Stockfish17のAffineTransformとAffineTransformSparseInputを移植した (#289)

yaneurao · Oct 7, 2024 · 9c41f5b · 9c41f5b
1 parent 434a339
commit 9c41f5b
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Showing 11 changed files with 756 additions and 619 deletions.
diff --git a/source/eval/nnue/architectures/halfkp_1024x2-8-32.h b/source/eval/nnue/architectures/halfkp_1024x2-8-32.h
@@ -8,6 +8,7 @@
 
 #include "../layers/input_slice.h"
 #include "../layers/affine_transform.h"
+#include "../layers/affine_transform_sparse_input.h"
 #include "../layers/clipped_relu.h"
 
 namespace Eval::NNUE {
@@ -26,7 +27,7 @@ namespace Layers {
 // Define network structure
 // ネットワーク構造の定義
 using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
-using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 8>>;
+using HiddenLayer1 = ClippedReLU<AffineTransformSparseInput<InputLayer, 8>>;
 using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
 using OutputLayer = AffineTransform<HiddenLayer2, 1>;
 

diff --git a/source/eval/nnue/architectures/halfkp_1024x2-8-64.h b/source/eval/nnue/architectures/halfkp_1024x2-8-64.h
@@ -8,6 +8,7 @@
 
 #include "../layers/input_slice.h"
 #include "../layers/affine_transform.h"
+#include "../layers/affine_transform_sparse_input.h"
 #include "../layers/clipped_relu.h"
 
 namespace Eval::NNUE {
@@ -26,7 +27,7 @@ namespace Eval::NNUE {
 		// Define network structure
 		// ネットワーク構造の定義
 		using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
-		using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 8>>;
+		using HiddenLayer1 = ClippedReLU<AffineTransformSparseInput<InputLayer, 8>>;
 		using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 64>>;
 		using OutputLayer = AffineTransform<HiddenLayer2, 1>;
 

diff --git a/source/eval/nnue/architectures/halfkp_256x2-32-32.h b/source/eval/nnue/architectures/halfkp_256x2-32-32.h
@@ -8,6 +8,7 @@
 
 #include "../layers/input_slice.h"
 #include "../layers/affine_transform.h"
+#include "../layers/affine_transform_sparse_input.h"
 #include "../layers/clipped_relu.h"
 
 namespace Eval::NNUE {
@@ -26,7 +27,7 @@ namespace Layers {
 // Define network structure
 // ネットワーク構造の定義
 using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
-using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 32>>;
+using HiddenLayer1 = ClippedReLU<AffineTransformSparseInput<InputLayer, 32>>;
 using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
 using OutputLayer = AffineTransform<HiddenLayer2, 1>;
 

diff --git a/source/eval/nnue/architectures/halfkp_512x2-16-32.h b/source/eval/nnue/architectures/halfkp_512x2-16-32.h
@@ -8,6 +8,7 @@
 
 #include "../layers/input_slice.h"
 #include "../layers/affine_transform.h"
+#include "../layers/affine_transform_sparse_input.h"
 #include "../layers/clipped_relu.h"
 
 namespace Eval::NNUE {
@@ -26,7 +27,7 @@ namespace Layers {
 // Define network structure
 // ネットワーク構造の定義
 using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
-using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 16>>;
+using HiddenLayer1 = ClippedReLU<AffineTransformSparseInput<InputLayer, 16>>;
 using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
 using OutputLayer = AffineTransform<HiddenLayer2, 1>;
 

diff --git a/source/eval/nnue/architectures/halfkpe9_256x2-32-32.h b/source/eval/nnue/architectures/halfkpe9_256x2-32-32.h
@@ -8,6 +8,7 @@
 
 #include "../layers/input_slice.h"
 #include "../layers/affine_transform.h"
+#include "../layers/affine_transform_sparse_input.h"
 #include "../layers/clipped_relu.h"
 
 namespace Eval {
@@ -25,7 +26,7 @@ namespace NNUE {
 
 	// ネットワーク構造の定義
 	using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
-	using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 32>>;
+	using HiddenLayer1 = ClippedReLU<AffineTransformSparseInput<InputLayer, 32>>;
 	using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
 	using OutputLayer = AffineTransform<HiddenLayer2, 1>;
 

diff --git a/source/eval/nnue/architectures/halfkpvm_256x2-32-32.h b/source/eval/nnue/architectures/halfkpvm_256x2-32-32.h
@@ -8,6 +8,7 @@
 
 #include "../layers/input_slice.h"
 #include "../layers/affine_transform.h"
+#include "../layers/affine_transform_sparse_input.h"
 #include "../layers/clipped_relu.h"
 
 namespace Eval {
@@ -25,7 +26,7 @@ namespace Eval {
 
             // ネットワーク構造の定義
             using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
-            using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 32>>;
+            using HiddenLayer1 = ClippedReLU<AffineTransformSparseInput<InputLayer, 32>>;
             using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
             using OutputLayer = AffineTransform<HiddenLayer2, 1>;
 

diff --git a/source/eval/nnue/architectures/kp_256x2-32-32.h b/source/eval/nnue/architectures/kp_256x2-32-32.h
@@ -8,6 +8,7 @@
 
 #include "../layers/input_slice.h"
 #include "../layers/affine_transform.h"
+#include "../layers/affine_transform_sparse_input.h"
 #include "../layers/clipped_relu.h"
 
 namespace Eval {
@@ -24,7 +25,7 @@ namespace Layers {
 
 // ネットワーク構造の定義
 using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
-using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 32>>;
+using HiddenLayer1 = ClippedReLU<AffineTransformSparseInput<InputLayer, 32>>;
 using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
 using OutputLayer = AffineTransform<HiddenLayer2, 1>;
 

diff --git a/source/eval/nnue/architectures/nnue_arch_gen.py b/source/eval/nnue/architectures/nnue_arch_gen.py
@@ -127,6 +127,7 @@
 header += f"""
     #include "../layers/input_slice.h"
     #include "../layers/affine_transform.h"
+    #include "../layers/affine_transform_sparse_input.h"
     #include "../layers/clipped_relu.h"
 
     namespace Eval::NNUE {{
@@ -164,7 +165,7 @@
             // Define network structure
             // ネットワーク構造の定義
             using InputLayer = InputSlice<kTransformedFeatureDimensions * {first_layer[1]}>;
-            using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, {layers[1]}>>;
+            using HiddenLayer1 = ClippedReLU<AffineTransformSparseInput<InputLayer, {layers[1]}>>;
             using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, {layers[2]}>>;
             using OutputLayer = AffineTransform<HiddenLayer2, 1>;