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Support multi-class with base margin. (#7381)

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This is already partially supported but never properly tested. So the only possible way to use it is calling `numpy.ndarray.flatten` with `base_margin` before passing it into XGBoost. This PR adds proper support
for most of the data types along with tests.
This commit is contained in:
Jiaming Yuan
2021-11-02 13:38:00 +08:00
committed by GitHub
parent 6295dc3b67
commit a13321148a
18 changed files with 274 additions and 92 deletions
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6
src/predictor/gpu_predictor.cu
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@@ -938,7 +938,11 @@ class GPUPredictor : public xgboost::Predictor {
out_preds->SetDevice(generic_param_->gpu_id);
out_preds->Resize(n);
if (base_margin.Size() != 0) {
CHECK_EQ(base_margin.Size(), n);
std::string expected{
"(" + std::to_string(info.num_row_) + ", " +
std::to_string(model.learner_model_param->num_output_group) + ")"};
CHECK_EQ(base_margin.Size(), n)
<< "Invalid shape of base_margin. Expected:" << expected;
out_preds->Copy(base_margin);
} else {
out_preds->Fill(model.learner_model_param->base_score);