Add NNUE evaluation

[stockfish] / src / nnue / architectures / halfkp_256x2-32-32.h

diff --git a/src/nnue/architectures/halfkp_256x2-32-32.h b/src/nnue/architectures/halfkp_256x2-32-32.h
new file mode 100644 (file)
index 0000000..9216bd4
--- /dev/null
+++ b/src/nnue/architectures/halfkp_256x2-32-32.h
@@ -0,0 +1,54 @@
+/*
+  Stockfish, a UCI chess playing engine derived from Glaurung 2.1
+  Copyright (C) 2004-2020 The Stockfish developers (see AUTHORS file)
+
+  Stockfish is free software: you can redistribute it and/or modify
+  it under the terms of the GNU General Public License as published by
+  the Free Software Foundation, either version 3 of the License, or
+  (at your option) any later version.
+
+  Stockfish is distributed in the hope that it will be useful,
+  but WITHOUT ANY WARRANTY; without even the implied warranty of
+  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+  GNU General Public License for more details.
+
+  You should have received a copy of the GNU General Public License
+  along with this program.  If not, see <http://www.gnu.org/licenses/>.
+*/
+
+// Definition of input features and network structure used in NNUE evaluation function
+
+#ifndef NNUE_HALFKP_256X2_32_32_H_INCLUDED
+#define NNUE_HALFKP_256X2_32_32_H_INCLUDED
+
+#include "../features/feature_set.h"
+#include "../features/half_kp.h"
+
+#include "../layers/input_slice.h"
+#include "../layers/affine_transform.h"
+#include "../layers/clipped_relu.h"
+
+namespace Eval::NNUE {
+
+// Input features used in evaluation function
+using RawFeatures = Features::FeatureSet<
+    Features::HalfKP<Features::Side::kFriend>>;
+
+// Number of input feature dimensions after conversion
+constexpr IndexType kTransformedFeatureDimensions = 256;
+
+namespace Layers {
+
+// Define network structure
+using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
+using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 32>>;
+using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
+using OutputLayer = AffineTransform<HiddenLayer2, 1>;
+
+}  // namespace Layers
+
+using Network = Layers::OutputLayer;
+
+}  // namespace Eval::NNUE
+
+#endif // #ifndef NNUE_HALFKP_256X2_32_32_H_INCLUDED