fixup SemEnsemble: SemML loss

Author: Alexey Stukalov

src/loss/ML/ML.jl

@@ -92,20 +92,20 @@ function evaluate!(
     objective,
     gradient,
     hessian,
-    ml::SemML{<:Any, <:SemImpliedSymbolic},
+    loss::SemML{<:Any, <:SemImpliedSymbolic},
     par,
 )
-    implied = SEM.implied(ml)
+    implied = SEM.implied(loss)
 
     if !isnothing(hessian)
         (MeanStruct(implied) === HasMeanStruct) &&
             throw(DomainError(H, "hessian of ML + meanstructure is not available"))
     end
 
     Σ = implied.Σ
-    Σₒ = obs_cov(observed(model))
-    Σ⁻¹Σₒ = ml.Σ⁻¹Σₒ
-    Σ⁻¹ = ml.Σ⁻¹
+    Σₒ = obs_cov(observed(loss))
+    Σ⁻¹Σₒ = loss.Σ⁻¹Σₒ
+    Σ⁻¹ = loss.Σ⁻¹
 
     copyto!(Σ⁻¹, Σ)
     Σ_chol = cholesky!(Symmetric(Σ⁻¹); check = false)
@@ -123,7 +123,7 @@ function evaluate!(
 
     if MeanStruct(implied) === HasMeanStruct
         μ = implied.μ
-        μₒ = obs_mean(observed(ml))
+        μₒ = obs_mean(observed(loss))
         μ₋ = μₒ - μ
 
         isnothing(objective) || (objective += dot(μ₋, Σ⁻¹, μ₋))
@@ -142,7 +142,7 @@ function evaluate!(
             mul!(gradient, ∇Σ', J')
         end
         if !isnothing(hessian)
-            if HessianEval(ml) === ApproxHessian
+            if HessianEval(loss) === ApproxHessian
                 mul!(hessian, ∇Σ' * kron(Σ⁻¹, Σ⁻¹), ∇Σ, 2, 0)
             else
                 ∇²Σ = implied.∇²Σ