Forward over reverse drops custom rule if corresponding function is inlined

[danielwe]

My custom reverse rule works as expected in 1st order reverse mode, but I need to give the corresponding function @noinline tag for it to be picked up in 2nd order forward over reverse. In the MWE below I've introduced a bug in the rule such that both the gradient and the hv product should be different between g and g_custom; gradients are always different, but hv products are only different when I add @noinline.

using Enzyme

#=@noinline=# f(x) = sum(abs2, x)
#=@noinline=# f_custom(x) = sum(abs2, x)

g(x) = cos(f(x))
g_custom(x) = cos(f_custom(x))

function dg_deferred!(dx, x)
    make_zero!(dx)
    autodiff_deferred(Reverse, g, Active, Duplicated(x, dx))
    return nothing
end

function dg_custom_deferred!(dx, x)
    make_zero!(dx)
    autodiff_deferred(Reverse, g_custom, Active, Duplicated(x, dx))
    return nothing
end

function EnzymeRules.augmented_primal(
    config::EnzymeRules.Config, f::Const{typeof(f_custom)}, ::Type{<:Active}, x::Duplicated
)
    tape = EnzymeRules.overwritten(config)[2] ? copy(x.val) : nothing
    primal = EnzymeRules.needs_primal(config) ? f.val(x.val) : nothing
    return EnzymeRules.AugmentedReturn(primal, nothing#=shadow=#, tape)
end

function EnzymeRules.reverse(
    config::EnzymeRules.Config,
    ::Const{typeof(f_custom)},
    dret::Active,
    tape,
    x::Duplicated,
)
    xval = EnzymeRules.overwritten(config)[2] ? tape : x.val
    x.dval .= (2dret.val) .* xval
    x.dval .^= 2  # Deliberate bug as signature of custom rule 🐛
    return (nothing,)
end

x = [2.0]
dx, dx_custom = make_zero(x), make_zero(x)

v = first(onehot(x))
hv, hv_custom = make_zero(v), make_zero(v)

# gradients
dg_deferred!(dx, x)
@show dx

dg_custom_deferred!(dx_custom, x)
@show dx_custom

# hvps
autodiff(Forward, dg_deferred!, Const, Duplicated(dx, hv), Duplicated(x, v))
@show hv

autodiff(
    Forward,
    dg_custom_deferred!,
    Const,
    Duplicated(dx_custom, hv_custom),
    Duplicated(x, v),
)
@show hv_custom

Output as written: different gradients, equal hv products.

dx = [3.027209981231713]
dx_custom = [9.164000270468907]
hv = [11.971902924433648]
hv_custom = [11.971902924433648]

Output with @noinline: both gradients and hv products different.

dx = [3.027209981231713]
dx_custom = [9.164000270468907]
hv = [11.971902924433648]
hv_custom = [72.48292805436535]