Optimize projinv in backward fallback

[juliohm]

The backward fallback relies on projinv with Zygote-based AD. It turns out that Zygote.gradient can detect when a formula doesn't depend on any of the arguments, returning nothing instead of 0.0. We can use this information to reduce the computation in half in the Newton-Rhapson iteration.