Clang-tidy static analysis (#3222)
* Clang-tidy static analysis * Modernise checks * Google coding standard checks * Identifier renaming according to Google style
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@@ -36,21 +36,21 @@ class MyLogistic : public ObjFunction {
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void GetGradient(HostDeviceVector<bst_float> *preds,
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const MetaInfo &info,
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int iter,
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HostDeviceVector<bst_gpair> *out_gpair) override {
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out_gpair->resize(preds->size());
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std::vector<bst_float>& preds_h = preds->data_h();
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std::vector<bst_gpair>& out_gpair_h = out_gpair->data_h();
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HostDeviceVector<GradientPair> *out_gpair) override {
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out_gpair->Resize(preds->Size());
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std::vector<bst_float>& preds_h = preds->HostVector();
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std::vector<GradientPair>& out_gpair_h = out_gpair->HostVector();
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for (size_t i = 0; i < preds_h.size(); ++i) {
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bst_float w = info.GetWeight(i);
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// scale the negative examples!
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if (info.labels[i] == 0.0f) w *= param_.scale_neg_weight;
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if (info.labels_[i] == 0.0f) w *= param_.scale_neg_weight;
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// logistic transformation
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bst_float p = 1.0f / (1.0f + std::exp(-preds_h[i]));
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// this is the gradient
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bst_float grad = (p - info.labels[i]) * w;
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bst_float grad = (p - info.labels_[i]) * w;
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// this is the second order gradient
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bst_float hess = p * (1.0f - p) * w;
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out_gpair_h.at(i) = bst_gpair(grad, hess);
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out_gpair_h.at(i) = GradientPair(grad, hess);
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}
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}
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const char* DefaultEvalMetric() const override {
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@@ -58,7 +58,7 @@ class MyLogistic : public ObjFunction {
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}
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void PredTransform(HostDeviceVector<bst_float> *io_preds) override {
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// transform margin value to probability.
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std::vector<bst_float> &preds = io_preds->data_h();
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std::vector<bst_float> &preds = io_preds->HostVector();
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for (size_t i = 0; i < preds.size(); ++i) {
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preds[i] = 1.0f / (1.0f + std::exp(-preds[i]));
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}
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