I’m wondering what’s the Tensorflow way of storing and performing Tensor manipulation (i.e. Tensor multiplication, apply_gradient) of trainable weights in a custom layer that could potentially be sparse based on user specification. I’ve looked into
and
but I’m not sure if it’s possible to apply these as ways to store and update trainable weights.