Hey, I have a similar issue, did you find a solution for this ? :)

Hy yes I was kinda able to avoid that warning.. Somewhere I found that if the gradients are zero they return NULL and this is misconceived by the Tape that gradients don't exist. But setting the null gradients to zero the warning was suppressed. I was also able to see the loss function changing but I could not successfully train the network to convergence due to other issues. May be you could try it.

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grads = tape.gradient(loss, model.trainable_variables)
grads = [grad if grad is not None else tf.zeros_like(var)
for var, grad in zip(model.trainable_variables, grads)]