Incorrect layer stack hash about nnue-pytorch HOT 13 CLOSED

diff --git a/model.py b/model.py
index fb34284..c1d4724 100644
--- a/model.py
+++ b/model.py
@@ -6,9 +6,9 @@ import torch.nn.functional as F
 import pytorch_lightning as pl
 
 # 3 layer fully connected network
-L1 = 256
-L2 = 32
-L3 = 32
+L1 = 512
+L2 = 16
+L3 = 16
 
 class NNUE(pl.LightningModule):
   """

diff --git a/src/evaluate.h b/src/evaluate.h
index 8beca2d0a..92cf96df0 100644
--- a/src/evaluate.h
+++ b/src/evaluate.h
@@ -36,7 +36,7 @@ namespace Eval {
   // The default net name MUST follow the format nn-[SHA256 first 12 digits].nnue
   // for the build process (profile-build and fishtest) to work. Do not change the
   // name of the macro, as it is used in the Makefile.
-  #define EvalFileDefaultName   "nn-62ef826d1a6d.nnue"
+  #define EvalFileDefaultName   "nn-f73eccf09644.nnue"
 
   namespace NNUE {
 
diff --git a/src/nnue/architectures/halfkp_256x2-32-32.h b/src/nnue/architectures/halfkp_256x2-32-32.h
index a0fe2e0ad..410465139 100644
--- a/src/nnue/architectures/halfkp_256x2-32-32.h
+++ b/src/nnue/architectures/halfkp_256x2-32-32.h
@@ -35,14 +35,14 @@ using RawFeatures = Features::FeatureSet<
     Features::HalfKP<Features::Side::kFriend>>;
 
 // Number of input feature dimensions after conversion
-constexpr IndexType kTransformedFeatureDimensions = 256;
+constexpr IndexType kTransformedFeatureDimensions = 512;
 
 namespace Layers {
 
 // Define network structure
 using InputLayer = InputSlice<kTransformedFeatureDimensions * 2>;
-using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 32>>;
-using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 32>>;
+using HiddenLayer1 = ClippedReLU<AffineTransform<InputLayer, 16>>;
+using HiddenLayer2 = ClippedReLU<AffineTransform<HiddenLayer1, 16>>;
 using OutputLayer = AffineTransform<HiddenLayer2, 1>;
 
 }  // namespace Layers