def eager_decay_rate():
    """Callable to compute the learning rate."""
    rate_index = tf.reduce_max(tf.where(
        tf.greater_equal(global_step, boundaries),
        list(range(num_boundaries)),
        [0] * num_boundaries))
    return tf.reduce_sum(rates * tf.one_hot(rate_index, depth=num_boundaries),
                         name='learning_rate')
Callable to compute the learning rate.
inference_api/src/main/object_detection/utils/learning_schedules.py