fix: avoid closures in batched_jacobian

Author: avik-pal

ext/LuxEnzymeExt/batched_autodiff.jl

@@ -1,11 +1,11 @@
-function Lux.AutoDiffInternalImpl.batched_jacobian_impl(
-        f::F, ad::AutoEnzyme, x::AbstractArray) where {F}
+function Lux.AutoDiffInternalImpl.batched_jacobian_internal(
+        f::F, ad::AutoEnzyme, x::AbstractArray, args...) where {F}
     backend = normalize_backend(True(), ad)
-    return batched_enzyme_jacobian_impl(f, backend, ADTypes.mode(backend), x)
+    return batched_enzyme_jacobian_impl(f, backend, ADTypes.mode(backend), x, args...)
 end
 
 function batched_enzyme_jacobian_impl(
-        f_orig::G, ad::AutoEnzyme, ::ForwardMode, x::AbstractArray) where {G}
+        f_orig::G, ad::AutoEnzyme, ::ForwardMode, x::AbstractArray, args...) where {G}
     # We need to run the function once to get the output type. Can we use ForwardWithPrimal?
     y = f_orig(x)
     f = annotate_function(ad, f_orig)
@@ -26,7 +26,8 @@ function batched_enzyme_jacobian_impl(
     for i in 1:chunk_size:(length(x) ÷ B)
         idxs = i:min(i + chunk_size - 1, length(x) ÷ B)
         partials′ = make_onehot!(partials, idxs)
-        J_partials = only(Enzyme.autodiff(ad.mode, f, BatchDuplicated(x, partials′)))
+        J_partials = only(Enzyme.autodiff(
+            ad.mode, f, BatchDuplicated(x, partials′), Const.(args)...))
         for (idx, J_partial) in zip(idxs, J_partials)
             copyto!(view(J, :, idx, :), reshape(J_partial, :, B))
         end
@@ -36,7 +37,7 @@ function batched_enzyme_jacobian_impl(
 end
 
 function batched_enzyme_jacobian_impl(
-        f_orig::G, ad::AutoEnzyme, ::ReverseMode, x::AbstractArray) where {G}
+        f_orig::G, ad::AutoEnzyme, ::ReverseMode, x::AbstractArray, args...) where {G}
     # We need to run the function once to get the output type. Can we use ReverseWithPrimal?
     y = f_orig(x)
 
@@ -60,7 +61,8 @@ function batched_enzyme_jacobian_impl(
         partials′ = make_onehot!(partials, idxs)
         J_partials′ = make_zero!(J_partials, idxs)
         Enzyme.autodiff(
-            ad.mode, fn, BatchDuplicated(y, partials′), BatchDuplicated(x, J_partials′)
+            ad.mode, fn, BatchDuplicated(y, partials′),
+            BatchDuplicated(x, J_partials′), Const.(args)...
         )
         for (idx, J_partial) in zip(idxs, J_partials)
             copyto!(view(J, idx, :, :), reshape(J_partial, :, B))

src/autodiff/nested_autodiff.jl

@@ -1,10 +1,10 @@
 ## Written like this to avoid dynamic dispatch from Zygote
 # Input Gradient / Jacobian
 function rewrite_autodiff_call(f::ComposedFunction{F, <:StatefulLuxLayer}) where {F}
-    (f, f.inner.ps)
+    return f, f.inner.ps
 end
 function rewrite_autodiff_call(f::ComposedFunction{<:StatefulLuxLayer, F}) where {F}
-    (@closure((x, ps)->f.outer(f.inner(x), ps)), f.outer.ps)
+    return @closure((x, ps)->f.outer(f.inner(x), ps)), f.outer.ps
 end
 rewrite_autodiff_call(f::StatefulLuxLayer) = f, f.ps
 
@@ -22,10 +22,12 @@ function rewrite_autodiff_call(f::Base.Fix1{<:StatefulLuxLayer})
 end
 
 ## Break ambiguity
-for op in [ComposedFunction{<:StatefulLuxLayer, <:StatefulLuxLayer},
+for op in [
+    ComposedFunction{<:StatefulLuxLayer, <:StatefulLuxLayer},
     ComposedFunction{<:Base.Fix1{<:StatefulLuxLayer}, <:StatefulLuxLayer},
     ComposedFunction{<:StatefulLuxLayer, <:Base.Fix1{<:StatefulLuxLayer}},
-    ComposedFunction{<:Base.Fix1{<:StatefulLuxLayer}, <:Base.Fix1{<:StatefulLuxLayer}}]
+    ComposedFunction{<:Base.Fix1{<:StatefulLuxLayer}, <:Base.Fix1{<:StatefulLuxLayer}}
+]
     @eval function rewrite_autodiff_call(::$op)
         error("Cannot rewrite ComposedFunction with StatefulLuxLayer as inner and outer \
                layers")