Hi -

Dumb question! May be I haven’t encountered it in the docs.

Suppose due to transformation and some bad functional form, I’m not able to build an expression graph in the forward pass. However, I’m able to do some analytic calculations and the gradient for the ill-formed loss function is tractable.

Is there a way to substitute `grad`

or gradients WRT a loss function, with something I’ve implemented, for example, using finite differencing?

I’m sure my deep learning understanding is rather poor.

Thanks,

Andre