Merged eigen/eigen

Eigen/src/Core/GenericPacketMath.h

@@ -276,12 +276,12 @@ pselect(const Packet& mask, const Packet& a, const Packet& b) {
 
 template<> EIGEN_DEVICE_FUNC inline float pselect<float>(
     const float& mask, const float& a, const float&b) {
-  return mask == 0 ? b : a;
+  return numext::equal_strict(mask,0.f) ? b : a;
 }
 
 template<> EIGEN_DEVICE_FUNC inline double pselect<double>(
     const double& mask, const double& a, const double& b) {
-  return mask == 0 ? b : a;
+  return numext::equal_strict(mask,0.) ? b : a;
 }
 
 /** \internal \returns a <= b as a bit mask */

Eigen/src/Core/arch/AVX512/PacketMath.h

@@ -95,8 +95,8 @@ template<> struct packet_traits<float>  : default_packet_traits
 #if EIGEN_GNUC_AT_LEAST(5, 3) || (!EIGEN_COMP_GNUC_STRICT)
 #ifdef EIGEN_VECTORIZE_AVX512DQ
     HasLog = 1,
-    HasLog1p = 1,
+    HasLog1p  = 1,
-    HasExpm1 = 1,
+    HasExpm1  = 1,
     HasNdtri = 1,
 #endif
     HasExp = 1,

Eigen/src/Core/arch/SSE/PacketMath.h

@@ -112,6 +112,7 @@ template<> struct packet_traits<float>  : default_packet_traits
     HasLog  = 1,
     HasLog1p  = 1,
     HasExpm1  = 1,
+    HasNdtri = 1,
     HasExp  = 1,
     HasNdtri = 1,
     HasSqrt = 1,

Eigen/src/SparseCore/SparseCwiseUnaryOp.h

@@ -49,6 +49,7 @@ template<typename UnaryOp, typename ArgType>
 class unary_evaluator<CwiseUnaryOp<UnaryOp,ArgType>, IteratorBased>::InnerIterator
     : public unary_evaluator<CwiseUnaryOp<UnaryOp,ArgType>, IteratorBased>::EvalIterator
 {
+  protected:
     typedef typename XprType::Scalar Scalar;
     typedef typename unary_evaluator<CwiseUnaryOp<UnaryOp,ArgType>, IteratorBased>::EvalIterator Base;
   public:
@@ -99,6 +100,7 @@ template<typename ViewOp, typename ArgType>
 class unary_evaluator<CwiseUnaryView<ViewOp,ArgType>, IteratorBased>::InnerIterator
     : public unary_evaluator<CwiseUnaryView<ViewOp,ArgType>, IteratorBased>::EvalIterator
 {
+  protected:
     typedef typename XprType::Scalar Scalar;
     typedef typename unary_evaluator<CwiseUnaryView<ViewOp,ArgType>, IteratorBased>::EvalIterator Base;
   public:

Eigen/src/SparseCore/SparseView.h

@@ -90,6 +90,7 @@ struct unary_evaluator<SparseView<ArgType>, IteratorBased>
     
     class InnerIterator : public EvalIterator
     {
+      protected:
         typedef typename XprType::Scalar Scalar;
       public:
 

Eigen/src/plugins/ArrayCwiseUnaryOps.h

@@ -608,16 +608,18 @@ erfc() const
   return ErfcReturnType(derived());
 }
 
-/** \cpp11 \returns an expression of the coefficient-wise Complementary error
+/** \returns an expression of the coefficient-wise inverse of the CDF of the Normal distribution function
   * function of *this.
   *
   * \specialfunctions_module
+  * 
+  * In other words, considering `x = ndtri(y)`, it returns the argument, x, for which the area under the
+  * Gaussian probability density function (integrated from minus infinity to x) is equal to y.
   *
-  * \note This function supports only float and double scalar types in c++11 mode. To support other scalar types,
+  * \note This function supports only float and double scalar types. To support other scalar types,
-  * or float/double in non c++11 mode, the user has to provide implementations of ndtri(T) for any scalar
+  * the user has to provide implementations of ndtri(T) for any scalar type T to be supported.
-  * type T to be supported.
   *
-  * \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_ndtri">Math functions</a>, erf()
+  * \sa <a href="group__CoeffwiseMathFunctions.html#cwisetable_ndtri">Math functions</a>
   */
 EIGEN_DEVICE_FUNC
 inline const NdtriReturnType

