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Move ellpack page construction into DMatrix (#4833)

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This commit is contained in:
Rong Ou
2019-09-16 20:50:55 -07:00
committed by Jiaming Yuan
parent 512f037e55
commit 125bcec62e
17 changed files with 761 additions and 513 deletions
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118
tests/cpp/tree/test_gpu_hist.cu
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@@ -98,82 +98,13 @@ void BuildGidx(DeviceShard<GradientSumT>* shard, int n_rows, int n_cols,
for (size_t i = 1; i < offset_vec.size(); ++i) {
row_stride = std::max(row_stride, offset_vec[i] - offset_vec[i-1]);
}
shard->InitCompressedData(cmat, row_stride, is_dense);
shard->InitHistogram(cmat, row_stride, is_dense);
shard->CreateHistIndices(
batch, cmat, RowStateOnDevice(batch.Size(), batch.Size()), -1);
delete dmat;
}
TEST(GpuHist, BuildGidxDense) {
int constexpr kNRows = 16, kNCols = 8;
tree::TrainParam param;
std::vector<std::pair<std::string, std::string>> args {
{"max_depth", "1"},
{"max_leaves", "0"},
};
param.Init(args);
DeviceShard<GradientPairPrecise> shard(0, kNRows, param, kNCols, kNCols);
BuildGidx(&shard, kNRows, kNCols);
std::vector<common::CompressedByteT> h_gidx_buffer(shard.gidx_buffer.size());
dh::CopyDeviceSpanToVector(&h_gidx_buffer, shard.gidx_buffer);
common::CompressedIterator<uint32_t> gidx(h_gidx_buffer.data(), 25);
ASSERT_EQ(shard.ellpack_matrix.row_stride, kNCols);
std::vector<uint32_t> solution = {
0, 3, 8, 9, 14, 17, 20, 21,
0, 4, 7, 10, 14, 16, 19, 22,
1, 3, 7, 11, 14, 15, 19, 21,
2, 3, 7, 9, 13, 16, 20, 22,
2, 3, 6, 9, 12, 16, 20, 21,
1, 5, 6, 10, 13, 16, 20, 21,
2, 5, 8, 9, 13, 17, 19, 22,
2, 4, 6, 10, 14, 17, 19, 21,
2, 5, 7, 9, 13, 16, 19, 22,
0, 3, 8, 10, 12, 16, 19, 22,
1, 3, 7, 10, 13, 16, 19, 21,
1, 3, 8, 10, 13, 17, 20, 22,
2, 4, 6, 9, 14, 15, 19, 22,
1, 4, 6, 9, 13, 16, 19, 21,
2, 4, 8, 10, 14, 15, 19, 22,
1, 4, 7, 10, 14, 16, 19, 21,
};
for (size_t i = 0; i < kNRows * kNCols; ++i) {
ASSERT_EQ(solution[i], gidx[i]);
}
}
TEST(GpuHist, BuildGidxSparse) {
int constexpr kNRows = 16, kNCols = 8;
TrainParam param;
std::vector<std::pair<std::string, std::string>> args {
{"max_depth", "1"},
{"max_leaves", "0"},
};
param.Init(args);
DeviceShard<GradientPairPrecise> shard(0, kNRows, param, kNCols, kNCols);
BuildGidx(&shard, kNRows, kNCols, 0.9f);
std::vector<common::CompressedByteT> h_gidx_buffer(shard.gidx_buffer.size());
dh::CopyDeviceSpanToVector(&h_gidx_buffer, shard.gidx_buffer);
common::CompressedIterator<uint32_t> gidx(h_gidx_buffer.data(), 25);
ASSERT_LE(shard.ellpack_matrix.row_stride, 3);
// row_stride = 3, 16 rows, 48 entries for ELLPack
std::vector<uint32_t> solution = {
15, 24, 24, 0, 24, 24, 24, 24, 24, 24, 24, 24, 20, 24, 24, 24,
24, 24, 24, 24, 24, 5, 24, 24, 0, 16, 24, 15, 24, 24, 24, 24,
24, 7, 14, 16, 4, 24, 24, 24, 24, 24, 9, 24, 24, 1, 24, 24
};
for (size_t i = 0; i < kNRows * shard.ellpack_matrix.row_stride; ++i) {
ASSERT_EQ(solution[i], gidx[i]);
}
}
std::vector<GradientPairPrecise> GetHostHistGpair() {
// 24 bins, 3 bins for each feature (column).
