Avoid batch size of 0 for empty inputs

[penelopeysm]

I ran into #802 again while refactoring some tests on Bijectors.jl, so this is a patch that lets forward-mode Enzyme work with empty inputs.

[gdalle]

I gave it a try too and it's a bit harder than it looks to make this work consistently. First, there are unavoidable discrepancies across backends:

• ForwardDiff can deal with zero chunk sizes, in fact it chooses them voluntarily with ForwardDiff.pickchunksize(0).
• Enzyme cannot deal with zero chunk sizes, it will error here.
• Other backends must have a default chunk size of 1, we cannot use max(1, length(x)) or it becomes type-unstable (see here).

This suggests we need to handle batch sizes of 0 while also setting a minimum of 1 when we can.
Second, there are some difficulties related to the DI operators themselves:

• For wrong-mode pushforwards and pullbacks, we propagate basis vectors, which error when empty (e.g. here). This is solvable.
• For Jacobians and Hessians, we precompute a set of basis vectors and perform preparation on the first one, which may not exist when the vector is empty (e.g. here). This is solvable.
• For Jacobians and Hessians, mapreduce(hcat, collection) errors when the collection is empty (e.g. here). I'm not sure how to solve that one.

[gdalle]

To give you an example of the kind of changes necessary, you can take a look at this commit. I'm not sure supporting empty arrays is worth it, especially if support is always gonna be divergent across backends as you noted in #802