How to prevent tensorflow from allocating the totality of a GPU memory?

Question

I work in an environment in which computational resources are shared, i.e., we have a few server machines equipped with a few Nvidia Titan X GPUs each.

For small to m

Answer 1

For Tensorflow 2.0 this this solution worked for me. (TF-GPU 2.0, Windows 10, GeForce RTX 2070)

physical_devices = tf.config.experimental.list_physical_devices('GPU')
assert len(physical_devices) > 0, "Not enough GPU hardware devices available"
tf.config.experimental.set_memory_growth(physical_devices[0], True)