a96039141a
* Use sparse page as singular CSR matrix representation * Simplify dmatrix methods * Reduce statefullness of batch iterators * BREAKING CHANGE: Remove prob_buffer_row parameter. Users are instead recommended to sample their dataset as a preprocessing step before using XGBoost.
40 lines
1.2 KiB
C++
40 lines
1.2 KiB
C++
// Copyright by Contributors
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#include <gtest/gtest.h>
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#include <xgboost/c_api.h>
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#include <xgboost/data.h>
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TEST(c_api, XGDMatrixCreateFromMat_omp) {
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std::vector<int> num_rows = {100, 11374, 15000};
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for (auto row : num_rows) {
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int num_cols = 50;
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int num_missing = 5;
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DMatrixHandle handle;
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std::vector<float> data(num_cols * row, 1.5);
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for (int i = 0; i < num_missing; i++) {
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data[i] = std::numeric_limits<float>::quiet_NaN();
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}
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XGDMatrixCreateFromMat_omp(data.data(), row, num_cols,
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std::numeric_limits<float>::quiet_NaN(), &handle,
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0);
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std::shared_ptr<xgboost::DMatrix> dmat =
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*static_cast<std::shared_ptr<xgboost::DMatrix> *>(handle);
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xgboost::MetaInfo &info = dmat->Info();
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ASSERT_EQ(info.num_col_, num_cols);
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ASSERT_EQ(info.num_row_, row);
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ASSERT_EQ(info.num_nonzero_, num_cols * row - num_missing);
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auto iter = dmat->RowIterator();
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iter->BeforeFirst();
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while (iter->Next()) {
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auto batch = iter->Value();
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for (int i = 0; i < batch.Size(); i++) {
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auto inst = batch[i];
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for (int j = 0; i < inst.length; i++) {
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ASSERT_EQ(inst[j].fvalue, 1.5);
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}
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}
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}
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}
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} |