Support categorical data in ellpack. (#6140)

src/data/ellpack_page.cu

@@ -1,10 +1,10 @@
 /*!
- * Copyright 2019 XGBoost contributors
+ * Copyright 2019-2020 XGBoost contributors
  */
-
 #include <xgboost/data.h>
 #include <thrust/iterator/discard_iterator.h>
 #include <thrust/iterator/transform_output_iterator.h>
+#include "../common/categorical.h"
 #include "../common/hist_util.cuh"
 #include "../common/random.h"
 #include "./ellpack_page.cuh"
@@ -33,6 +33,7 @@ __global__ void CompressBinEllpackKernel(
     const Entry* __restrict__ entries,      // One batch of input data
     const float* __restrict__ cuts,         // HistogramCuts::cut_values_
     const uint32_t* __restrict__ cut_rows,  // HistogramCuts::cut_ptrs_
+    common::Span<FeatureType const> feature_types,
     size_t base_row,                        // batch_row_begin
     size_t n_rows,
     size_t row_stride,
@@ -51,11 +52,19 @@ __global__ void CompressBinEllpackKernel(
     // {feature_cuts, ncuts} forms the array of cuts of `feature'.
     const float* feature_cuts = &cuts[cut_rows[feature]];
     int ncuts = cut_rows[feature + 1] - cut_rows[feature];
+    bool is_cat = common::IsCat(feature_types, ifeature);
     // Assigning the bin in current entry.
     // S.t.: fvalue < feature_cuts[bin]
-    bin = thrust::upper_bound(thrust::seq, feature_cuts, feature_cuts + ncuts,
-                              fvalue) -
-          feature_cuts;
+    if (is_cat) {
+      auto it = dh::MakeTransformIterator<int>(
+          feature_cuts, [](float v) { return common::AsCat(v); });
+      bin = thrust::lower_bound(thrust::seq, it, it + ncuts, common::AsCat(fvalue)) - it;
+    } else {
+      bin = thrust::upper_bound(thrust::seq, feature_cuts, feature_cuts + ncuts,
+                                fvalue) -
+            feature_cuts;
+    }
+
     if (bin >= ncuts) {
       bin = ncuts - 1;
     }
@@ -83,14 +92,13 @@ EllpackPageImpl::EllpackPageImpl(int device, common::HistogramCuts cuts,
 }
 
 EllpackPageImpl::EllpackPageImpl(int device, common::HistogramCuts cuts,
-                                 const SparsePage& page, bool is_dense,
-                                 size_t row_stride)
-    : cuts_(std::move(cuts)),
-      is_dense(is_dense),
-      n_rows(page.Size()),
+                                 const SparsePage &page, bool is_dense,
+                                 size_t row_stride,
+                                 common::Span<FeatureType const> feature_types)
+    : cuts_(std::move(cuts)), is_dense(is_dense), n_rows(page.Size()),
       row_stride(row_stride) {
   this->InitCompressedData(device);
-  this->CreateHistIndices(device, page);
+  this->CreateHistIndices(device, page, feature_types);
 }
 
 // Construct an ELLPACK matrix in memory.
@@ -108,12 +116,14 @@ EllpackPageImpl::EllpackPageImpl(DMatrix* dmat, const BatchParam& param)
   monitor_.Stop("Quantiles");
 
   monitor_.Start("InitCompressedData");
-  InitCompressedData(param.gpu_id);
+  this->InitCompressedData(param.gpu_id);
   monitor_.Stop("InitCompressedData");
 
+  dmat->Info().feature_types.SetDevice(param.gpu_id);
+  auto ft = dmat->Info().feature_types.ConstDeviceSpan();
   monitor_.Start("BinningCompression");
   for (const auto& batch : dmat->GetBatches<SparsePage>()) {
-    CreateHistIndices(param.gpu_id, batch);
+    CreateHistIndices(param.gpu_id, batch, ft);
   }
   monitor_.Stop("BinningCompression");
 }
@@ -365,7 +375,8 @@ void EllpackPageImpl::InitCompressedData(int device) {
 
 // Compress a CSR page into ELLPACK.
 void EllpackPageImpl::CreateHistIndices(int device,
-                                        const SparsePage& row_batch) {
+                                        const SparsePage& row_batch,
+                                        common::Span<FeatureType const> feature_types) {
   if (row_batch.Size() == 0) return;
   unsigned int null_gidx_value = NumSymbols() - 1;
 