doc/CoeffwiseMathFunctionsTable.dox

@@ -553,6 +553,18 @@ This also means that, unless specified, if the function \c std::foo is available
   </td>
   <td></td>
 </tr>
+<tr>
+  <td class="code">
+  \anchor cwisetable_ndtri
+  a.\link ArrayBase::ndtri ndtri\endlink(); \n
+  \link Eigen::ndtri ndtri\endlink(a);
+  </td>
+  <td>Inverse of the CDF of the Normal distribution function</td>
+  <td>
+  built-in for float and double
+  </td>
+  <td></td>
+</tr>
 <tr><td colspan="4"></td></tr>
 </table>
 

unsupported/Eigen/CXX11/src/Tensor/TensorBase.h

@@ -1071,12 +1071,12 @@ class TensorBase : public TensorBase<Derived, ReadOnlyAccessors> {
 
 #ifdef EIGEN_USE_THREADS
     // Select the async device on which to evaluate the expression.
-    template <typename DeviceType>
+    template <typename DeviceType, typename DoneCallback>
     typename internal::enable_if<
         internal::is_same<DeviceType, ThreadPoolDevice>::value,
-        TensorAsyncDevice<Derived, DeviceType>>::type
+        TensorAsyncDevice<Derived, DeviceType, DoneCallback>>::type
-    device(const DeviceType& dev, std::function<void()> done) {
+    device(const DeviceType& dev, DoneCallback done) {
-      return TensorAsyncDevice<Derived, DeviceType>(dev, derived(), std::move(done));
+      return TensorAsyncDevice<Derived, DeviceType, DoneCallback>(dev, derived(), std::move(done));
     }
 #endif  // EIGEN_USE_THREADS
 

unsupported/Eigen/CXX11/src/Tensor/TensorDevice.h

@@ -73,21 +73,21 @@ template <typename ExpressionType, typename DeviceType> class TensorDevice {
   * ThreadPoolDevice).
   *
   * Example:
-  *    std::function<void()> done = []() {};
+  *    auto done = []() { ... expression evaluation done ... };
   *    C.device(EIGEN_THREAD_POOL, std::move(done)) = A + B;
  */
 
-template <typename ExpressionType, typename DeviceType>
+template <typename ExpressionType, typename DeviceType, typename DoneCallback>
 class TensorAsyncDevice {
  public:
   TensorAsyncDevice(const DeviceType& device, ExpressionType& expression,
-                    std::function<void()> done)
+                    DoneCallback done)
       : m_device(device), m_expression(expression), m_done(std::move(done)) {}
 
   template <typename OtherDerived>
   EIGEN_STRONG_INLINE TensorAsyncDevice& operator=(const OtherDerived& other) {
     typedef TensorAssignOp<ExpressionType, const OtherDerived> Assign;
-    typedef internal::TensorAsyncExecutor<const Assign, DeviceType> Executor;
+    typedef internal::TensorAsyncExecutor<const Assign, DeviceType, DoneCallback> Executor;
 
     // WARNING: After assignment 'm_done' callback will be in undefined state.
     Assign assign(m_expression, other);
@@ -99,7 +99,7 @@ class TensorAsyncDevice {
  protected:
   const DeviceType& m_device;
   ExpressionType& m_expression;
-  std::function<void()> m_done;
+  DoneCallback m_done;
 };
 
 #endif  // EIGEN_USE_THREADS

unsupported/Eigen/CXX11/src/Tensor/TensorExecutor.h

@@ -101,8 +101,8 @@ class TensorExecutor {
  * Default async execution strategy is not implemented. Currently it's only
  * available for ThreadPoolDevice (see definition below).
  */
-template <typename Expression, typename Device, bool Vectorizable,
+template <typename Expression, typename Device, typename DoneCallback,
-          bool Tileable>
+          bool Vectorizable, bool Tileable>
 class TensorAsyncExecutor {};
 
 /**
@@ -419,15 +419,17 @@ class TensorExecutor<Expression, ThreadPoolDevice, Vectorizable, /*Tileable*/ tr
   }
 };
 
-template <typename Expression, bool Vectorizable, bool Tileable>
+template <typename Expression, typename DoneCallback, bool Vectorizable,
-class TensorAsyncExecutor<Expression, ThreadPoolDevice, Vectorizable, Tileable> {
+          bool Tileable>
+class TensorAsyncExecutor<Expression, ThreadPoolDevice, DoneCallback,
+                          Vectorizable, Tileable> {
  public:
   typedef typename Expression::Index StorageIndex;
   typedef TensorEvaluator<Expression, ThreadPoolDevice> Evaluator;
 
   static EIGEN_STRONG_INLINE void runAsync(const Expression& expr,
                                            const ThreadPoolDevice& device,
-                                           std::function<void()> done) {
+                                           DoneCallback done) {
     TensorAsyncExecutorContext* const ctx =
         new TensorAsyncExecutorContext(expr, device, std::move(done));
 
