Use ellpack for prediction only when sparsepage doesn't exist. (#5504)
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@@ -68,7 +68,7 @@ TEST(Adapter, CSCAdapterColsMoreThanRows) {
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}
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TEST(CAPI, DMatrixSliceAdapterFromSimpleDMatrix) {
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auto p_dmat = RandomDataGenerator(6, 2, 1.0).GenerateDMatix();
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auto p_dmat = RandomDataGenerator(6, 2, 1.0).GenerateDMatrix();
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std::vector<int> ridx_set = {1, 3, 5};
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data::DMatrixSliceAdapter adapter(p_dmat.get(),
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@@ -23,7 +23,7 @@ TEST(DeviceDMatrix, RowMajor) {
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auto adapter = common::AdapterFromData(x_device, num_rows, num_columns);
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data::DeviceDMatrix dmat(&adapter,
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std::numeric_limits<float>::quiet_NaN(), 1, 256);
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std::numeric_limits<float>::quiet_NaN(), 1, 256);
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auto &batch = *dmat.GetBatches<EllpackPage>({0, 256, 0}).begin();
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auto impl = batch.Impl();
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@@ -60,7 +60,7 @@ TEST(DeviceDMatrix, RowMajorMissing) {
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EXPECT_EQ(iterator[1], impl->GetDeviceAccessor(0).NullValue());
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EXPECT_EQ(iterator[5], impl->GetDeviceAccessor(0).NullValue());
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// null values get placed after valid values in a row
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EXPECT_EQ(iterator[7], impl->GetDeviceAccessor(0).NullValue());
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EXPECT_EQ(iterator[7], impl->GetDeviceAccessor(0).NullValue());
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EXPECT_EQ(dmat.Info().num_col_, num_columns);
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EXPECT_EQ(dmat.Info().num_row_, num_rows);
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EXPECT_EQ(dmat.Info().num_nonzero_, num_rows*num_columns-3);
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@@ -17,7 +17,7 @@ namespace xgboost {
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TEST(EllpackPage, EmptyDMatrix) {
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constexpr int kNRows = 0, kNCols = 0, kMaxBin = 256;
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constexpr float kSparsity = 0;
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auto dmat = RandomDataGenerator(kNRows, kNCols, kSparsity).GenerateDMatix();
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auto dmat = RandomDataGenerator(kNRows, kNCols, kSparsity).GenerateDMatrix();
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auto& page = *dmat->GetBatches<EllpackPage>({0, kMaxBin}).begin();
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auto impl = page.Impl();
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ASSERT_EQ(impl->row_stride, 0);
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@@ -220,7 +220,7 @@ TEST(SimpleDMatrix, FromFile) {
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TEST(SimpleDMatrix, Slice) {
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const int kRows = 6;
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const int kCols = 2;
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auto p_dmat = RandomDataGenerator(kRows, kCols, 1.0).GenerateDMatix();
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auto p_dmat = RandomDataGenerator(kRows, kCols, 1.0).GenerateDMatrix();
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auto &labels = p_dmat->Info().labels_.HostVector();
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auto &weights = p_dmat->Info().weights_.HostVector();
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auto &base_margin = p_dmat->Info().base_margin_.HostVector();
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