Check inf in data for all types of DMatrix. (#8911)

src/data/data.cc

@@ -10,13 +10,16 @@
 #include <cstring>
 
 #include "../collective/communicator-inl.h"
-#include "../common/algorithm.h"  // StableSort
-#include "../common/api_entry.h"  // XGBAPIThreadLocalEntry
+#include "../collective/communicator.h"
+#include "../common/common.h"
+#include "../common/algorithm.h"  // for StableSort
+#include "../common/api_entry.h"  // for XGBAPIThreadLocalEntry
+#include "../common/error_msg.h"  // for InfInData
 #include "../common/group_data.h"
 #include "../common/io.h"
 #include "../common/linalg_op.h"
 #include "../common/math.h"
-#include "../common/numeric.h"  // Iota
+#include "../common/numeric.h"  // for Iota
 #include "../common/threading_utils.h"
 #include "../common/version.h"
 #include "../data/adapter.h"
@@ -1144,7 +1147,7 @@ uint64_t SparsePage::Push(const AdapterBatchT& batch, float missing, int nthread
     });
   }
   exec.Rethrow();
-  CHECK(valid) << "Input data contains `inf` or `nan`";
+  CHECK(valid) << error::InfInData();
   for (const auto & max : max_columns_vector) {
     max_columns = std::max(max_columns, max[0]);
   }

src/data/device_adapter.cuh

@@ -4,7 +4,10 @@
  */
 #ifndef XGBOOST_DATA_DEVICE_ADAPTER_H_
 #define XGBOOST_DATA_DEVICE_ADAPTER_H_
-#include <cstddef>  // for size_t
+#include <thrust/iterator/counting_iterator.h>  // for make_counting_iterator
+#include <thrust/logical.h>                     // for none_of
+
+#include <cstddef>                              // for size_t
 #include <limits>
 #include <memory>
 #include <string>
@@ -213,6 +216,20 @@ size_t GetRowCounts(const AdapterBatchT batch, common::Span<size_t> offset,
                  static_cast<std::size_t>(0), thrust::maximum<size_t>());
   return row_stride;
 }
+
+/**
+ * \brief Check there's no inf in data.
+ */
+template <typename AdapterBatchT>
+bool HasInfInData(AdapterBatchT const& batch, IsValidFunctor is_valid) {
+  auto counting = thrust::make_counting_iterator(0llu);
+  auto value_iter = dh::MakeTransformIterator<float>(
+      counting, [=] XGBOOST_DEVICE(std::size_t idx) { return batch.GetElement(idx).value; });
+  auto valid =
+      thrust::none_of(value_iter, value_iter + batch.Size(),
+                      [is_valid] XGBOOST_DEVICE(float v) { return is_valid(v) && std::isinf(v); });
+  return valid;
+}
 };  // namespace data
 }  // namespace xgboost
 #endif  // XGBOOST_DATA_DEVICE_ADAPTER_H_

src/data/ellpack_page.cu

@@ -1,5 +1,5 @@
-/*!
- * Copyright 2019-2022 XGBoost contributors
+/**
+ * Copyright 2019-2023 by XGBoost contributors
  */
 #include <thrust/iterator/discard_iterator.h>
 #include <thrust/iterator/transform_output_iterator.h>
@@ -9,7 +9,7 @@
 #include "../common/random.h"
 #include "../common/transform_iterator.h"  // MakeIndexTransformIter
 #include "./ellpack_page.cuh"
-#include "device_adapter.cuh"
+#include "device_adapter.cuh"  // for HasInfInData
 #include "gradient_index.h"
 #include "xgboost/data.h"
 
@@ -189,9 +189,8 @@ struct TupleScanOp {
 // Here the data is already correctly ordered and simply needs to be compacted
 // to remove missing data
 template <typename AdapterBatchT>
-void CopyDataToEllpack(const AdapterBatchT &batch,
-                       common::Span<FeatureType const> feature_types,
-                       EllpackPageImpl *dst, int device_idx, float missing) {
+void CopyDataToEllpack(const AdapterBatchT& batch, common::Span<FeatureType const> feature_types,
+                       EllpackPageImpl* dst, int device_idx, float missing) {
   // Some witchcraft happens here
   // The goal is to copy valid elements out of the input to an ELLPACK matrix
   // with a given row stride, using no extra working memory Standard stream
@@ -201,6 +200,9 @@ void CopyDataToEllpack(const AdapterBatchT &batch,
   // correct output position
   auto counting = thrust::make_counting_iterator(0llu);
   data::IsValidFunctor is_valid(missing);
+  bool valid = data::HasInfInData(batch, is_valid);
+  CHECK(valid) << error::InfInData();
+
   auto key_iter = dh::MakeTransformIterator<size_t>(
       counting,
       [=] __device__(size_t idx) {
@@ -239,9 +241,9 @@ void CopyDataToEllpack(const AdapterBatchT &batch,
       cub::DispatchScan<decltype(key_value_index_iter), decltype(out),
                         TupleScanOp<Tuple>, cub::NullType, int64_t>;
 #if THRUST_MAJOR_VERSION >= 2
-  DispatchScan::Dispatch(nullptr, temp_storage_bytes, key_value_index_iter, out,
-                         TupleScanOp<Tuple>(), cub::NullType(), batch.Size(),
-                         nullptr);
+  dh::safe_cuda(DispatchScan::Dispatch(nullptr, temp_storage_bytes, key_value_index_iter, out,
+                                       TupleScanOp<Tuple>(), cub::NullType(), batch.Size(),
+                                       nullptr));
 #else
   DispatchScan::Dispatch(nullptr, temp_storage_bytes, key_value_index_iter, out,
                          TupleScanOp<Tuple>(), cub::NullType(), batch.Size(),
@@ -249,9 +251,9 @@ void CopyDataToEllpack(const AdapterBatchT &batch,
 #endif
   dh::TemporaryArray<char> temp_storage(temp_storage_bytes);
 #if THRUST_MAJOR_VERSION >= 2
-  DispatchScan::Dispatch(temp_storage.data().get(), temp_storage_bytes,
-                         key_value_index_iter, out, TupleScanOp<Tuple>(),
-                         cub::NullType(), batch.Size(), nullptr);
+  dh::safe_cuda(DispatchScan::Dispatch(temp_storage.data().get(), temp_storage_bytes,
+                                       key_value_index_iter, out, TupleScanOp<Tuple>(),
+                                       cub::NullType(), batch.Size(), nullptr));
 #else
   DispatchScan::Dispatch(temp_storage.data().get(), temp_storage_bytes,
                          key_value_index_iter, out, TupleScanOp<Tuple>(),

