I work on a model based on this tutorial:
I want to make this vae an annealed beta-vae, so I have defined a “tf.keras.backend.variable” which is updated every epoch in a custom callback. This variable is then applied as a factor to the latent loss in the train_step function.
My first concern is that if I’m not forcing eager mode, the value of the variable is never updated in the train_step() function.
My second concern is that if I force eager mode in .compile() with run_eagerly=True, the value is now correctly updated in the train_step() function but the impact on runtime is HUGE : it’s twice the time for each epoch.
Do you have any idea of what is going on here ?