diff --git a/include/xgboost/linalg.h b/include/xgboost/linalg.h
index e4449bb8986b..b4fea37de09e 100644
--- a/include/xgboost/linalg.h
+++ b/include/xgboost/linalg.h
@@ -6,10 +6,12 @@
 #ifndef XGBOOST_LINALG_H_
 #define XGBOOST_LINALG_H_
 
+#include <xgboost/base.h>
 #include <xgboost/generic_parameters.h>
 #include <xgboost/span.h>
 
 #include <algorithm>
+#include <cassert>
 #include <type_traits>
 #include <utility>
 #include <vector>
@@ -24,8 +26,7 @@ constexpr size_t Offset(S (&strides)[D], size_t n, size_t dim, Head head) {
 }
 
 template <typename S, size_t D, typename Head, typename... Tail>
-constexpr size_t Offset(S (&strides)[D], size_t n, size_t dim, Head head,
-                        Tail &&...rest) {
+constexpr size_t Offset(S (&strides)[D], size_t n, size_t dim, Head head, Tail &&...rest) {
   assert(dim < D);
   return Offset(strides, n + (head * strides[dim]), dim + 1, rest...);
 }
@@ -36,7 +37,8 @@ struct IntTag {};
 /**
  * \brief Calculate the dimension of sliced tensor.
  */
-template <typename T> constexpr int32_t CalcSliceDim() {
+template <typename T>
+constexpr int32_t CalcSliceDim() {
   return std::is_same<T, IntTag>::value ? 0 : 1;
 }
 
@@ -49,8 +51,7 @@ template <typename S>
 using RemoveCRType = std::remove_const_t<std::remove_reference_t<S>>;
 
 template <typename S>
-using IndexToTag = std::conditional_t<std::is_integral<RemoveCRType<S>>::value,
-                                      IntTag, AllTag>;
+using IndexToTag = std::conditional_t<std::is_integral<RemoveCRType<S>>::value, IntTag, AllTag>;
 
 template <int32_t n, typename Fn>
 constexpr XGBOOST_DEVICE auto UnrollLoop(Fn fn) {
@@ -74,7 +75,8 @@ constexpr detail::AllTag All() { return {}; }
  * \brief A tensor view with static type and shape, it implements indexing and
  *        slicing.
  */
-template <typename T, int32_t kDim = 5> class TensorView {
+template <typename T, int32_t kDim = 5>
+class TensorView {
   using ShapeT = size_t[kDim];
   using StrideT = ShapeT;
 
@@ -102,40 +104,34 @@ template <typename T, int32_t kDim = 5> class TensorView {
   };
 
   template <int32_t D, typename... S>
-  XGBOOST_DEVICE SliceHelper MakeSliceDim(size_t old_dim, size_t new_dim,
-                                          size_t new_shape[D],
-                                          size_t new_stride[D],
-                                          detail::AllTag) const {
+  XGBOOST_DEVICE SliceHelper MakeSliceDim(size_t old_dim, size_t new_dim, size_t new_shape[D],
+                                          size_t new_stride[D], detail::AllTag) const {
     new_stride[new_dim] = stride_[old_dim];
     new_shape[new_dim] = shape_[old_dim];
     return {old_dim + 1, new_dim + 1, 0};
   }
 
   template <int32_t D, typename... S>
-  XGBOOST_DEVICE SliceHelper MakeSliceDim(size_t old_dim, size_t new_dim,
-                                          size_t new_shape[D],
+  XGBOOST_DEVICE SliceHelper MakeSliceDim(size_t old_dim, size_t new_dim, size_t new_shape[D],
                                           size_t new_stride[D], detail::AllTag,
                                           S &&...slices) const {
     new_stride[new_dim] = stride_[old_dim];
     new_shape[new_dim] = shape_[old_dim];
-    return MakeSliceDim<D>(old_dim + 1, new_dim + 1, new_shape, new_stride,
-                           slices...);
+    return MakeSliceDim<D>(old_dim + 1, new_dim + 1, new_shape, new_stride, slices...);
   }
 
