Method ValidateDMatrix

src/learner.cc:1298–1318

  }

  void ValidateDMatrix(DMatrix* p_fmat, bool is_training) const {
    MetaInfo const& info = p_fmat->Info();
    info.Validate(ctx_.Device());

    if (is_training) {
      CHECK_EQ(learner_model_param_.num_feature, p_fmat->Info().num_col_)
          << "Number of columns does not match number of features in "
             "booster.";
    } else {
      CHECK_GE(learner_model_param_.num_feature, p_fmat->Info().num_col_)
          << "Number of columns does not match number of features in "
             "booster.";
    }

    if (p_fmat->Info().num_row_ == 0) {
      error::WarnEmptyDataset();
    }
    if (!p_fmat->Info().base_margin_.Empty()) {
      CHECK_EQ(p_fmat->Info().base_margin_.Shape(1), this->mparam_.OutputLength());
    }
  }

 private:
  void GetGradient(HostDeviceVector<float> const& preds, MetaInfo const& info, std::int32_t iter,