Merge branch 'master' into trainer

src/nnue/evaluate_nnue.cpp

@@ -142,7 +142,6 @@ namespace Eval::NNUE {
     if (!Detail::ReadParameters(stream, network)) return false;
     return stream && stream.peek() == std::ios::traits_type::eof();
   }
-
   // write evaluation function parameters
   bool WriteParameters(std::ostream& stream) {
     if (!WriteHeader(stream, kHashValue, GetArchitectureString())) return false;
@@ -150,32 +149,16 @@ namespace Eval::NNUE {
     if (!Detail::WriteParameters(stream, network)) return false;
     return !stream.fail();
   }
-
-  // Proceed with the difference calculation if possible
-  static void UpdateAccumulatorIfPossible(const Position& pos) {
-
-    feature_transformer->UpdateAccumulatorIfPossible(pos);
-  }
-
-  // Calculate the evaluation value
-  static Value ComputeScore(const Position& pos, bool refresh) {
-
-    auto& accumulator = pos.state()->accumulator;
-    if (!refresh && accumulator.computed_score) {
-      return accumulator.score;
-    }
+  // Evaluation function. Perform differential calculation.
+  Value evaluate(const Position& pos) {
 
     alignas(kCacheLineSize) TransformedFeatureType
         transformed_features[FeatureTransformer::kBufferSize];
-    feature_transformer->Transform(pos, transformed_features, refresh);
+    feature_transformer->Transform(pos, transformed_features);
     alignas(kCacheLineSize) char buffer[Network::kBufferSize];
     const auto output = network->Propagate(transformed_features, buffer);
 
-    auto score = static_cast<Value>(output[0] / FV_SCALE);
-
-    accumulator.score = score;
-    accumulator.computed_score = true;
-    return accumulator.score;
+    return static_cast<Value>(output[0] / FV_SCALE);
   }
 
   // Load eval, from a file stream or a memory stream
@@ -191,19 +174,4 @@ namespace Eval::NNUE {
     return ReadParameters(stream);
   }
 
-  // Evaluation function. Perform differential calculation.
-  Value evaluate(const Position& pos) {
-    return ComputeScore(pos, false);
-  }
-
-  // Evaluation function. Perform full calculation.
-  Value compute_eval(const Position& pos) {
-    return ComputeScore(pos, true);
-  }
-
-  // Proceed with the difference calculation if possible
-  void update_eval(const Position& pos) {
-    UpdateAccumulatorIfPossible(pos);
-  }
-
 } // namespace Eval::NNUE

src/nnue/evaluate_nnue_learner.cpp

@@ -1,6 +1,6 @@
 // Code for learning NNUE evaluation function
 
-#if defined(EVAL_LEARN) && defined(EVAL_NNUE)
+#if defined(EVAL_LEARN)
 
 #include <random>
 #include <fstream>
@@ -115,7 +115,6 @@ void RestoreParameters(const std::string& dir_name) {
   std::ifstream stream(file_name, std::ios::binary);
   bool result = ReadParameters(stream);
   assert(result);
-
   SendMessages({{"reset"}});
 }
 
@@ -216,9 +215,8 @@ void save_eval(std::string dir_name) {
 
   const std::string file_name = Path::Combine(eval_dir, NNUE::savedfileName);
   std::ofstream stream(file_name, std::ios::binary);
-  const bool result = NNUE::WriteParameters(stream);
+  bool result = NNUE::WriteParameters(stream);
   assert(result);
-
   std::cout << "save_eval() finished. folder = " << eval_dir << std::endl;
 }
 
@@ -229,4 +227,4 @@ double get_eta() {
 
 }  // namespace Eval
 
-#endif  // defined(EVAL_LEARN) && defined(EVAL_NNUE)
+#endif  // defined(EVAL_LEARN)

src/nnue/evaluate_nnue_learner.h

@@ -3,7 +3,7 @@
 #ifndef _EVALUATE_NNUE_LEARNER_H_
 #define _EVALUATE_NNUE_LEARNER_H_
 
-#if defined(EVAL_LEARN) && defined(EVAL_NNUE)
+#if defined(EVAL_LEARN)
 
 #include "../learn/learn.h"
 
@@ -41,6 +41,6 @@ void CheckHealth();
 
 }  // namespace Eval
 
-#endif  // defined(EVAL_LEARN) && defined(EVAL_NNUE)
+#endif  // defined(EVAL_LEARN)
 
