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Correctly account for factors when computing the average absolute weight of the feature transformer.

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Tomasz Sobczyk
2020-12-24 13:49:44 +01:00
committed by nodchip
parent 2061be4730
commit 7636bcccd1
1 changed files with 13 additions and 2 deletions
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src/nnue/trainer/trainer_feature_transformer.h
+13 -2
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@@ -621,8 +621,19 @@ namespace Eval::NNUE {
for(auto b : biases_) for(auto b : biases_)
abs_bias_sum += std::abs(b); abs_bias_sum += std::abs(b);
for(auto w : weights_) std::vector<TrainingFeature> training_features;
abs_weight_sum += std::abs(w); for (IndexType j = 0; j < RawFeatures::kDimensions; ++j)
{
training_features.clear();
Features::Factorizer<RawFeatures>::append_training_features(
j, &training_features);
for (const auto& feature : training_features) {
for (IndexType i = 0; i < kHalfDimensions; ++i) {
abs_weight_sum += std::abs(weights_[kHalfDimensions * feature.get_index() + i]);
}
}
}
auto out = sync_region_cout.new_region(); auto out = sync_region_cout.new_region();