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Clean up and simplify some nnue code.

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Remove some unnecessary code and it's execution during inference. Also the change on line 49 in nnue_architecture.h results in a more efficient SIMD code path through ClippedReLU::propagate().

passed STC:
https://tests.stockfishchess.org/tests/view/6217d3bfda649bba32ef25d5
LLR: 2.94 (-2.94,2.94) <-2.25,0.25>
Total: 12056 W: 3281 L: 3092 D: 5683
Ptnml(0-2): 55, 1213, 3312, 1384, 64

passed STC SMP:
https://tests.stockfishchess.org/tests/view/6217f344da649bba32ef295e
LLR: 2.94 (-2.94,2.94) <-2.25,0.25>
Total: 27376 W: 7295 L: 7137 D: 12944
Ptnml(0-2): 52, 2859, 7715, 3003, 59

closes https://github.com/official-stockfish/Stockfish/pull/3944

No functional change

bench: 6820724
This commit is contained in:
mstembera
2022-02-23 18:19:36 -08:00
committed by Joost VandeVondele
parent 27139dedac
commit 5f781d366e
6 changed files with 27 additions and 32 deletions
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src/nnue/layers/affine_transform.h
+8 -8
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@@ -235,10 +235,10 @@ namespace Stockfish::Eval::NNUE::Layers {
// Read network parameters
bool read_parameters(std::istream& stream) {
for (std::size_t i = 0; i < OutputDimensions; ++i)
for (IndexType i = 0; i < OutputDimensions; ++i)
biases[i] = read_little_endian<BiasType>(stream);
for (std::size_t i = 0; i < OutputDimensions * PaddedInputDimensions; ++i)
for (IndexType i = 0; i < OutputDimensions * PaddedInputDimensions; ++i)
weights[get_weight_index(i)] = read_little_endian<WeightType>(stream);
return !stream.fail();
@@ -246,10 +246,10 @@ namespace Stockfish::Eval::NNUE::Layers {
// Write network parameters
bool write_parameters(std::ostream& stream) const {
for (std::size_t i = 0; i < OutputDimensions; ++i)
for (IndexType i = 0; i < OutputDimensions; ++i)
write_little_endian<BiasType>(stream, biases[i]);
for (std::size_t i = 0; i < OutputDimensions * PaddedInputDimensions; ++i)
for (IndexType i = 0; i < OutputDimensions * PaddedInputDimensions; ++i)
write_little_endian<WeightType>(stream, weights[get_weight_index(i)]);
return !stream.fail();
@@ -422,9 +422,9 @@ namespace Stockfish::Eval::NNUE::Layers {
// Read network parameters
bool read_parameters(std::istream& stream) {
for (std::size_t i = 0; i < OutputDimensions; ++i)
for (IndexType i = 0; i < OutputDimensions; ++i)
biases[i] = read_little_endian<BiasType>(stream);
for (std::size_t i = 0; i < OutputDimensions * PaddedInputDimensions; ++i)
for (IndexType i = 0; i < OutputDimensions * PaddedInputDimensions; ++i)
weights[get_weight_index(i)] = read_little_endian<WeightType>(stream);
return !stream.fail();
@@ -432,10 +432,10 @@ namespace Stockfish::Eval::NNUE::Layers {
// Write network parameters
bool write_parameters(std::ostream& stream) const {
for (std::size_t i = 0; i < OutputDimensions; ++i)
for (IndexType i = 0; i < OutputDimensions; ++i)
write_little_endian<BiasType>(stream, biases[i]);
for (std::size_t i = 0; i < OutputDimensions * PaddedInputDimensions; ++i)
for (IndexType i = 0; i < OutputDimensions * PaddedInputDimensions; ++i)
write_little_endian<WeightType>(stream, weights[get_weight_index(i)]);
return !stream.fail();