diff --git a/src/learn/learn.cpp b/src/learn/learn.cpp
index 450a80c6..449542a7 100644
--- a/src/learn/learn.cpp
+++ b/src/learn/learn.cpp
@@ -310,7 +310,8 @@ namespace Learner
         return perf;
     }
 
-    [[maybe_unused]] static ValueWithGrad<double> get_loss_noob(Value shallow, Value teacher_signal, int result, int /* ply */)
+    [[maybe_unused]] static ValueWithGrad<double> get_loss_noob(
+        Value shallow, Value teacher_signal, int result, int /* ply */)
     {
         using namespace Learner::Autograd::UnivariateStatic;
 
@@ -328,7 +329,7 @@ namespace Learner
         return loss_.eval(args);
     }
 
-    static ValueWithGrad<double> get_loss_cross_entropy(Value shallow, Value teacher_signal, int result, int /* ply */)
+    static auto& get_loss_cross_entropy_()
     {
         using namespace Learner::Autograd::UnivariateStatic;
 
@@ -338,18 +339,45 @@ namespace Learner
         static thread_local auto lambda_ = ConstantParameter<double, 3>{};
         static thread_local auto& loss_ = cross_entropy_(q_, p_, t_, lambda_);
 
-        auto args = std::tuple(
+        return loss_;
+    }
+
+    static auto get_loss_cross_entropy_args(
+        Value shallow, Value teacher_signal, int result)
+    {
+        return std::tuple(
             (double)shallow,
             (double)teacher_signal,
             (double)result,
             calculate_lambda(teacher_signal)
         );
+    }
+
+    static ValueWithGrad<double> get_loss_cross_entropy(
+        Value shallow, Value teacher_signal, int result, int /* ply */)
+    {
+        using namespace Learner::Autograd::UnivariateStatic;
+
+        static thread_local auto& loss_ = get_loss_cross_entropy_();
+
+        auto args = get_loss_cross_entropy_args(shallow, teacher_signal, result);
 
         return loss_.eval(args);
     }
 
-    static ValueWithGrad<double> get_loss_cross_entropy_use_wdl(
-        Value shallow, Value teacher_signal, int result, int ply)
+    static ValueWithGrad<double> get_loss_cross_entropy_no_grad(
+        Value shallow, Value teacher_signal, int result, int /* ply */)
+    {
+        using namespace Learner::Autograd::UnivariateStatic;
+
+        static thread_local auto& loss_ = get_loss_cross_entropy_();
+
+        auto args = get_loss_cross_entropy_args(shallow, teacher_signal, result);
+
+        return { loss_.value(args), 0.0 };
+    }
+
+    static auto& get_loss_cross_entropy_use_wdl_()
     {
         using namespace Learner::Autograd::UnivariateStatic;
 
@@ -364,7 +392,13 @@ namespace Learner
         static thread_local auto lambda_ = ConstantParameter<double, 3>{};
         static thread_local auto& loss_ = cross_entropy_(q_, p_, t_, lambda_);
 
-        auto args = std::tuple(
+        return loss_;
+    }
+
+    static auto get_loss_cross_entropy_use_wdl_args(
+        Value shallow, Value teacher_signal, int result, int ply)
+    {
+        return std::tuple(
             (double)shallow,
             // This is required because otherwise MSVC crashes :(
             expected_perf_use_wdl(scale_score(teacher_signal), ply),
@@ -372,10 +406,32 @@ namespace Learner
             calculate_lambda(teacher_signal),
             (double)std::min(240, ply)
         );
+    }
+
+    static ValueWithGrad<double> get_loss_cross_entropy_use_wdl(
+        Value shallow, Value teacher_signal, int result, int ply)
+    {
+        using namespace Learner::Autograd::UnivariateStatic;
+
+        static thread_local auto& loss_ = get_loss_cross_entropy_use_wdl_();
+
+        auto args = get_loss_cross_entropy_use_wdl_args(shallow, teacher_signal, result, ply);
 
         return loss_.eval(args);
     }
 
+    static ValueWithGrad<double> get_loss_cross_entropy_use_wdl_no_grad(
+        Value shallow, Value teacher_signal, int result, int ply)
+    {
+        using namespace Learner::Autograd::UnivariateStatic;
+
+        static thread_local auto& loss_ = get_loss_cross_entropy_use_wdl_();
+
+        auto args = get_loss_cross_entropy_use_wdl_args(shallow, teacher_signal, result, ply);
+
+        return { loss_.value(args), 0.0 };
+    }
+
     static auto get_loss(Value shallow, Value teacher_signal, int result, int ply)
     {
         using namespace Learner::Autograd::UnivariateStatic;
@@ -390,7 +446,21 @@ namespace Learner
         }
     }
 
-    static auto get_loss(
+    static auto get_loss_no_grad(Value shallow, Value teacher_signal, int result, int ply)
+    {
+        using namespace Learner::Autograd::UnivariateStatic;
+
+        if (use_wdl)
+        {
+            return get_loss_cross_entropy_use_wdl_no_grad(shallow, teacher_signal, result, ply);
+        }
+        else
+        {
+            return get_loss_cross_entropy_no_grad(shallow, teacher_signal, result, ply);
+        }
+    }
+
+    [[maybe_unused]] static auto get_loss(
         Value teacher_signal,
         Value shallow,
         const PackedSfenValue& psv)
@@ -398,6 +468,14 @@ namespace Learner
         return get_loss(shallow, teacher_signal, psv.game_result, psv.gamePly);
     }
 
+    static auto get_loss_no_grad(
+        Value teacher_signal,
+        Value shallow,
+        const PackedSfenValue& psv)
+    {
+        return get_loss_no_grad(shallow, teacher_signal, psv.game_result, psv.gamePly);
+    }
+
     // Class to generate sfen with multiple threads
     struct LearnerThink
     {
@@ -828,11 +906,11 @@ namespace Learner
 
         if (psv.size() && test_loss_sum.count() > 0)
         {
-            test_loss_sum.print("val", out);
+            test_loss_sum.print_only_loss("val", out);
 
             if (learn_loss_sum.count() > 0)
             {
-                learn_loss_sum.print("train", out);
+                learn_loss_sum.print_with_grad("train", out);
             }
 
             out << "  - norm = " << sum_norm << endl;
@@ -880,7 +958,7 @@ namespace Learner
             // Evaluation value of deep search
             const auto deep_value = (Value)ps.score;
 
-            const auto loss = get_loss(
+            const auto loss = get_loss_no_grad(
                 deep_value,
                 shallow_value,
                 ps);
diff --git a/src/learn/learn.h b/src/learn/learn.h
index 552096b2..842ffad0 100644
--- a/src/learn/learn.h
+++ b/src/learn/learn.h
@@ -126,12 +126,18 @@ namespace Learner
         }
 
         template <typename StreamT>
-        void print(const std::string& prefix, StreamT& s) const
+        void print_with_grad(const std::string& prefix, StreamT& s) const
         {
             s << "  - " << prefix << "_loss       = " << m_loss.value / (double)m_count << std::endl;
             s << "  - " << prefix << "_grad_norm  = " << m_loss.grad / (double)m_count << std::endl;
         }
 
+        template <typename StreamT>
+        void print_only_loss(const std::string& prefix, StreamT& s) const
+        {
+            s << "  - " << prefix << "_loss       = " << m_loss.value / (double)m_count << std::endl;
+        }
+
     private:
         ValueWithGrad<double> m_loss{ 0.0, 0.0 };
         uint64_t m_count{0};