Re: [eigen] overriding scalar_X_op for auto-dif?

[Bob Carpenter <carp@xxxxxxxxxxx>]

I'm glad to hear that a solution is possible.

Is there any way I could help?

It's important to us because it's holding up
the efficient use of matrices in multivariate
distributions like the normal, and we do a lot
of hierarchical regression modeling.

We can code around this by promoting everything to
an auto-dif variable, but it's hugely wasteful
in both time and space.  Eventually, we plan to
override the matrix arithmetic ops for auto-dif
to save even more space and time, but we want
to get everything working before worrying about
further optimization.

- Bob

On 5/19/11 5:42 PM, Gael Guennebaud wrote:
> ok, actually it seems this is something we have to solve in Eigen
> itself. Nothing difficult though.
>
> gael
>
> On Thu, May 19, 2011 at 10:48 PM, Bob Carpenter<carp@xxxxxxxxxxx>  wrote:
> > Thanks so much for getting back to me so quickly
> > on this.  I tried overloading scalar_product_traits
> > and NumTraits, but still no luck getting multiplication
> > of an auto-dif matrix times a double matrix to compile.
> >
> > I'd MUCH rather just overload the basic ops for now.
> > Later,  I can optimize with expressions and hand-coded
> > gradients for some cases without disturbing the API.
> > I'm afraid your auto-dif scalar code's a bit beyond
> > my current understanding of Eigen and C++ templates.
> >
> > I've attached a small tar.gz ball.  Check out the
> > README.txt, which shows how to run our reverse-mode
> > auto-dif, has an example using Eigen auto-dif var
> > multiplication which works fine, and then a demo that
> > doesn't compile using double * auto-dif variables.
> > I include the specialization of scalar_product_traits
> > you suggested (with both orders), as well as NumTraits,
> > but still no luck.
> >
> > - Bob Carpenter
> >   Columbia Uni, Dept of Statistics