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PascalCase -> snake_case for consistency with the rest of the codebase.

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This commit is contained in:
Tomasz Sobczyk
2020-10-14 22:42:58 +02:00
committed by nodchip
parent 2398d34e87
commit 146a6b056e
37 changed files with 844 additions and 737 deletions
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src/nnue/trainer/features/factorizer_feature_set.h
+17 -17
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@@ -22,12 +22,12 @@ namespace Eval::NNUE::Features {
FeatureSet<FirstFeatureType, RemainingFeatureTypes...>::kDimensions;
// Get the dimensionality of the learning feature
static constexpr IndexType GetDimensions() {
return Head::GetDimensions() + Tail::GetDimensions();
static constexpr IndexType get_dimensions() {
return Head::get_dimensions() + Tail::get_dimensions();
}
// Get index of learning feature and scale of learning rate
static void AppendTrainingFeatures(
static void append_training_features(
IndexType base_index, std::vector<TrainingFeature>* training_features,
IndexType base_dimensions = kBaseDimensions) {
@@ -36,29 +36,29 @@ namespace Eval::NNUE::Features {
constexpr auto boundary = FeatureSet<RemainingFeatureTypes...>::kDimensions;
if (base_index < boundary) {
Tail::AppendTrainingFeatures(
Tail::append_training_features(
base_index, training_features, base_dimensions);
}
else {
const auto start = training_features->size();
Head::AppendTrainingFeatures(
Head::append_training_features(
base_index - boundary, training_features, base_dimensions);
for (auto i = start; i < training_features->size(); ++i) {
auto& feature = (*training_features)[i];
const auto index = feature.GetIndex();
const auto index = feature.get_index();
assert(index < Head::GetDimensions() ||
assert(index < Head::get_dimensions() ||
(index >= base_dimensions &&
index < base_dimensions +
Head::GetDimensions() - Head::kBaseDimensions));
Head::get_dimensions() - Head::kBaseDimensions));
if (index < Head::kBaseDimensions) {
feature.ShiftIndex(Tail::kBaseDimensions);
feature.shift_index(Tail::kBaseDimensions);
}
else {
feature.ShiftIndex(Tail::GetDimensions() - Tail::kBaseDimensions);
feature.shift_index(Tail::get_dimensions() - Tail::kBaseDimensions);
}
}
}
@@ -74,12 +74,12 @@ namespace Eval::NNUE::Features {
static constexpr IndexType kBaseDimensions = FeatureType::kDimensions;
// Get the dimensionality of the learning feature
static constexpr IndexType GetDimensions() {
return Factorizer<FeatureType>::GetDimensions();
static constexpr IndexType get_dimensions() {
return Factorizer<FeatureType>::get_dimensions();
}
// Get index of learning feature and scale of learning rate
static void AppendTrainingFeatures(
static void append_training_features(
IndexType base_index, std::vector<TrainingFeature>* training_features,
IndexType base_dimensions = kBaseDimensions) {
@@ -87,14 +87,14 @@ namespace Eval::NNUE::Features {
const auto start = training_features->size();
Factorizer<FeatureType>::AppendTrainingFeatures(
Factorizer<FeatureType>::append_training_features(
base_index, training_features);
for (auto i = start; i < training_features->size(); ++i) {
auto& feature = (*training_features)[i];
assert(feature.GetIndex() < Factorizer<FeatureType>::GetDimensions());
if (feature.GetIndex() >= kBaseDimensions) {
feature.ShiftIndex(base_dimensions - kBaseDimensions);
assert(feature.get_index() < Factorizer<FeatureType>::get_dimensions());
if (feature.get_index() >= kBaseDimensions) {
feature.shift_index(base_dimensions - kBaseDimensions);
}
}
}