 #endif

src/nnue/features/castling_right.cpp

@@ -1,7 +1,5 @@
 //Definition of input feature quantity K of NNUE evaluation function
 
-#if defined(EVAL_NNUE)
-
 #include "castling_right.h"
 #include "index_list.h"
 
@@ -28,7 +26,7 @@ namespace Eval {
             & ((castling_rights >> 2) & 3);
         }
 
-        for (int i = 0; i <kDimensions; ++i) {
+        for (unsigned int i = 0; i <kDimensions; ++i) {
           if (relative_castling_rights & (i << 1)) {
             active->push_back(i);
           }
@@ -56,7 +54,7 @@ namespace Eval {
             & ((current_castling_rights >> 2) & 3);
         }
 
-        for (int i = 0; i < kDimensions; ++i) {
+        for (unsigned int i = 0; i < kDimensions; ++i) {
           if ((relative_previous_castling_rights & (i << 1)) &&
             (relative_current_castling_rights & (i << 1)) == 0) {
             removed->push_back(i);
@@ -69,5 +67,3 @@ namespace Eval {
   }  // namespace NNUE
 
 }  // namespace Eval
-
-#endif  // defined(EVAL_NNUE)

src/nnue/features/castling_right.h

@@ -3,8 +3,6 @@
 #ifndef _NNUE_FEATURES_CASTLING_RIGHT_H_
 #define _NNUE_FEATURES_CASTLING_RIGHT_H_
 
-#if defined(EVAL_NNUE)
-
 #include "../../evaluate.h"
 #include "features_common.h"
 
@@ -43,6 +41,4 @@ namespace Eval {
 
 }  // namespace Eval
 
-#endif  // defined(EVAL_NNUE)
-
 #endif

src/nnue/features/enpassant.cpp

@@ -1,7 +1,5 @@
 //Definition of input feature quantity K of NNUE evaluation function
 
-#if defined(EVAL_NNUE)
-
 #include "enpassant.h"
 #include "index_list.h"
 
@@ -43,5 +41,3 @@ namespace Eval {
   }  // namespace NNUE
 
 }  // namespace Eval
-
-#endif  // defined(EVAL_NNUE)

src/nnue/features/enpassant.h

@@ -3,8 +3,6 @@
 #ifndef _NNUE_FEATURES_ENPASSANT_H_
 #define _NNUE_FEATURES_ENPASSANT_H_
 
-#if defined(EVAL_NNUE)
-
 #include "../../evaluate.h"
 #include "features_common.h"
 
@@ -43,6 +41,4 @@ namespace Eval {
 
 }  // namespace Eval
 
-#endif  // defined(EVAL_NNUE)
-
 #endif

src/nnue/features/half_relative_kp.cpp

@@ -1,7 +1,5 @@
 //Definition of input features HalfRelativeKP of NNUE evaluation function
 
-#if defined(EVAL_NNUE)
-
 #include "half_relative_kp.h"
 #include "index_list.h"
 
@@ -74,5 +72,3 @@ template class HalfRelativeKP<Side::kEnemy>;
 }  // namespace NNUE
 
 }  // namespace Eval
-
-#endif  // defined(EVAL_NNUE)

src/nnue/features/half_relative_kp.h

@@ -3,8 +3,6 @@
 #ifndef _NNUE_FEATURES_HALF_RELATIVE_KP_H_
 #define _NNUE_FEATURES_HALF_RELATIVE_KP_H_
 
-#if defined(EVAL_NNUE)
-
 #include "../../evaluate.h"
 #include "features_common.h"
 
@@ -60,6 +58,4 @@ class HalfRelativeKP {
 
 }  // namespace Eval
 
-#endif  // defined(EVAL_NNUE)
-
 #endif

src/nnue/features/k.cpp

@@ -1,7 +1,5 @@
 //Definition of input feature quantity K of NNUE evaluation function
 
-#if defined(EVAL_NNUE)
-
 #include "k.h"
 #include "index_list.h"
 
@@ -54,5 +52,3 @@ void K::AppendChangedIndices(
 }  // namespace NNUE
 
 }  // namespace Eval
-
-#endif  // defined(EVAL_NNUE)

src/nnue/features/k.h

@@ -3,8 +3,6 @@
 #ifndef _NNUE_FEATURES_K_H_
 #define _NNUE_FEATURES_K_H_
 
-#if defined(EVAL_NNUE)
-
 #include "../../evaluate.h"
 #include "features_common.h"
 
