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Replaced std::vector-based interfaces with HostDeviceVector-based interfaces. (#3116)

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* Replaced std::vector-based interfaces with HostDeviceVector-based interfaces.

- replacement was performed in the learner, boosters, predictors,
  updaters, and objective functions
- only interfaces used in training were replaced;
  interfaces like PredictInstance() still use std::vector
- refactoring necessary for replacement of interfaces was also performed,
  such as using HostDeviceVector in prediction cache

* HostDeviceVector-based interfaces for custom objective function example plugin.
This commit is contained in:
Andrew V. Adinetz
2018-02-28 01:00:04 +01:00
committed by Rory Mitchell
parent 11bfa8584d
commit d5992dd881
38 changed files with 371 additions and 519 deletions
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18
plugin/example/custom_obj.cc
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@@ -33,30 +33,32 @@ class MyLogistic : public ObjFunction {
void Configure(const std::vector<std::pair<std::string, std::string> >& args) override {
param_.InitAllowUnknown(args);
}
void GetGradient(const std::vector<bst_float> &preds,
void GetGradient(HostDeviceVector<bst_float> *preds,
const MetaInfo &info,
int iter,
std::vector<bst_gpair> *out_gpair) override {
out_gpair->resize(preds.size());
for (size_t i = 0; i < preds.size(); ++i) {
HostDeviceVector<bst_gpair> *out_gpair) override {
out_gpair->resize(preds->size());
std::vector<bst_float>& preds_h = preds->data_h();
std::vector<bst_gpair>& out_gpair_h = out_gpair->data_h();
for (size_t i = 0; i < preds_h.size(); ++i) {
bst_float w = info.GetWeight(i);
// scale the negative examples!
if (info.labels[i] == 0.0f) w *= param_.scale_neg_weight;
// logistic transformation
bst_float p = 1.0f / (1.0f + std::exp(-preds[i]));
bst_float p = 1.0f / (1.0f + std::exp(-preds_h[i]));
// this is the gradient
bst_float grad = (p - info.labels[i]) * w;
// this is the second order gradient
bst_float hess = p * (1.0f - p) * w;
out_gpair->at(i) = bst_gpair(grad, hess);
out_gpair_h.at(i) = bst_gpair(grad, hess);
}
}
const char* DefaultEvalMetric() const override {
return "error";
}
void PredTransform(std::vector<bst_float> *io_preds) override {
void PredTransform(HostDeviceVector<bst_float> *io_preds) override {
// transform margin value to probability.
std::vector<bst_float> &preds = *io_preds;
std::vector<bst_float> &preds = io_preds->data_h();
for (size_t i = 0; i < preds.size(); ++i) {
preds[i] = 1.0f / (1.0f + std::exp(-preds[i]));
}