Is there any method to support Jacobian-matrix products? For example, let’s say I have a scalar loss and parameters of dimension p. My “v” vector in JVP is a matrix of dimension “batch_size x p”. I want to compute the JVP for each batch so that the output is “batch_size x 1”. I was wondering If there any ways to do this without using a loop.