):
      # Almost the same as above, but now returns the placeholders and
      # gradient.
      with tf.Graph().as_default():
          loss, init, x_data, y_data = make_linear_network()
          sess = tf.Session()
          variables = ray.experimental.tf_utils.TensorFlowVariables(
              loss, sess
          )
          optimizer = tf.train.GradientDescentOptimizer(0.9)
          grads = optimizer.compute_gradients(loss)
          train = optimizer.apply_gradients(grads)
      self.values = [
          loss,
          variables,
          init,
          sess,
          grads,
          train,
          [x_data, y_data],
      ]
      sess.run(init)
  
imports: from numpy.testing import assert_almost_equal
  import ray
  import ray.experimental.tf_utils
  from ray.rllib.utils.framework import try_import_tf
label_desc: Use image node_id 1 to create a new TrainActor object  with example: obj = TrainActor()