code: def optimizer(self):
      lr = tf.get_variable(
          "learning_rate", initializer=1e-3, trainable=False
      )
      tf.summary.scalar("learning_rate-summary", lr)
      opt = tf.train.RMSPropOptimizer(
          lr, decay=0.95, momentum=0.95, epsilon=1e-2
      )
      return optimizer.apply_grad_processors(
          opt, [gradproc.SummaryGradient()]
      )
  
file_path: tensorpack/examples/DeepQNetwork/DQNModel.py
imports: import abc
  from tensorpack import ModelDesc
  from tensorpack.compat import tfv1
  from tensorpack.tfutils import gradproc, optimizer, summary, varreplace
  from tensorpack.tfutils.scope_utils import auto_reuse_variable_scope
  from tensorpack.utils import logger
label_desc: Use image node_id 6 for calling the Model obj's underlying member method code with example usage: obj.optimizer() and returns: optimizer