72cd1517d6
* Replaced std::vector with HostDeviceVector in MetaInfo and SparsePage. - added distributions to HostDeviceVector - using HostDeviceVector for labels, weights and base margings in MetaInfo - using HostDeviceVector for offset and data in SparsePage - other necessary refactoring * Added const version of HostDeviceVector API calls. - const versions added to calls that can trigger data transfers, e.g. DevicePointer() - updated the code that uses HostDeviceVector - objective functions now accept const HostDeviceVector<bst_float>& for predictions * Updated src/linear/updater_gpu_coordinate.cu. * Added read-only state for HostDeviceVector sync. - this means no copies are performed if both host and devices access the HostDeviceVector read-only * Fixed linter and test errors. - updated the lz4 plugin - added ConstDeviceSpan to HostDeviceVector - using device % dh::NVisibleDevices() for the physical device number, e.g. in calls to cudaSetDevice() * Fixed explicit template instantiation errors for HostDeviceVector. - replaced HostDeviceVector<unsigned int> with HostDeviceVector<int> * Fixed HostDeviceVector tests that require multiple GPUs. - added a mock set device handler; when set, it is called instead of cudaSetDevice()
86 lines
2.9 KiB
C++
86 lines
2.9 KiB
C++
// Copyright by Contributors
|
|
#include <xgboost/data.h>
|
|
#include "../../../src/data/simple_dmatrix.h"
|
|
|
|
#include "../helpers.h"
|
|
|
|
TEST(SimpleDMatrix, MetaInfo) {
|
|
std::string tmp_file = CreateSimpleTestData();
|
|
xgboost::DMatrix * dmat = xgboost::DMatrix::Load(tmp_file, true, false);
|
|
std::remove(tmp_file.c_str());
|
|
|
|
// Test the metadata that was parsed
|
|
EXPECT_EQ(dmat->Info().num_row_, 2);
|
|
EXPECT_EQ(dmat->Info().num_col_, 5);
|
|
EXPECT_EQ(dmat->Info().num_nonzero_, 6);
|
|
EXPECT_EQ(dmat->Info().labels_.Size(), dmat->Info().num_row_);
|
|
|
|
delete dmat;
|
|
}
|
|
|
|
TEST(SimpleDMatrix, RowAccess) {
|
|
std::string tmp_file = CreateSimpleTestData();
|
|
xgboost::DMatrix * dmat = xgboost::DMatrix::Load(tmp_file, false, false);
|
|
std::remove(tmp_file.c_str());
|
|
|
|
auto row_iter = dmat->RowIterator();
|
|
// Loop over the batches and count the records
|
|
long row_count = 0;
|
|
row_iter->BeforeFirst();
|
|
while (row_iter->Next()) row_count += row_iter->Value().Size();
|
|
EXPECT_EQ(row_count, dmat->Info().num_row_);
|
|
// Test the data read into the first row
|
|
row_iter->BeforeFirst();
|
|
row_iter->Next();
|
|
auto first_row = row_iter->Value()[0];
|
|
ASSERT_EQ(first_row.size(), 3);
|
|
EXPECT_EQ(first_row[2].index, 2);
|
|
EXPECT_EQ(first_row[2].fvalue, 20);
|
|
row_iter = nullptr;
|
|
|
|
delete dmat;
|
|
}
|
|
|
|
TEST(SimpleDMatrix, ColAccessWithoutBatches) {
|
|
std::string tmp_file = CreateSimpleTestData();
|
|
xgboost::DMatrix * dmat = xgboost::DMatrix::Load(tmp_file, true, false);
|
|
std::remove(tmp_file.c_str());
|
|
|
|
// Unsorted column access
|
|
const std::vector<bool> enable(dmat->Info().num_col_, true);
|
|
EXPECT_EQ(dmat->HaveColAccess(false), false);
|
|
dmat->InitColAccess(dmat->Info().num_row_, false);
|
|
dmat->InitColAccess(0, false); // Calling it again should not change it
|
|
ASSERT_EQ(dmat->HaveColAccess(false), true);
|
|
|
|
// Sorted column access
|
|
EXPECT_EQ(dmat->HaveColAccess(true), false);
|
|
dmat->InitColAccess(dmat->Info().num_row_, true);
|
|
dmat->InitColAccess(0, true); // Calling it again should not change it
|
|
ASSERT_EQ(dmat->HaveColAccess(true), true);
|
|
|
|
EXPECT_EQ(dmat->GetColSize(0), 2);
|
|
EXPECT_EQ(dmat->GetColSize(1), 1);
|
|
EXPECT_EQ(dmat->GetColDensity(0), 1);
|
|
EXPECT_EQ(dmat->GetColDensity(1), 0.5);
|
|
ASSERT_TRUE(dmat->SingleColBlock());
|
|
|
|
auto* col_iter = dmat->ColIterator();
|
|
// Loop over the batches and assert the data is as expected
|
|
long num_col_batch = 0;
|
|
col_iter->BeforeFirst();
|
|
while (col_iter->Next()) {
|
|
num_col_batch += 1;
|
|
EXPECT_EQ(col_iter->Value().Size(), dmat->Info().num_col_)
|
|
<< "Expected batch size = number of cells as #batches is 1.";
|
|
for (int i = 0; i < static_cast<int>(col_iter->Value().Size()); ++i) {
|
|
EXPECT_EQ(col_iter->Value()[i].size(), dmat->GetColSize(i))
|
|
<< "Expected length of each colbatch = colsize as #batches is 1.";
|
|
}
|
|
}
|
|
EXPECT_EQ(num_col_batch, 1) << "Expected number of batches to be 1";
|
|
col_iter = nullptr;
|
|
|
|
delete dmat;
|
|
}
|