std::vector<GradientPairPrecise> hist_gpair = {
@@ -199,9 +130,10 @@ void TestBuildHist(bool use_shared_memory_histograms) {
{"max_leaves", "0"},
};
param.Init(args);
DeviceShard<GradientSumT> shard(0, kNRows, param, kNCols, kNCols);
BuildGidx(&shard, kNRows, kNCols);
auto page = BuildEllpackPage(kNRows, kNCols);
DeviceShard<GradientSumT> shard(0, page.get(), kNRows, param, kNCols, kNCols);
shard.InitHistogram();
xgboost::SimpleLCG gen;
xgboost::SimpleRealUniformDistribution<bst_float> dist(0.0f, 1.0f);
std::vector<GradientPair> h_gpair(kNRows);
@@ -211,12 +143,11 @@ void TestBuildHist(bool use_shared_memory_histograms) {
gpair = GradientPair(grad, hess);
}
thrust::host_vector<common::CompressedByteT> h_gidx_buffer (
shard.gidx_buffer.size());
thrust::host_vector<common::CompressedByteT> h_gidx_buffer (page->gidx_buffer.size());
common::CompressedByteT* d_gidx_buffer_ptr = shard.gidx_buffer.data();
common::CompressedByteT* d_gidx_buffer_ptr = page->gidx_buffer.data();
dh::safe_cuda(cudaMemcpy(h_gidx_buffer.data(), d_gidx_buffer_ptr,
sizeof(common::CompressedByteT) * shard.gidx_buffer.size(),
sizeof(common::CompressedByteT) * page->gidx_buffer.size(),
cudaMemcpyDeviceToHost));
shard.row_partitioner.reset(new RowPartitioner(0, kNRows));
@@ -300,8 +231,9 @@ TEST(GpuHist, EvaluateSplits) {
int max_bins = 4;
// Initialize DeviceShard
auto page = BuildEllpackPage(kNRows, kNCols);
std::unique_ptr<DeviceShard<GradientPairPrecise>> shard{
new DeviceShard<GradientPairPrecise>(0, kNRows, param, kNCols, kNCols)};
new DeviceShard<GradientPairPrecise>(0, page.get(), kNRows, param, kNCols, kNCols)};
// Initialize DeviceShard::node_sum_gradients
shard->node_sum_gradients = {{6.4f, 12.8f}};
@@ -310,18 +242,14 @@ TEST(GpuHist, EvaluateSplits) {
// Copy cut matrix to device.
shard->ba.Allocate(0,
&(shard->feature_segments), cmat.Ptrs().size(),
&(shard->min_fvalue), cmat.MinValues().size(),
&(shard->gidx_fvalue_map), 24,
&(page->ellpack_matrix.feature_segments), cmat.Ptrs().size(),
&(page->ellpack_matrix.min_fvalue), cmat.MinValues().size(),
&(page->ellpack_matrix.gidx_fvalue_map), 24,
&(shard->monotone_constraints), kNCols);
dh::CopyVectorToDeviceSpan(shard->feature_segments, cmat.Ptrs());
dh::CopyVectorToDeviceSpan(shard->gidx_fvalue_map, cmat.Values());
dh::CopyVectorToDeviceSpan(shard->monotone_constraints,
param.monotone_constraints);
shard->ellpack_matrix.feature_segments = shard->feature_segments;
shard->ellpack_matrix.gidx_fvalue_map = shard->gidx_fvalue_map;
dh::CopyVectorToDeviceSpan(shard->min_fvalue, cmat.MinValues());
shard->ellpack_matrix.min_fvalue = shard->min_fvalue;
dh::CopyVectorToDeviceSpan(page->ellpack_matrix.feature_segments, cmat.Ptrs());
dh::CopyVectorToDeviceSpan(page->ellpack_matrix.gidx_fvalue_map, cmat.Values());
dh::CopyVectorToDeviceSpan(shard->monotone_constraints, param.monotone_constraints);
dh::CopyVectorToDeviceSpan(page->ellpack_matrix.min_fvalue, cmat.MinValues());
// Initialize DeviceShard::hist
shard->hist.Init(0, (max_bins - 1) * kNCols);
@@ -391,15 +319,15 @@ void TestHistogramIndexImpl() {
// Extract the device shard from the histogram makers and from that its compressed
// histogram index
const auto &dev_shard = hist_maker.shard_;
std::vector<common::CompressedByteT> h_gidx_buffer(dev_shard->gidx_buffer.size());
dh::CopyDeviceSpanToVector(&h_gidx_buffer, dev_shard->gidx_buffer);
std::vector<common::CompressedByteT> h_gidx_buffer(dev_shard->page->gidx_buffer.size());
dh::CopyDeviceSpanToVector(&h_gidx_buffer, dev_shard->page->gidx_buffer);
const auto &dev_shard_ext = hist_maker_ext.shard_;
std::vector<common::CompressedByteT> h_gidx_buffer_ext(dev_shard_ext->gidx_buffer.size());
dh::CopyDeviceSpanToVector(&h_gidx_buffer_ext, dev_shard_ext->gidx_buffer);
std::vector<common::CompressedByteT> h_gidx_buffer_ext(dev_shard_ext->page->gidx_buffer.size());
dh::CopyDeviceSpanToVector(&h_gidx_buffer_ext, dev_shard_ext->page->gidx_buffer);
ASSERT_EQ(dev_shard->n_bins, dev_shard_ext->n_bins);
ASSERT_EQ(dev_shard->gidx_buffer.size(), dev_shard_ext->gidx_buffer.size());
ASSERT_EQ(dev_shard->page->n_bins, dev_shard_ext->page->n_bins);
ASSERT_EQ(dev_shard->page->gidx_buffer.size(), dev_shard_ext->page->gidx_buffer.size());
ASSERT_EQ(h_gidx_buffer, h_gidx_buffer_ext);
}