New NNUE architecture and net

[stockfish] / src / nnue / nnue_architecture.h

diff --git a/src/nnue/nnue_architecture.h b/src/nnue/nnue_architecture.h
index 879a39cdbe68cfb4a4a6e3b64a457909520623c9..193a197d3b2ad1040aefb19a57199c1aad12ad7b 100644 (file)
--- a/src/nnue/nnue_architecture.h
+++ b/src/nnue/nnue_architecture.h
@@ -23,7 +23,7 @@
 
 #include "nnue_common.h"
 
-#include "features/half_ka_v2.h"
+#include "features/half_ka_v2_hm.h"
 
 #include "layers/input_slice.h"
 #include "layers/affine_transform.h"
@@ -32,10 +32,10 @@
 namespace Stockfish::Eval::NNUE {
 
   // Input features used in evaluation function
-  using FeatureSet = Features::HalfKAv2;
+  using FeatureSet = Features::HalfKAv2_hm;
 
   // Number of input feature dimensions after conversion
-  constexpr IndexType TransformedFeatureDimensions = 512;
+  constexpr IndexType TransformedFeatureDimensions = 1024;
   constexpr IndexType PSQTBuckets = 8;
   constexpr IndexType LayerStacks = 8;
 
@@ -43,7 +43,7 @@ namespace Stockfish::Eval::NNUE {
 
     // Define network structure
     using InputLayer = InputSlice<TransformedFeatureDimensions * 2>;
-    using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 16>>;
+    using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 8>>;
     using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
     using OutputLayer = AffineTransform<HiddenLayer2, 1>;