@@ -47,6 +45,4 @@ private:
 
 }  // namespace Eval
 
-#endif  // defined(EVAL_NNUE)
-
 #endif

src/nnue/features/p.cpp

@@ -1,7 +1,5 @@
 //Definition of input feature P of NNUE evaluation function
 
-#if defined(EVAL_NNUE)
-
 #include "p.h"
 #include "index_list.h"
 
@@ -52,5 +50,3 @@ void P::AppendChangedIndices(
 }  // namespace NNUE
 
 }  // namespace Eval
-
-#endif  // defined(EVAL_NNUE)

src/nnue/features/p.h

@@ -3,8 +3,6 @@
 #ifndef _NNUE_FEATURES_P_H_
 #define _NNUE_FEATURES_P_H_
 
-#if defined(EVAL_NNUE)
-
 #include "../../evaluate.h"
 #include "features_common.h"
 
@@ -47,6 +45,4 @@ class P {
 
 }  // namespace Eval
 
-#endif  // defined(EVAL_NNUE)
-
 #endif

src/nnue/layers/sum.h

@@ -3,8 +3,6 @@
 #ifndef _NNUE_LAYERS_SUM_H_
 #define _NNUE_LAYERS_SUM_H_
 
-#if defined(EVAL_NNUE)
-
 #include "../nnue_common.h"
 
 namespace Eval {
@@ -158,6 +156,4 @@ class Sum<PreviousLayer> {
 
 }  // namespace Eval
 
-#endif  // defined(EVAL_NNUE)
-
 #endif

src/nnue/nnue_accumulator.h

@@ -29,9 +29,7 @@ namespace Eval::NNUE {
   struct alignas(kCacheLineSize) Accumulator {
     std::int16_t
         accumulation[2][kRefreshTriggers.size()][kTransformedFeatureDimensions];
-    Value score;
     bool computed_accumulation;
-    bool computed_score;
   };
 
 }  // namespace Eval::NNUE

src/nnue/nnue_feature_transformer.h

@@ -50,6 +50,7 @@ namespace Eval::NNUE {
 
     // Hash value embedded in the evaluation file
     static constexpr std::uint32_t GetHashValue() {
+
       return RawFeatures::kHashValue ^ kOutputDimensions;
     }
 
@@ -62,6 +63,7 @@ namespace Eval::NNUE {
 
     // Read network parameters
     bool ReadParameters(std::istream& stream) {
+
       for (std::size_t i = 0; i < kHalfDimensions; ++i)
         biases_[i] = read_little_endian<BiasType>(stream);
       for (std::size_t i = 0; i < kHalfDimensions * kInputDimensions; ++i)
@@ -80,23 +82,26 @@ namespace Eval::NNUE {
 
     // Proceed with the difference calculation if possible
     bool UpdateAccumulatorIfPossible(const Position& pos) const {
+
       const auto now = pos.state();
-      if (now->accumulator.computed_accumulation) {
+      if (now->accumulator.computed_accumulation)
         return true;
-      }
+
       const auto prev = now->previous;
       if (prev && prev->accumulator.computed_accumulation) {
         UpdateAccumulator(pos);
         return true;
       }
+
       return false;
     }
 
     // Convert input features
-    void Transform(const Position& pos, OutputType* output, bool refresh) const {
-      if (refresh || !UpdateAccumulatorIfPossible(pos)) {
+    void Transform(const Position& pos, OutputType* output) const {
+
+      if (!UpdateAccumulatorIfPossible(pos))
         RefreshAccumulator(pos);
-      }
+
       const auto& accumulation = pos.state()->accumulator.accumulation;
 
   #if defined(USE_AVX2)
@@ -193,6 +198,7 @@ namespace Eval::NNUE {
    private:
     // Calculate cumulative value without using difference calculation
     void RefreshAccumulator(const Position& pos) const {
+
       auto& accumulator = pos.state()->accumulator;
       IndexType i = 0;
       Features::IndexList active_indices[2];
@@ -232,9 +238,8 @@ namespace Eval::NNUE {
               &accumulator.accumulation[perspective][i][0]);
           auto column = reinterpret_cast<const __m64*>(&weights_[offset]);
           constexpr IndexType kNumChunks = kHalfDimensions / (kSimdWidth / 2);
-          for (IndexType j = 0; j < kNumChunks; ++j) {
+          for (IndexType j = 0; j < kNumChunks; ++j)
             accumulation[j] = _mm_add_pi16(accumulation[j], column[j]);
-          }
 
