def eager_decay_rate():
    """Callable to compute the learning rate."""
    post_burnin_learning_rate = tf.train.exponential_decay(
        learning_rate_base,
        global_step - burnin_steps,
        learning_rate_decay_steps,
        learning_rate_decay_factor,
        staircase=staircase)
    if callable(post_burnin_learning_rate):
      post_burnin_learning_rate = post_burnin_learning_rate()
    return tf.maximum(tf.where(
        tf.less(tf.cast(global_step, tf.int32), tf.constant(burnin_steps)),
        tf.constant(burnin_learning_rate),
        post_burnin_learning_rate), min_learning_rate, name='learning_rate')
Callable to compute the learning rate.
inference_api/src/main/object_detection/utils/learning_schedules.py