Remove threads for now

Author: odow

src/Nonlinear/SymbolicAD/SymbolicAD.jl

@@ -812,7 +812,7 @@ function gradient_and_hessian(
     n = length(x)
     ∇f = Vector{Any}(undef, n)
     H_by_x, ∇²f_by_x = [Tuple{Int,Int}[] for _ in 1:n], [Any[] for _ in 1:n]
-    Threads.@threads for i in eachindex(x)
+    for i in eachindex(x)
         xi = x[i]
         ∇fi = simplify!(derivative(f, xi))
         ∇f[i] = ∇fi
@@ -1437,7 +1437,7 @@ function _evaluate!(model::Evaluator, x)
     if o !== nothing
         _evaluate!(model.dag[o.hash], o, x)
     end
-    Threads.@threads for h in collect(keys(model.constraint_index_by_hash))
+    for h in collect(keys(model.constraint_index_by_hash))
         dag = model.dag[h]
         for i in model.constraint_index_by_hash[h]
             _evaluate!(dag, model.constraints[i], x)
@@ -1461,7 +1461,7 @@ end
 function MOI.eval_objective_gradient(model::Evaluator, ∇f, x)
     _evaluate!(model, x)
     fill!(∇f, 0.0)
-    Threads.@threads for i in eachindex(model.objective.x)
+    for i in eachindex(model.objective.x)
         xi = model.objective.x[i]
         ∇f[xi] = model.objective.result[1+i]
     end
@@ -1470,7 +1470,7 @@ end
 
 function MOI.eval_constraint(model::Evaluator, g, x)
     _evaluate!(model, x)
-    Threads.@threads for i in eachindex(model.constraints)
+    for i in eachindex(model.constraints)
         g[i] = model.constraints[i].result[1]
     end
     return
@@ -1479,7 +1479,7 @@ end
 function MOI.jacobian_structure(model::Evaluator)
     d = last(model.constraints)
     J = Vector{Tuple{Int,Int}}(undef, d.jac_offset + length(d.x))
-    Threads.@threads for i in eachindex(model.constraints)
+    for i in eachindex(model.constraints)
         c = model.constraints[i]
         for (j, xj) in enumerate(c.x)
             J[c.jac_offset+j] = (i, xj)
@@ -1490,7 +1490,7 @@ end
 
 function MOI.eval_constraint_jacobian(model::Evaluator, J, x)
     _evaluate!(model, x)
-    Threads.@threads for c in model.constraints
+    for c in model.constraints
         for j in eachindex(c.x)
             J[c.jac_offset+j] = c.result[1+j]
         end
@@ -1514,7 +1514,7 @@ function MOI.hessian_lagrangian_structure(model::Evaluator)
             H[k] = (o.x[hi], o.x[hj])
         end
     end
-    Threads.@threads for c in model.constraints
+    for c in model.constraints
         for (k, (hi, hj)) in enumerate(model.H[c.hash])
             H[c.hess_offset+k] = (c.x[hi], c.x[hj])
         end
@@ -1531,7 +1531,7 @@ function MOI.eval_hessian_lagrangian(model::Evaluator, H, x, σ, μ)
             H[offset+j] = σ * o.result[j]
         end
     end
-    Threads.@threads for i in eachindex(model.constraints)
+    for i in eachindex(model.constraints)
         c = model.constraints[i]
         # It is important that `offset_c` does not shadow `offset` from the
         # objective block. If we use the same name, Julia creates a Core.Box