   #elif defined(USE_NEON)
           auto accumulation = reinterpret_cast<int16x8_t*>(
@@ -256,11 +261,11 @@ namespace Eval::NNUE {
   #endif
 
       accumulator.computed_accumulation = true;
-      accumulator.computed_score = false;
     }
 
     // Calculate cumulative value using difference calculation
     void UpdateAccumulator(const Position& pos) const {
+
       const auto prev_accumulator = pos.state()->previous->accumulator;
       auto& accumulator = pos.state()->accumulator;
       IndexType i = 0;
@@ -304,33 +309,27 @@ namespace Eval::NNUE {
 
   #if defined(USE_AVX2)
             auto column = reinterpret_cast<const __m256i*>(&weights_[offset]);
-            for (IndexType j = 0; j < kNumChunks; ++j) {
+            for (IndexType j = 0; j < kNumChunks; ++j)
               accumulation[j] = _mm256_sub_epi16(accumulation[j], column[j]);
-            }
 
   #elif defined(USE_SSE2)
             auto column = reinterpret_cast<const __m128i*>(&weights_[offset]);
-            for (IndexType j = 0; j < kNumChunks; ++j) {
+            for (IndexType j = 0; j < kNumChunks; ++j)
               accumulation[j] = _mm_sub_epi16(accumulation[j], column[j]);
-            }
 
   #elif defined(USE_MMX)
             auto column = reinterpret_cast<const __m64*>(&weights_[offset]);
-            for (IndexType j = 0; j < kNumChunks; ++j) {
+            for (IndexType j = 0; j < kNumChunks; ++j)
               accumulation[j] = _mm_sub_pi16(accumulation[j], column[j]);
-            }
 
   #elif defined(USE_NEON)
             auto column = reinterpret_cast<const int16x8_t*>(&weights_[offset]);
-            for (IndexType j = 0; j < kNumChunks; ++j) {
+            for (IndexType j = 0; j < kNumChunks; ++j)
               accumulation[j] = vsubq_s16(accumulation[j], column[j]);
-            }
 
   #else
-            for (IndexType j = 0; j < kHalfDimensions; ++j) {
-              accumulator.accumulation[perspective][i][j] -=
-                  weights_[offset + j];
-            }
+            for (IndexType j = 0; j < kHalfDimensions; ++j)
+              accumulator.accumulation[perspective][i][j] -= weights_[offset + j];
   #endif
 
           }
@@ -341,33 +340,27 @@ namespace Eval::NNUE {
 
   #if defined(USE_AVX2)
             auto column = reinterpret_cast<const __m256i*>(&weights_[offset]);
-            for (IndexType j = 0; j < kNumChunks; ++j) {
+            for (IndexType j = 0; j < kNumChunks; ++j)
               accumulation[j] = _mm256_add_epi16(accumulation[j], column[j]);
-            }
 
   #elif defined(USE_SSE2)
             auto column = reinterpret_cast<const __m128i*>(&weights_[offset]);
-            for (IndexType j = 0; j < kNumChunks; ++j) {
+            for (IndexType j = 0; j < kNumChunks; ++j)
               accumulation[j] = _mm_add_epi16(accumulation[j], column[j]);
-            }
 
   #elif defined(USE_MMX)
             auto column = reinterpret_cast<const __m64*>(&weights_[offset]);
-            for (IndexType j = 0; j < kNumChunks; ++j) {
+            for (IndexType j = 0; j < kNumChunks; ++j)
               accumulation[j] = _mm_add_pi16(accumulation[j], column[j]);
-            }
 
   #elif defined(USE_NEON)
             auto column = reinterpret_cast<const int16x8_t*>(&weights_[offset]);
-            for (IndexType j = 0; j < kNumChunks; ++j) {
+            for (IndexType j = 0; j < kNumChunks; ++j)
               accumulation[j] = vaddq_s16(accumulation[j], column[j]);
-            }
 
