Gradient with Zygote and Identity about tullio.jl HOT 2 CLOSED

Here's what's going on:

julia> @tullio res = identity(arr[i, j]) verbose=true 
┌ Warning: Symbolic gradient failed
│   err = no diffrule found for function identity(_).
└ @ Tullio ~/.julia/dev/Tullio/src/macro.jl:878
[ Info: left index ranges
┌ Info: reduction index ranges
│   i = Base.OneTo(5)
└   j = Base.OneTo(5)
25.0

That is, the default behaviour is to work out a symbolic gradient of the RHS, using Diffruls.jl. It turns out that nobody wrote a rule for identity, and certainly there will be no rule for foo. The macro sees only the symbol :foo, in general it has to assume that any function called :log behaves like Base.log, etc.

It is also possible to use dual numbers instead, in which case all that matters is that foo only contains operations which ForwardDiff understands:

using ForwardDiff
foo = sqrt
f_foo(arr) = @tullio res = foo(arr[i, j]) grad=Dual
gradient(f_foo, ones(5,5))[1]

from tullio.jl.

Hm, ok.
Yeah, what I wanted to try was to pass a function by reference to Tullio. So foo would have been
a differentiable function.

However, in my special case (similar to the metaprogramming #11 ) I could solve it with $foo where foo was assigned to be foo = :sqrt

Thanks!

from tullio.jl.