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Remove internal use of gpu_id. (#9568)

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This commit is contained in:
Jiaming Yuan
2023-09-20 23:29:51 +08:00
committed by GitHub
parent 38ac52dd87
commit 8c676c889d
121 changed files with 1012 additions and 1044 deletions
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35
tests/cpp/common/test_hist_util.cu
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@@ -208,7 +208,7 @@ TEST(HistUtil, RemoveDuplicatedCategories) {
ASSERT_EQ(info.feature_types.Size(), n_features);
HostDeviceVector<bst_row_t> cuts_ptr{0, n_samples, n_samples * 2, n_samples * 3};
cuts_ptr.SetDevice(0);
cuts_ptr.SetDevice(DeviceOrd::CUDA(0));
dh::device_vector<float> weight(n_samples * n_features, 0);
dh::Iota(dh::ToSpan(weight));
@@ -221,7 +221,7 @@ TEST(HistUtil, RemoveDuplicatedCategories) {
thrust::sort_by_key(sorted_entries.begin(), sorted_entries.end(), weight.begin(),
detail::EntryCompareOp());
detail::RemoveDuplicatedCategories(ctx.gpu_id, info, cuts_ptr.DeviceSpan(), &sorted_entries,
detail::RemoveDuplicatedCategories(ctx.Device(), info, cuts_ptr.DeviceSpan(), &sorted_entries,
&weight, &columns_ptr);
auto const& h_cptr = cuts_ptr.ConstHostVector();
@@ -363,7 +363,8 @@ template <typename Adapter>
auto MakeUnweightedCutsForTest(Adapter adapter, int32_t num_bins, float missing, size_t batch_size = 0) {
common::HistogramCuts batched_cuts;
HostDeviceVector<FeatureType> ft;
SketchContainer sketch_container(ft, num_bins, adapter.NumColumns(), adapter.NumRows(), 0);
SketchContainer sketch_container(ft, num_bins, adapter.NumColumns(), adapter.NumRows(),
DeviceOrd::CUDA(0));
MetaInfo info;
AdapterDeviceSketch(adapter.Value(), num_bins, info, missing, &sketch_container, batch_size);
sketch_container.MakeCuts(&batched_cuts, info.IsColumnSplit());
@@ -430,7 +431,7 @@ TEST(HistUtil, AdapterSketchSlidingWindowMemory) {
ConsoleLogger::Configure({{"verbosity", "3"}});
common::HistogramCuts batched_cuts;
HostDeviceVector<FeatureType> ft;
SketchContainer sketch_container(ft, num_bins, num_columns, num_rows, 0);
SketchContainer sketch_container(ft, num_bins, num_columns, num_rows, DeviceOrd::CUDA(0));
AdapterDeviceSketch(adapter.Value(), num_bins, info, std::numeric_limits<float>::quiet_NaN(),
&sketch_container);
HistogramCuts cuts;
@@ -458,7 +459,7 @@ TEST(HistUtil, AdapterSketchSlidingWindowWeightedMemory) {
ConsoleLogger::Configure({{"verbosity", "3"}});
common::HistogramCuts batched_cuts;
HostDeviceVector<FeatureType> ft;
SketchContainer sketch_container(ft, num_bins, num_columns, num_rows, 0);
SketchContainer sketch_container(ft, num_bins, num_columns, num_rows, DeviceOrd::CUDA(0));
AdapterDeviceSketch(adapter.Value(), num_bins, info,
std::numeric_limits<float>::quiet_NaN(),
&sketch_container);
@@ -493,7 +494,7 @@ void TestCategoricalSketchAdapter(size_t n, size_t num_categories,
}
ASSERT_EQ(info.feature_types.Size(), 1);
SketchContainer container(info.feature_types, num_bins, 1, n, 0);
SketchContainer container(info.feature_types, num_bins, 1, n, DeviceOrd::CUDA(0));
AdapterDeviceSketch(adapter.Value(), num_bins, info,
std::numeric_limits<float>::quiet_NaN(), &container);
HistogramCuts cuts;
@@ -566,7 +567,7 @@ TEST(HistUtil, AdapterDeviceSketchBatches) {
namespace {
auto MakeData(Context const* ctx, std::size_t n_samples, bst_feature_t n_features) {