   #else
-            for (IndexType j = 0; j < kHalfDimensions; ++j) {
-              accumulator.accumulation[perspective][i][j] +=
-                  weights_[offset + j];
-            }
+            for (IndexType j = 0; j < kHalfDimensions; ++j)
+              accumulator.accumulation[perspective][i][j] += weights_[offset + j];
   #endif
 
           }
@@ -378,7 +371,6 @@ namespace Eval::NNUE {
   #endif
 
       accumulator.computed_accumulation = true;
-      accumulator.computed_score = false;
     }
 
     using BiasType = std::int16_t;

src/nnue/nnue_test_command.cpp

@@ -1,6 +1,6 @@
 // USI extended command for NNUE evaluation function
 
-#if defined(ENABLE_TEST_CMD) && defined(EVAL_NNUE)
+#if defined(ENABLE_TEST_CMD)
 
 #include "../thread.h"
 #include "../uci.h"
@@ -198,4 +198,4 @@ void TestCommand(Position& pos, std::istream& stream) {
 
 }  // namespace Eval
 
-#endif  // defined(ENABLE_TEST_CMD) && defined(EVAL_NNUE)
+#endif  // defined(ENABLE_TEST_CMD)

src/nnue/nnue_test_command.h

@@ -3,7 +3,7 @@
 #ifndef _NNUE_TEST_COMMAND_H_
 #define _NNUE_TEST_COMMAND_H_
 
-#if defined(ENABLE_TEST_CMD) && defined(EVAL_NNUE)
+#if defined(ENABLE_TEST_CMD)
 
 namespace Eval {
 
@@ -16,6 +16,6 @@ void TestCommand(Position& pos, std::istream& stream);
 
 }  // namespace Eval
 
-#endif  // defined(ENABLE_TEST_CMD) && defined(EVAL_NNUE)
+#endif  // defined(ENABLE_TEST_CMD)
 
 #endif

src/nnue/trainer/features/factorizer.h

@@ -3,8 +3,6 @@
 #ifndef _NNUE_TRAINER_FEATURES_FACTORIZER_H_
 #define _NNUE_TRAINER_FEATURES_FACTORIZER_H_
 
-#if defined(EVAL_NNUE)
-
 #include "../../nnue_common.h"
 #include "../trainer.h"
 
@@ -105,6 +103,4 @@ constexpr std::size_t GetArrayLength(const T (&/*array*/)[N]) {
 
 }  // namespace Eval
 
-#endif  // defined(EVAL_NNUE)
-
 #endif

src/nnue/trainer/features/factorizer_feature_set.h

@@ -3,8 +3,6 @@
 #ifndef _NNUE_TRAINER_FEATURES_FACTORIZER_FEATURE_SET_H_
 #define _NNUE_TRAINER_FEATURES_FACTORIZER_FEATURE_SET_H_
 
-#if defined(EVAL_NNUE)
-
 #include "../../features/feature_set.h"
 #include "factorizer.h"
 
@@ -99,6 +97,4 @@ public:
 
 }  // namespace Eval
 
-#endif  // defined(EVAL_NNUE)
-
 #endif

src/nnue/trainer/features/factorizer_half_kp.h

@@ -3,8 +3,6 @@
 #ifndef _NNUE_TRAINER_FEATURES_FACTORIZER_HALF_KP_H_
 #define _NNUE_TRAINER_FEATURES_FACTORIZER_HALF_KP_H_
 
-#if defined(EVAL_NNUE)
-
 #include "../../features/half_kp.h"
 #include "../../features/p.h"
 #include "../../features/half_relative_kp.h"
@@ -98,6 +96,4 @@ constexpr FeatureProperties Factorizer<HalfKP<AssociatedKing>>::kProperties[];
 
 }  // namespace Eval
 
-#endif  // defined(EVAL_NNUE)
-
 #endif

src/nnue/trainer/trainer.h

@@ -3,7 +3,7 @@
 #ifndef _NNUE_TRAINER_H_
 #define _NNUE_TRAINER_H_
 
-#if defined(EVAL_LEARN) && defined(EVAL_NNUE)
+#if defined(EVAL_LEARN)
 
 #include "../nnue_common.h"
 #include "../features/index_list.h"
@@ -70,8 +70,8 @@ struct Example {
 
