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Purge device_helpers.cuh (#5534)

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* Simplifications with caching_device_vector

* Purge device helpers
This commit is contained in:
Rory Mitchell
2020-04-15 21:51:56 +12:00
committed by GitHub
parent a2f54963b6
commit ca4e05660e
9 changed files with 182 additions and 733 deletions
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60
tests/cpp/tree/test_gpu_hist.cu
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@@ -24,37 +24,33 @@ namespace tree {
TEST(GpuHist, DeviceHistogram) {
// Ensures that node allocates correctly after reaching `kStopGrowingSize`.
dh::SaveCudaContext{
[&]() {
dh::safe_cuda(cudaSetDevice(0));
constexpr size_t kNBins = 128;
constexpr size_t kNNodes = 4;
constexpr size_t kStopGrowing = kNNodes * kNBins * 2u;
DeviceHistogram<GradientPairPrecise, kStopGrowing> histogram;
histogram.Init(0, kNBins);
for (size_t i = 0; i < kNNodes; ++i) {
histogram.AllocateHistogram(i);
}
histogram.Reset();
ASSERT_EQ(histogram.Data().size(), kStopGrowing);
dh::safe_cuda(cudaSetDevice(0));
constexpr size_t kNBins = 128;
constexpr size_t kNNodes = 4;
constexpr size_t kStopGrowing = kNNodes * kNBins * 2u;
DeviceHistogram<GradientPairPrecise, kStopGrowing> histogram;
histogram.Init(0, kNBins);
for (size_t i = 0; i < kNNodes; ++i) {
histogram.AllocateHistogram(i);
}
histogram.Reset();
ASSERT_EQ(histogram.Data().size(), kStopGrowing);
// Use allocated memory but do not erase nidx_map.
for (size_t i = 0; i < kNNodes; ++i) {
histogram.AllocateHistogram(i);
}
for (size_t i = 0; i < kNNodes; ++i) {
ASSERT_TRUE(histogram.HistogramExists(i));
}
// Use allocated memory but do not erase nidx_map.
for (size_t i = 0; i < kNNodes; ++i) {
histogram.AllocateHistogram(i);
}
for (size_t i = 0; i < kNNodes; ++i) {
ASSERT_TRUE(histogram.HistogramExists(i));
}
// Erase existing nidx_map.
for (size_t i = kNNodes; i < kNNodes * 2; ++i) {
histogram.AllocateHistogram(i);
}
for (size_t i = 0; i < kNNodes; ++i) {
ASSERT_FALSE(histogram.HistogramExists(i));
}
}
};
// Erase existing nidx_map.
for (size_t i = kNNodes; i < kNNodes * 2; ++i) {
histogram.AllocateHistogram(i);
}
for (size_t i = 0; i < kNNodes; ++i) {
ASSERT_FALSE(histogram.HistogramExists(i));
}
}
std::vector<GradientPairPrecise> GetHostHistGpair() {
@@ -187,16 +183,14 @@ TEST(GpuHist, EvaluateSplits) {
GPUHistMakerDevice<GradientPairPrecise>
maker(0, page.get(), kNRows, param, kNCols, kNCols, true, batch_param);
// Initialize GPUHistMakerDevice::node_sum_gradients
maker.node_sum_gradients = {{6.4f, 12.8f}};
maker.host_node_sum_gradients = {{6.4f, 12.8f}};
// Initialize GPUHistMakerDevice::cut
auto cmat = GetHostCutMatrix();
// Copy cut matrix to device.
page->Cuts() = cmat;
maker.ba.Allocate(0, &(maker.monotone_constraints), kNCols);
dh::CopyVectorToDeviceSpan(maker.monotone_constraints,
param.monotone_constraints);
maker.monotone_constraints = param.monotone_constraints;
// Initialize GPUHistMakerDevice::hist
maker.hist.Init(0, (max_bins - 1) * kNCols);