   template <int32_t D, typename Index>
-  XGBOOST_DEVICE SliceHelper MakeSliceDim(size_t old_dim, size_t new_dim,
-                                          size_t new_shape[D],
+  XGBOOST_DEVICE SliceHelper MakeSliceDim(size_t old_dim, size_t new_dim, size_t new_shape[D],
                                           size_t new_stride[D], Index i) const {
     return {old_dim + 1, new_dim, stride_[old_dim] * i};
   }
 
   template <int32_t D, typename Index, typename... S>
-  XGBOOST_DEVICE std::enable_if_t<std::is_integral<Index>::value, SliceHelper>
-  MakeSliceDim(size_t old_dim, size_t new_dim, size_t new_shape[D],
-               size_t new_stride[D], Index i, S &&...slices) const {
+  XGBOOST_DEVICE std::enable_if_t<std::is_integral<Index>::value, SliceHelper> MakeSliceDim(
+      size_t old_dim, size_t new_dim, size_t new_shape[D], size_t new_stride[D], Index i,
+      S &&...slices) const {
     auto offset = stride_[old_dim] * i;
-    auto res =
-        MakeSliceDim<D>(old_dim + 1, new_dim, new_shape, new_stride, slices...);
+    auto res = MakeSliceDim<D>(old_dim + 1, new_dim, new_shape, new_stride, slices...);
     return {res.old_dim, res.new_dim, res.offset + offset};
   }
 
@@ -148,8 +144,7 @@ template <typename T, int32_t kDim = 5> class TensorView {
    * \brief Create a tensor with data and shape.
    */
   template <typename I, int32_t D>
-  XGBOOST_DEVICE TensorView(common::Span<T> data, I const (&shape)[D],
-                        int32_t device)
+  XGBOOST_DEVICE TensorView(common::Span<T> data, I const (&shape)[D], int32_t device)
       : data_{data}, device_{device} {
     static_assert(D > 0 && D <= kDim, "Invalid shape.");
     // shape
@@ -170,8 +165,8 @@ template <typename T, int32_t kDim = 5> class TensorView {
    *        stride can be calculated from shape.
    */
   template <typename I, int32_t D>
-  XGBOOST_DEVICE TensorView(common::Span<T> data, I const (&shape)[D],
-                        I const (&stride)[D], int32_t device)
+  XGBOOST_DEVICE TensorView(common::Span<T> data, I const (&shape)[D], I const (&stride)[D],
+                            int32_t device)
       : data_{data}, device_{device} {
     static_assert(D == kDim, "Invalid shape & stride.");
     detail::UnrollLoop<D>([&](auto i) {
@@ -202,7 +197,8 @@ template <typename T, int32_t kDim = 5> class TensorView {
    *
    * \endcode
    */
-  template <typename... Index> XGBOOST_DEVICE T &operator()(Index &&...index) {
+  template <typename... Index>
+  XGBOOST_DEVICE T &operator()(Index &&...index) {
     static_assert(sizeof...(index) <= kDim, "Invalid index.");
     size_t offset = detail::Offset(stride_, 0ul, 0ul, index...);
     return data_[offset];
@@ -229,29 +225,27 @@ template <typename T, int32_t kDim = 5> class TensorView {
    *
    * \endcode
    */
-  template <typename... S> XGBOOST_DEVICE auto Slice(S &&...slices) const {
+  template <typename... S>
+  XGBOOST_DEVICE auto Slice(S &&...slices) const {
     static_assert(sizeof...(slices) <= kDim, "Invalid slice.");
     int32_t constexpr kNewDim{detail::CalcSliceDim<detail::IndexToTag<S>...>()};
     size_t new_shape[kNewDim];
     size_t new_stride[kNewDim];
-    auto res = MakeSliceDim<kNewDim>(size_t(0), size_t(0), new_shape,
-                                     new_stride, slices...);
+    auto res = MakeSliceDim<kNewDim>(size_t(0), size_t(0), new_shape, new_stride, slices...);
     // ret is a different type due to changed dimension, so we can not access its private
     // fields.
-    TensorView<T, kNewDim> ret{data_.subspan(data_.empty() ? 0 : res.offset),
-                           new_shape, new_stride, device_};
+    TensorView<T, kNewDim> ret{data_.subspan(data_.empty() ? 0 : res.offset), new_shape, new_stride,
+                               device_};
     return ret;
   }
 
