How to use GPU Memory Oversubscription in TensorFlow 2 (Keras API)?

General Discussion
,
#1

Hi, guys, I’m using Keras to train my model, as model itself is large and GPU only gets 16 GiB.

How can I oversubscribe GPU memory in Keras?
I tried the following but it doesn’t work.

for physical_gpu in physical_gpus:
    print("Memory growth for {} before: {}".format(physical_gpu,
                                                   tf.config.experimental.get_memory_growth(physical_gpu)))
    tf.config.experimental.set_memory_growth(physical_gpu, False)
    print("Memory growth for {} after: {}".format(physical_gpu,
                                                  tf.config.experimental.get_memory_growth(physical_gpu)))
    print("Logical device configuration for {} before: {}".format(
        physical_gpu, tf.config.get_logical_device_configuration(physical_gpu))
    )
    tf.config.set_logical_device_configuration(
        physical_gpu, [tf.config.LogicalDeviceConfiguration(memory_limit=30*1024)]
    )
    print("Logical device configuration for {} after: {}".format(
        physical_gpu, tf.config.get_logical_device_configuration(physical_gpu))
    )