there's a fuzzy boundary between 'embedded dsl' and 'just a library' (similar to the problem of 'what is a framework'), but at the point that a library provides functions you can use to build your computational graph out of, it's clearly not just an automatic differentiation library; it's some kind of computational-graph-composing library which perhaps sports automatic differentiation as one of its features. and what i'm saying is that, if you want to write an automatic differentiation library in most languages, it's basically going to have to be a compiler that statically transforms your algorithm, whether it's a compiler for fortran or for an embedded dsl

this is less true for forward-mode automatic differentiation, which you can do a pretty reasonable job of in python as just a dual-number class which you can pass to many, though not all, ordinary numerical computation functions. unfortunately forward-mode automatic differentiation is unusably slow for gradients with respect to large parameter vectors

It’s a DSL by definition because a function provided by an external library cannot be a language primitive in the host language, or else it wouldn’t need to be an external library! Unless we’re talking about a LISP but we’re not.