Don't support Batched TR for correctness reasons

Author: avik-pal

src/nlsolve/dfsane.jl

@@ -102,15 +102,15 @@ function SciMLBase.__solve(prob::NonlinearProblem, alg::SimpleDFSane, args...;
         fx_norm_new = NONLINEARSOLVE_DEFAULT_NORM(fx)^nexp
 
         while k < maxiters
-            fx_norm_new ≤ (f_bar + η - γ * α_p^2 * fx_norm) && break
+            Bool(fx_norm_new ≤ (f_bar + η - γ * α_p^2 * fx_norm)) && break
 
             α_p = α_p^2 * fx_norm / (fx_norm_new + (T(2) * α_p - T(1)) * fx_norm)
             @bb @. x -= α_m * d
 
             fx = __eval_f(prob, fx, x)
             fx_norm_new = NONLINEARSOLVE_DEFAULT_NORM(fx)^nexp
 
-            fx_norm_new ≤ (f_bar + η - γ * α_m^2 * fx_norm) && break
+            Bool(fx_norm_new ≤ (f_bar + η - γ * α_m^2 * fx_norm)) && break
 
             α_tm = α_m^2 * fx_norm / (fx_norm_new + (T(2) * α_m - T(1)) * fx_norm)
             α_p = clamp(α_p, τ_min * α_p, τ_max * α_p)

src/nlsolve/trustRegion.jl

@@ -99,7 +99,7 @@ function SciMLBase.__solve(prob::NonlinearProblem, alg::SimpleTrustRegion, args.
         r = (fₖ₊₁ - fₖ) / (dot(δ, g) + dot(δ, Hδ) / T(2))
 
         # Update the trust region radius.
-        if Bool(r ≥ η₂)
+        if r ≥ η₂
             shrink_counter = 0
         else
             Δ = t₁ * Δ
@@ -108,7 +108,7 @@ function SciMLBase.__solve(prob::NonlinearProblem, alg::SimpleTrustRegion, args.
                 retcode = ReturnCode.ConvergenceFailure)
         end
 
-        if Bool(r ≥ η₁)
+        if r ≥ η₁
             # Termination Checks
             tc_sol = check_termination(tc_cache, fx, x, xo, prob, alg)
             tc_sol !== nothing && return tc_sol
@@ -137,14 +137,14 @@ function dogleg_method!!(cache, J, f, g, Δ)
     @bb δN .= _restructure(δN, J \ _vec(f))
     @bb δN .*= -1
     # Test if the full step is within the trust region.
-    Bool(norm(δN) ≤ Δ) && return δN
+    (norm(δN) ≤ Δ) && return δN
 
     # Calcualte Cauchy point, optimum along the steepest descent direction.
     @bb δsd .= g
     @bb @. δsd *= -1
     norm_δsd = norm(δsd)
 
-    if Bool(norm_δsd ≥ Δ)
+    if (norm_δsd ≥ Δ)
         @bb @. δsd *= Δ / norm_δsd
         return δsd
     end