@@ -397,9 +408,9 @@ void EllpackPageImpl::CreateHistIndices(int device,
     size_t n_entries = ent_cnt_end - ent_cnt_begin;
     dh::device_vector<Entry> entries_d(n_entries);
     // copy data entries to device.
-    dh::safe_cuda(cudaMemcpy(entries_d.data().get(),
-                             data_vec.data() + ent_cnt_begin,
-                             n_entries * sizeof(Entry), cudaMemcpyDefault));
+    dh::safe_cuda(cudaMemcpyAsync(entries_d.data().get(),
+                                  data_vec.data() + ent_cnt_begin,
+                                  n_entries * sizeof(Entry), cudaMemcpyDefault));
     const dim3 block3(32, 8, 1);  // 256 threads
     const dim3 grid3(common::DivRoundUp(batch_nrows, block3.x),
                      common::DivRoundUp(row_stride, block3.y), 1);
@@ -408,7 +419,7 @@ void EllpackPageImpl::CreateHistIndices(int device,
         CompressBinEllpackKernel, common::CompressedBufferWriter(NumSymbols()),
         gidx_buffer.DevicePointer(), row_ptrs.data().get(),
         entries_d.data().get(), device_accessor.gidx_fvalue_map.data(),
-        device_accessor.feature_segments.data(),
+        device_accessor.feature_segments.data(), feature_types,
         row_batch.base_rowid + batch_row_begin, batch_nrows, row_stride,
         null_gidx_value);
   }

src/data/ellpack_page.cuh

@@ -118,10 +118,12 @@ class EllpackPageImpl {
    */
   EllpackPageImpl(int device, common::HistogramCuts cuts, bool is_dense,
                   size_t row_stride, size_t n_rows);
-
+  /*!
+   * \brief Constructor used for external memory.
+   */
   EllpackPageImpl(int device, common::HistogramCuts cuts,
-                  const SparsePage& page,
-                  bool is_dense, size_t row_stride);
+                  const SparsePage &page, bool is_dense, size_t row_stride,
+                  common::Span<FeatureType const> feature_types);
 
   /*!
    * \brief Constructor from an existing DMatrix.
@@ -184,8 +186,8 @@ class EllpackPageImpl {
    * @param row_batch The CSR page.
    */
   void CreateHistIndices(int device,
-                         const SparsePage& row_batch
-                         );
+                         const SparsePage& row_batch,
+                         common::Span<FeatureType const> feature_types);
   /*!
    * \brief Initialize the buffer to store compressed features.
    */

src/data/ellpack_page_source.cu

@@ -55,6 +55,7 @@ void EllpackPageSource::WriteEllpackPages(int device, DMatrix* dmat,
   SparsePage temp_host_page;
   writer.Alloc(&page);
   auto* impl = page->Impl();
+  auto ft = dmat->Info().feature_types.ConstDeviceSpan();
 
   size_t bytes_write = 0;
   double tstart = dmlc::GetTime();
@@ -66,7 +67,7 @@ void EllpackPageSource::WriteEllpackPages(int device, DMatrix* dmat,
     if (mem_cost_bytes >= page_size_) {
       bytes_write += mem_cost_bytes;
       *impl = EllpackPageImpl(device, cuts, temp_host_page, dmat->IsDense(),
-                              row_stride);
+                              row_stride, ft);
       writer.PushWrite(std::move(page));
       writer.Alloc(&page);
       impl = page->Impl();
@@ -79,7 +80,7 @@ void EllpackPageSource::WriteEllpackPages(int device, DMatrix* dmat,
   }
   if (temp_host_page.Size() != 0) {
     *impl = EllpackPageImpl(device, cuts, temp_host_page, dmat->IsDense(),
-                            row_stride);
+                            row_stride, ft);
     writer.PushWrite(std::move(page));
   }
 }

tests/cpp/common/test_hist_util.h

@@ -60,19 +60,6 @@ inline data::CupyAdapter AdapterFromData(const thrust::device_vector<float> &x,
 }
 #endif
 
-inline std::vector<float> GenerateRandomCategoricalSingleColumn(int n,
-                                                                int num_categories) {
-  std::vector<float> x(n);
-  std::mt19937 rng(0);
-  std::uniform_int_distribution<int> dist(0, num_categories - 1);
-  std::generate(x.begin(), x.end(), [&]() { return dist(rng); });
-  // Make sure each category is present
-  for(auto i = 0; i < num_categories; i++) {
-    x[i] = i;
-  }
-  return x;
-}
-
 inline std::shared_ptr<data::SimpleDMatrix>
 GetDMatrixFromData(const std::vector<float> &x, int num_rows, int num_columns) {
   data::DenseAdapter adapter(x.data(), num_rows, num_columns);

tests/cpp/data/test_ellpack_page.cu

@@ -1,5 +1,5 @@
 /*!
- * Copyright 2019 XGBoost contributors
+ * Copyright 2019-2020 XGBoost contributors
  */
 #include <xgboost/base.h>
 
@@ -9,6 +9,7 @@
 #include "../histogram_helpers.h"
 #include "gtest/gtest.h"
 
+#include "../../../src/common/categorical.h"
 #include "../../../src/common/hist_util.h"
 #include "../../../src/data/ellpack_page.cuh"
 