src/data/gradient_index.h

@@ -1,21 +1,23 @@
-/*!
- * Copyright 2017-2022 by XGBoost Contributors
+/**
+ * Copyright 2017-2023 by XGBoost Contributors
  * \brief Data type for fast histogram aggregation.
  */
 #ifndef XGBOOST_DATA_GRADIENT_INDEX_H_
 #define XGBOOST_DATA_GRADIENT_INDEX_H_
 
-#include <algorithm>  // std::min
-#include <cinttypes>  // std::uint32_t
-#include <cstddef>    // std::size_t
+#include <algorithm>  // for min
+#include <atomic>     // for atomic
+#include <cinttypes>  // for uint32_t
+#include <cstddef>    // for size_t
 #include <memory>
 #include <vector>
 
 #include "../common/categorical.h"
+#include "../common/error_msg.h"  // for InfInData
 #include "../common/hist_util.h"
 #include "../common/numeric.h"
 #include "../common/threading_utils.h"
-#include "../common/transform_iterator.h"  // common::MakeIndexTransformIter
+#include "../common/transform_iterator.h"  // for MakeIndexTransformIter
 #include "adapter.h"
 #include "proxy_dmatrix.h"
 #include "xgboost/base.h"
@@ -62,6 +64,7 @@ class GHistIndexMatrix {
     BinIdxType* index_data = index_data_span.data();
     auto const& ptrs = cut.Ptrs();
     auto const& values = cut.Values();
+    std::atomic<bool> valid{true};
     common::ParallelFor(batch_size, batch_threads, [&](size_t i) {
       auto line = batch.GetLine(i);
       size_t ibegin = row_ptr[rbegin + i];  // index of first entry for current block
@@ -70,6 +73,9 @@ class GHistIndexMatrix {
       for (size_t j = 0; j < line.Size(); ++j) {
         data::COOTuple elem = line.GetElement(j);
         if (is_valid(elem)) {
+          if (XGBOOST_EXPECT((std::isinf(elem.value)), false)) {
+            valid = false;
+          }
           bst_bin_t bin_idx{-1};
           if (common::IsCat(ft, elem.column_idx)) {
             bin_idx = cut.SearchCatBin(elem.value, elem.column_idx, ptrs, values);
@@ -82,6 +88,8 @@ class GHistIndexMatrix {
         }
       }
     });
+
+    CHECK(valid) << error::InfInData();
   }
 
   // Gather hit_count from all threads

src/data/simple_dmatrix.cuh

@@ -1,18 +1,19 @@
-/*!
- * Copyright 2019-2021 by XGBoost Contributors
+/**
+ * Copyright 2019-2023 by XGBoost Contributors
  * \file simple_dmatrix.cuh
  */
 #ifndef XGBOOST_DATA_SIMPLE_DMATRIX_CUH_
 #define XGBOOST_DATA_SIMPLE_DMATRIX_CUH_
 
 #include <thrust/copy.h>
-#include <thrust/scan.h>
 #include <thrust/execution_policy.h>
-#include "device_adapter.cuh"
-#include "../common/device_helpers.cuh"
+#include <thrust/scan.h>
 
-namespace xgboost {
-namespace data {
+#include "../common/device_helpers.cuh"
+#include "../common/error_msg.h"  // for InfInData
+#include "device_adapter.cuh"     // for HasInfInData
+
+namespace xgboost::data {
 
 template <typename AdapterBatchT>
 struct COOToEntryOp {
@@ -61,7 +62,11 @@ void CountRowOffsets(const AdapterBatchT& batch, common::Span<bst_row_t> offset,
 }
 
 template <typename AdapterBatchT>
-size_t CopyToSparsePage(AdapterBatchT const& batch, int32_t device, float missing, SparsePage* page) {
+size_t CopyToSparsePage(AdapterBatchT const& batch, int32_t device, float missing,
+                        SparsePage* page) {
+  bool valid = HasInfInData(batch, IsValidFunctor{missing});
+  CHECK(valid) << error::InfInData();
+
   page->offset.SetDevice(device);
   page->data.SetDevice(device);
   page->offset.Resize(batch.NumRows() + 1);
@@ -73,6 +78,5 @@ size_t CopyToSparsePage(AdapterBatchT const& batch, int32_t device, float missin
 
   return num_nonzero_;
 }
-}  // namespace data
-}  // namespace xgboost
+}  // namespace xgboost::data
 #endif  // XGBOOST_DATA_SIMPLE_DMATRIX_CUH_