@tom The reason I’m doing this is that the forward pass takes a parametrized distribution as input and estimates a property of the distribution by sampling from it. This sampling means I can’t backpropagate directly to the parameters of the distribution. However, I know another estimator for the gradient of the property with respect to the distribution, and this is what I use in the backward pass.