 // Message used for setting hyperparameters
 struct Message {
-  Message(const std::string& name, const std::string& value = ""):
-      name(name), value(value), num_peekers(0), num_receivers(0) {}
+  Message(const std::string& in_name, const std::string& in_value = ""):
+      name(in_name), value(in_value), num_peekers(0), num_receivers(0) {}
   const std::string name;
   const std::string value;
   std::uint32_t num_peekers;
@@ -120,6 +120,6 @@ std::shared_ptr<T> MakeAlignedSharedPtr(ArgumentTypes&&... arguments) {
 
 }  // namespace Eval
 
-#endif  // defined(EVAL_LEARN) && defined(EVAL_NNUE)
+#endif  // defined(EVAL_LEARN)
 
 #endif

src/nnue/trainer/trainer_affine_transform.h

@@ -3,7 +3,7 @@
 #ifndef _NNUE_TRAINER_AFFINE_TRANSFORM_H_
 #define _NNUE_TRAINER_AFFINE_TRANSFORM_H_
 
-#if defined(EVAL_LEARN) && defined(EVAL_NNUE)
+#if defined(EVAL_LEARN)
 
 #include "../../learn/learn.h"
 #include "../layers/affine_transform.h"
@@ -296,6 +296,6 @@ class Trainer<Layers::AffineTransform<PreviousLayer, OutputDimensions>> {
 
 }  // namespace Eval
 
-#endif  // defined(EVAL_LEARN) && defined(EVAL_NNUE)
+#endif  // defined(EVAL_LEARN)
 
 #endif

src/nnue/trainer/trainer_clipped_relu.h

@@ -3,7 +3,7 @@
 #ifndef _NNUE_TRAINER_CLIPPED_RELU_H_
 #define _NNUE_TRAINER_CLIPPED_RELU_H_
 
-#if defined(EVAL_LEARN) && defined(EVAL_NNUE)
+#if defined(EVAL_LEARN)
 
 #include "../../learn/learn.h"
 #include "../layers/clipped_relu.h"
@@ -137,6 +137,6 @@ class Trainer<Layers::ClippedReLU<PreviousLayer>> {
 
 }  // namespace Eval
 
-#endif  // defined(EVAL_LEARN) && defined(EVAL_NNUE)
+#endif  // defined(EVAL_LEARN)
 
 #endif

src/nnue/trainer/trainer_feature_transformer.h

@@ -3,7 +3,7 @@
 #ifndef _NNUE_TRAINER_FEATURE_TRANSFORMER_H_
 #define _NNUE_TRAINER_FEATURE_TRANSFORMER_H_
 
-#if defined(EVAL_LEARN) && defined(EVAL_NNUE)
+#if defined(EVAL_LEARN)
 
 #include "../../learn/learn.h"
 #include "../nnue_feature_transformer.h"
@@ -372,6 +372,6 @@ class Trainer<FeatureTransformer> {
 
 }  // namespace Eval
 
-#endif  // defined(EVAL_LEARN) && defined(EVAL_NNUE)
+#endif  // defined(EVAL_LEARN)
 
 #endif

src/nnue/trainer/trainer_input_slice.h

@@ -3,7 +3,7 @@
 #ifndef _NNUE_TRAINER_INPUT_SLICE_H_
 #define _NNUE_TRAINER_INPUT_SLICE_H_
 
-#if defined(EVAL_LEARN) && defined(EVAL_NNUE)
+#if defined(EVAL_LEARN)
 
 #include "../../learn/learn.h"
 #include "../layers/input_slice.h"
@@ -246,6 +246,6 @@ class Trainer<Layers::InputSlice<OutputDimensions, Offset>> {
 
 }  // namespace Eval
 
-#endif  // defined(EVAL_LEARN) && defined(EVAL_NNUE)
+#endif  // defined(EVAL_LEARN)
 
 #endif

src/nnue/trainer/trainer_sum.h

@@ -3,7 +3,7 @@
 #ifndef _NNUE_TRAINER_SUM_H_
 #define _NNUE_TRAINER_SUM_H_
 
-#if defined(EVAL_LEARN) && defined(EVAL_NNUE)
+#if defined(EVAL_LEARN)
 
 #include "../../learn/learn.h"
 #include "../layers/sum.h"
@@ -185,6 +185,6 @@ class Trainer<Layers::Sum<PreviousLayer>> {
 
 }  // namespace Eval
 
-#endif  // defined(EVAL_LEARN) && defined(EVAL_NNUE)
+#endif  // defined(EVAL_LEARN)
 
 #endif