Method optimizer

examples/A3C-Gym/train-atari.py:133–140

(self)

        return cost

    def optimizer(self):
        lr = tf.get_variable('learning_rate', initializer=0.001, trainable=False)
        opt = tf.train.AdamOptimizer(lr, epsilon=1e-3)

        gradprocs = [MapGradient(lambda grad: tf.clip_by_norm(grad, 0.1 * tf.cast(tf.size(grad), tf.float32))),
                     SummaryGradient()]
        opt = optimizer.apply_grad_processors(opt, gradprocs)
        return opt


class MySimulatorMaster(SimulatorMaster, Callback):