diff --git a/src/learn/learn.cpp b/src/learn/learn.cpp
index af867d42..dd893d9d 100644
--- a/src/learn/learn.cpp
+++ b/src/learn/learn.cpp
@@ -197,6 +197,29 @@ namespace Learner
         return lambda;
     }
 
+    template <typename ShallowT, typename TeacherT, typename ResultT, typename LambdaT>
+    static auto& cross_entropy_(
+        ShallowT& q_,
+        TeacherT& p_,
+        ResultT& t_,
+        LambdaT& lambda_
+    )
+    {
+        using namespace Learner::Autograd::UnivariateStatic;
+
+        constexpr double epsilon = 1e-12;
+
+        static thread_local auto teacher_entropy_ = -(p_ * log(p_ + epsilon) + (1.0 - p_) * log(1.0 - p_ + epsilon));
+        static thread_local auto outcome_entropy_ = -(t_ * log(t_ + epsilon) + (1.0 - t_) * log(1.0 - t_ + epsilon));
+        static thread_local auto teacher_loss_ = -(p_ * log(q_) + (1.0 - p_) * log(1.0 - q_));
+        static thread_local auto outcome_loss_ = -(t_ * log(q_) + (1.0 - t_) * log(1.0 - q_));
+        static thread_local auto result_ = lambda_ * teacher_loss_ + (1.0 - lambda_) * outcome_loss_;
+        static thread_local auto entropy_ = lambda_ * teacher_entropy_ + (1.0 - lambda_) * outcome_entropy_;
+        static thread_local auto loss_ = result_ - entropy_;
+
+        return loss_;
+    }
+
     static ValueWithGrad<double> get_loss(Value shallow, Value teacher_signal, int result, int ply)
     {
         using namespace Learner::Autograd::UnivariateStatic;
@@ -215,19 +238,11 @@ namespace Learner
         auto loss_ = pow(q_ - p_, 2.0) * (1.0 / (2400.0 * 2.0 * 600.0));
         */
 
-        constexpr double epsilon = 1e-12;
-
         static thread_local auto q_ = sigmoid(VariableParameter<double, 0>{} * ConstantParameter<double, 4>{});
         static thread_local auto p_ = sigmoid(ConstantParameter<double, 1>{} * ConstantParameter<double, 4>{});
         static thread_local auto t_ = (ConstantParameter<double, 2>{} + 1.0) * 0.5;
         static thread_local auto lambda_ = ConstantParameter<double, 3>{};
-        static thread_local auto teacher_entropy_ = -(p_ * log(p_ + epsilon) + (1.0 - p_) * log(1.0 - p_ + epsilon));
-        static thread_local auto outcome_entropy_ = -(t_ * log(t_ + epsilon) + (1.0 - t_) * log(1.0 - t_ + epsilon));
-        static thread_local auto teacher_loss_ = -(p_ * log(q_) + (1.0 - p_) * log(1.0 - q_));
-        static thread_local auto outcome_loss_ = -(t_ * log(q_) + (1.0 - t_) * log(1.0 - q_));
-        static thread_local auto result_ = lambda_ * teacher_loss_ + (1.0 - lambda_) * outcome_loss_;
-        static thread_local auto entropy_ = lambda_ * teacher_entropy_ + (1.0 - lambda_) * outcome_entropy_;
-        static thread_local auto loss_ = result_ - entropy_;
+        static thread_local auto loss_ = cross_entropy_(q_, p_, t_, lambda_);
 
         auto args = std::tuple(
             (double)shallow,