@@ -77,6 +78,45 @@ TEST(EllpackPage, BuildGidxSparse) {
   }
 }
 
+TEST(EllpackPage, FromCategoricalBasic) {
+  using common::AsCat;
+  size_t constexpr kRows = 1000, kCats = 13, kCols = 1;
+  size_t max_bins = 8;
+  auto x = GenerateRandomCategoricalSingleColumn(kRows, kCats);
+  auto m = GetDMatrixFromData(x, kRows, 1);
+  auto& h_ft = m->Info().feature_types.HostVector();
+  h_ft.resize(kCols, FeatureType::kCategorical);
+
+  BatchParam p(0, max_bins);
+  auto ellpack = EllpackPage(m.get(), p);
+  auto accessor = ellpack.Impl()->GetDeviceAccessor(0);
+  ASSERT_EQ(kCats, accessor.NumBins());
+
+  auto x_copy = x;
+  std::sort(x_copy.begin(), x_copy.end());
+  auto n_uniques = std::unique(x_copy.begin(), x_copy.end()) - x_copy.begin();
+  ASSERT_EQ(n_uniques, kCats);
+
+  std::vector<uint32_t> h_cuts_ptr(accessor.feature_segments.size());
+  dh::CopyDeviceSpanToVector(&h_cuts_ptr, accessor.feature_segments);
+  std::vector<float> h_cuts_values(accessor.gidx_fvalue_map.size());
+  dh::CopyDeviceSpanToVector(&h_cuts_values, accessor.gidx_fvalue_map);
+
+  ASSERT_EQ(h_cuts_ptr.size(), 2);
+  ASSERT_EQ(h_cuts_values.size(), kCats);
+
+  std::vector<common::CompressedByteT> const &h_gidx_buffer =
+      ellpack.Impl()->gidx_buffer.HostVector();
+  auto h_gidx_iter = common::CompressedIterator<uint32_t>(
+      h_gidx_buffer.data(), accessor.NumSymbols());
+
+  for (size_t i = 0; i < x.size(); ++i) {
+    auto bin = h_gidx_iter[i];
+    auto bin_value = h_cuts_values.at(bin);
+    ASSERT_EQ(AsCat(x[i]), AsCat(bin_value));
+  }
+}
+
 struct ReadRowFunction {
   EllpackDeviceAccessor matrix;
   int row;

tests/cpp/helpers.cc

@@ -17,6 +17,7 @@
 #include "helpers.h"
 #include "xgboost/c_api.h"
 #include "../../src/data/adapter.h"
+#include "../../src/data/simple_dmatrix.h"
 #include "../../src/gbm/gbtree_model.h"
 #include "xgboost/predictor.h"
 
@@ -350,6 +351,13 @@ RandomDataGenerator::GenerateDMatrix(bool with_label, bool float_label,
   return out;
 }
 
+std::shared_ptr<DMatrix>
+GetDMatrixFromData(const std::vector<float> &x, int num_rows, int num_columns){
+  data::DenseAdapter adapter(x.data(), num_rows, num_columns);
+  return std::shared_ptr<DMatrix>(new data::SimpleDMatrix(
+      &adapter, std::numeric_limits<float>::quiet_NaN(), 1));
+}
+
 std::unique_ptr<DMatrix> CreateSparsePageDMatrix(
     size_t n_entries, size_t page_size, std::string tmp_file) {
   // Create sufficiently large data to make two row pages
@@ -539,5 +547,4 @@ RMMAllocatorPtr SetUpRMMResourceForCppTests(int argc, char** argv) {
   return RMMAllocatorPtr(nullptr, DeleteRMMResource);
 }
 #endif  // !defined(XGBOOST_USE_RMM) || XGBOOST_USE_RMM != 1
-
 }  // namespace xgboost

tests/cpp/helpers.h

@@ -42,6 +42,12 @@ struct LearnerModelParam;
 class GradientBooster;
 }
 
+template <typename Float>
+Float RelError(Float l, Float r) {
+  static_assert(std::is_floating_point<Float>::value, "");
+  return std::abs(1.0f - l / r);
+}
+
 bool FileExists(const std::string& filename);
 
 int64_t GetFileSize(const std::string& filename);
@@ -254,6 +260,22 @@ class RandomDataGenerator {
 #endif
 };
 
+inline std::vector<float>
+GenerateRandomCategoricalSingleColumn(int n, size_t num_categories) {
+  std::vector<float> x(n);
+  std::mt19937 rng(0);
+  std::uniform_int_distribution<size_t> dist(0, num_categories - 1);
+  std::generate(x.begin(), x.end(), [&]() { return dist(rng); });
+  // Make sure each category is present
+  for(size_t i = 0; i < num_categories; i++) {
+    x[i] = i;
+  }
+  return x;
+}
+
+std::shared_ptr<DMatrix> GetDMatrixFromData(const std::vector<float> &x,
+                                            int num_rows, int num_columns);
+
 std::unique_ptr<DMatrix> CreateSparsePageDMatrix(
     size_t n_entries, size_t page_size, std::string tmp_file);
 

tests/cpp/histogram_helpers.h

@@ -45,7 +45,7 @@ inline std::unique_ptr<EllpackPageImpl> BuildEllpackPage(
   }
 
   auto page = std::unique_ptr<EllpackPageImpl>(
-      new EllpackPageImpl(0, cmat, batch, dmat->IsDense(), row_stride));
+      new EllpackPageImpl(0, cmat, batch, dmat->IsDense(), row_stride, {}));
 
   return page;
 }