Update

Author: odow

src/Nonlinear/ReverseAD/forward_over_reverse.jl

@@ -116,7 +116,6 @@ end
 
 function _hessian_slice_inner(d, ex, ::Val{CHUNK}) where {CHUNK}
     T = ForwardDiff.Partials{CHUNK,Float64}  # This is our element type.
-    input_ϵ = _reinterpret_unsafe(T, d.input_ϵ)
     fill!(d.output_ϵ, 0.0)
     output_ϵ = _reinterpret_unsafe(T, d.output_ϵ)
     subexpr_forward_values_ϵ =
@@ -168,11 +167,7 @@ end
     _forward_eval_ϵ(
         d::NLPEvaluator,
         ex::Union{_FunctionStorage,_SubexpressionStorage},
-        storage_ϵ::AbstractVector{ForwardDiff.Partials{N,T}},
         partials_storage_ϵ::AbstractVector{ForwardDiff.Partials{N,T}},
-        x_values_ϵ,
-        subexpression_values_ϵ,
-        user_operators::Nonlinear.OperatorRegistry,
     ) where {N,T}
 
 Evaluate the directional derivatives of the expression tree in `ex`.
@@ -186,14 +181,12 @@ This assumes that `_reverse_model(d, x)` has already been called.
 function _forward_eval_ϵ(
     d::NLPEvaluator,
     ex::Union{_FunctionStorage,_SubexpressionStorage},
-    partials_storage_ϵ::AbstractVector{ForwardDiff.Partials{N,T}},
-) where {N,T}
-    P = ForwardDiff.Partials{N,T}
+    partials_storage_ϵ::AbstractVector{P}
+) where {N,T,P<:ForwardDiff.Partials{N,T}}
     storage_ϵ = _reinterpret_unsafe(P, d.storage_ϵ)
     x_values_ϵ = reinterpret(P, d.input_ϵ)
     subexpression_values_ϵ =
         _reinterpret_unsafe(P, d.subexpression_forward_values_ϵ)
-    user_operators = d.data.operators
     @assert length(storage_ϵ) >= length(ex.nodes)
     @assert length(partials_storage_ϵ) >= length(ex.nodes)
     zero_ϵ = zero(P)
@@ -329,8 +322,8 @@ function _forward_eval_ϵ(
                         n_children,
                     )
                     has_hessian = Nonlinear.eval_multivariate_hessian(
-                        user_operators,
-                        user_operators.multivariate_operators[node.index],
+                        d.data.operators,
+                        d.data.operators.multivariate_operators[node.index],
                         H,
                         f_input,
                     )
@@ -356,7 +349,7 @@ function _forward_eval_ϵ(
             elseif node.type == Nonlinear.NODE_CALL_UNIVARIATE
                 @inbounds child_idx = children_arr[ex.adj.colptr[k]]
                 f′′ = Nonlinear.eval_univariate_hessian(
-                    user_operators,
+                    d.data.operators,
                     node.index,
                     ex.forward_storage[child_idx],
                 )