-  XGBOOST_DEVICE auto Shape() const {
-    return common::Span<size_t const, kDim>{shape_};
-  }
+  XGBOOST_DEVICE auto Shape() const { return common::Span<size_t const, kDim>{shape_}; }
   XGBOOST_DEVICE auto Shape(size_t i) const { return shape_[i]; }
 
-  XGBOOST_DEVICE auto cbegin() const { return data_.cbegin(); } // NOLINT
-  XGBOOST_DEVICE auto cend() const { return data_.cend(); }     // NOLINT
-  XGBOOST_DEVICE auto begin() { return data_.begin(); }         // NOLINT
-  XGBOOST_DEVICE auto end() { return data_.end(); }             // NOLINT
+  XGBOOST_DEVICE auto cbegin() const { return data_.cbegin(); }  // NOLINT
+  XGBOOST_DEVICE auto cend() const { return data_.cend(); }      // NOLINT
+  XGBOOST_DEVICE auto begin() { return data_.begin(); }          // NOLINT
+  XGBOOST_DEVICE auto end() { return data_.end(); }              // NOLINT
 
   XGBOOST_DEVICE size_t Size() const { return size_; }
   XGBOOST_DEVICE auto Values() const { return data_; }
@@ -273,6 +267,6 @@ using VectorView = TensorView<T, 1>;
  */
 template <typename T>
 using MatrixView = TensorView<T, 2>;
-}      // namespace linalg
-}      // namespace xgboost
+}  // namespace linalg
+}  // namespace xgboost
 #endif  // XGBOOST_LINALG_H_
diff --git a/tests/cpp/common/test_linalg.cc b/tests/cpp/common/test_linalg.cc
index 1d3e149c9a6a..13abb63f5659 100644
--- a/tests/cpp/common/test_linalg.cc
+++ b/tests/cpp/common/test_linalg.cc
@@ -1,19 +1,18 @@
 #include <gtest/gtest.h>
-#include <numeric>
 #include <xgboost/host_device_vector.h>
 #include <xgboost/linalg.h>
 
+#include <numeric>
+
 namespace xgboost {
 namespace linalg {
-auto MakeMatrixFromTest(HostDeviceVector<float> *storage, size_t n_rows,
-                        size_t n_cols) {
+auto MakeMatrixFromTest(HostDeviceVector<float> *storage, size_t n_rows, size_t n_cols) {
   storage->Resize(n_rows * n_cols);
   auto &h_storage = storage->HostVector();
 
   std::iota(h_storage.begin(), h_storage.end(), 0);
 
-  auto m = linalg::TensorView<float, 2>{
-      h_storage, {n_rows, static_cast<size_t>(n_cols)}, -1};
+  auto m = linalg::TensorView<float, 2>{h_storage, {n_rows, static_cast<size_t>(n_cols)}, -1};
   return m;
 }
 
@@ -57,10 +56,7 @@ TEST(Linalg, Tensor) {
   ASSERT_EQ(s.Shape()[1], 4);
 
   std::vector<std::vector<double>> sol{
-    {12.0, 13.0, 14.0, 15.0},
-    {16.0, 17.0, 18.0, 19.0},
-    {20.0, 21.0, 22.0, 23.0}
-  };
+      {12.0, 13.0, 14.0, 15.0}, {16.0, 17.0, 18.0, 19.0}, {20.0, 21.0, 22.0, 23.0}};
   for (size_t i = 0; i < s.Shape()[0]; ++i) {
     for (size_t j = 0; j < s.Shape()[1]; ++j) {
       ASSERT_EQ(s(i, j), sol[i][j]);
@@ -113,5 +109,5 @@ TEST(Linalg, Empty) {
     ASSERT_EQ(s.Shape(0), 0);
   }
 }
-} // namespace linalg
-} // namespace xgboost
+}  // namespace linalg
+}  // namespace xgboost