dh::safe_cuda(cudaSetDevice(ctx->gpu_id));
dh::safe_cuda(cudaSetDevice(ctx->Ordinal()));
auto n = n_samples * n_features;
std::vector<float> x;
x.resize(n);
@@ -606,21 +607,21 @@ void TestGetColumnSize(std::size_t n_samples) {
std::vector<std::size_t> h_column_size_1(column_sizes_scan.size());
detail::LaunchGetColumnSizeKernel<decltype(batch_iter), true, true>(
ctx.gpu_id, IterSpan{batch_iter, batch.Size()}, is_valid, dh::ToSpan(column_sizes_scan));
ctx.Device(), IterSpan{batch_iter, batch.Size()}, is_valid, dh::ToSpan(column_sizes_scan));
thrust::copy(column_sizes_scan.begin(), column_sizes_scan.end(), h_column_size.begin());
detail::LaunchGetColumnSizeKernel<decltype(batch_iter), true, false>(
ctx.gpu_id, IterSpan{batch_iter, batch.Size()}, is_valid, dh::ToSpan(column_sizes_scan));
ctx.Device(), IterSpan{batch_iter, batch.Size()}, is_valid, dh::ToSpan(column_sizes_scan));
thrust::copy(column_sizes_scan.begin(), column_sizes_scan.end(), h_column_size_1.begin());
ASSERT_EQ(h_column_size, h_column_size_1);
detail::LaunchGetColumnSizeKernel<decltype(batch_iter), false, true>(
ctx.gpu_id, IterSpan{batch_iter, batch.Size()}, is_valid, dh::ToSpan(column_sizes_scan));
ctx.Device(), IterSpan{batch_iter, batch.Size()}, is_valid, dh::ToSpan(column_sizes_scan));
thrust::copy(column_sizes_scan.begin(), column_sizes_scan.end(), h_column_size_1.begin());
ASSERT_EQ(h_column_size, h_column_size_1);
detail::LaunchGetColumnSizeKernel<decltype(batch_iter), false, false>(
ctx.gpu_id, IterSpan{batch_iter, batch.Size()}, is_valid, dh::ToSpan(column_sizes_scan));
ctx.Device(), IterSpan{batch_iter, batch.Size()}, is_valid, dh::ToSpan(column_sizes_scan));
thrust::copy(column_sizes_scan.begin(), column_sizes_scan.end(), h_column_size_1.begin());
ASSERT_EQ(h_column_size, h_column_size_1);
}
@@ -697,9 +698,9 @@ void TestAdapterSketchFromWeights(bool with_group) {
size_t constexpr kRows = 300, kCols = 20, kBins = 256;
size_t constexpr kGroups = 10;
HostDeviceVector<float> storage;
std::string m =
RandomDataGenerator{kRows, kCols, 0}.Device(0).GenerateArrayInterface(
&storage);
std::string m = RandomDataGenerator{kRows, kCols, 0}
.Device(DeviceOrd::CUDA(0))
.GenerateArrayInterface(&storage);
MetaInfo info;
Context ctx;
auto& h_weights = info.weights_.HostVector();
@@ -718,14 +719,14 @@ void TestAdapterSketchFromWeights(bool with_group) {
info.SetInfo(ctx, "group", groups.data(), DataType::kUInt32, kGroups);
}
info.weights_.SetDevice(0);
info.weights_.SetDevice(DeviceOrd::CUDA(0));
info.num_row_ = kRows;
info.num_col_ = kCols;
data::CupyAdapter adapter(m);
auto const& batch = adapter.Value();
HostDeviceVector<FeatureType> ft;
SketchContainer sketch_container(ft, kBins, kCols, kRows, 0);
SketchContainer sketch_container(ft, kBins, kCols, kRows, DeviceOrd::CUDA(0));
AdapterDeviceSketch(adapter.Value(), kBins, info, std::numeric_limits<float>::quiet_NaN(),
&sketch_container);
@@ -769,7 +770,7 @@ void TestAdapterSketchFromWeights(bool with_group) {
// https://github.com/dmlc/xgboost/issues/7946
h_weights[i] = (i % 2 == 0 ? 1 : 2) / static_cast<float>(kGroups);
}
SketchContainer sketch_container(ft, kBins, kCols, kRows, 0);
SketchContainer sketch_container{ft, kBins, kCols, kRows, DeviceOrd::CUDA(0)};
AdapterDeviceSketch(adapter.Value(), kBins, info, std::numeric_limits<float>::quiet_NaN(),
&sketch_container);
sketch_container.MakeCuts(&weighted, info.IsColumnSplit());