@@ -455,7 +457,7 @@ class TensorAsyncExecutor<Expression, ThreadPoolDevice, Vectorizable, Tileable>
   struct TensorAsyncExecutorContext {
     TensorAsyncExecutorContext(const Expression& expr,
                                const ThreadPoolDevice& thread_pool,
-                               std::function<void()> done)
+                               DoneCallback done)
         : evaluator(expr, thread_pool), on_done(std::move(done)) {}
 
     ~TensorAsyncExecutorContext() {
@@ -466,12 +468,13 @@ class TensorAsyncExecutor<Expression, ThreadPoolDevice, Vectorizable, Tileable>
     Evaluator evaluator;
 
    private:
-    std::function<void()> on_done;
+    DoneCallback on_done;
   };
 };
 
-template <typename Expression, bool Vectorizable>
+template <typename Expression, typename DoneCallback, bool Vectorizable>
-class TensorAsyncExecutor<Expression, ThreadPoolDevice, Vectorizable, /*Tileable*/ true> {
+class TensorAsyncExecutor<Expression, ThreadPoolDevice, DoneCallback,
+                          Vectorizable, /*Tileable*/ true> {
  public:
   typedef typename traits<Expression>::Index StorageIndex;
   typedef typename traits<Expression>::Scalar Scalar;
@@ -485,7 +488,7 @@ class TensorAsyncExecutor<Expression, ThreadPoolDevice, Vectorizable, /*Tileable
 
   static EIGEN_STRONG_INLINE void runAsync(const Expression& expr,
                                            const ThreadPoolDevice& device,
-                                           std::function<void()> done) {
+                                           DoneCallback done) {
     TensorAsyncExecutorContext* const ctx =
         new TensorAsyncExecutorContext(expr, device, std::move(done));
 
@@ -494,9 +497,10 @@ class TensorAsyncExecutor<Expression, ThreadPoolDevice, Vectorizable, /*Tileable
 
     if (total_size < cache_size &&
         !ExpressionHasTensorBroadcastingOp<Expression>::value) {
-      internal::TensorAsyncExecutor<Expression, ThreadPoolDevice, Vectorizable,
+      auto delete_ctx = [ctx]() { delete ctx; };
-                                    /*Tileable*/ false>::runAsync(
+      internal::TensorAsyncExecutor<
-                                        expr, device, [ctx]() { delete ctx; });
+          Expression, ThreadPoolDevice, decltype(delete_ctx), Vectorizable,
+          /*Tileable*/ false>::runAsync(expr, device, std::move(delete_ctx));
       return;
     }
 
@@ -532,7 +536,7 @@ class TensorAsyncExecutor<Expression, ThreadPoolDevice, Vectorizable, /*Tileable
   struct TensorAsyncExecutorContext {
     TensorAsyncExecutorContext(const Expression& expr,
                                const ThreadPoolDevice& thread_pool,
-                               std::function<void()> done)
+                               DoneCallback done)
         : device(thread_pool),
           evaluator(expr, thread_pool),
           on_done(std::move(done)) {}
@@ -548,7 +552,7 @@ class TensorAsyncExecutor<Expression, ThreadPoolDevice, Vectorizable, /*Tileable
     TilingContext tiling;
 
    private:
-    std::function<void()> on_done;
+    DoneCallback on_done;
   };
 };
 

unsupported/Eigen/CXX11/src/Tensor/TensorForwardDeclarations.h

@@ -94,7 +94,7 @@ template<typename XprType, template <class> class MakePointer_ = MakePointer> cl
 template<typename XprType> class TensorForcedEvalOp;
 
 template<typename ExpressionType, typename DeviceType> class TensorDevice;
-template<typename ExpressionType, typename DeviceType> class TensorAsyncDevice;
+template<typename ExpressionType, typename DeviceType, typename DoneCallback> class TensorAsyncDevice;
 template<typename Derived, typename Device> struct TensorEvaluator;
 
 struct NoOpOutputKernel;
@@ -168,7 +168,7 @@ template <typename Expression, typename Device,
           bool Tileable = IsTileable<Device, Expression>::value>
 class TensorExecutor;
 
-template <typename Expression, typename Device,
+template <typename Expression, typename Device, typename DoneCallback,
           bool Vectorizable = IsVectorizable<Device, Expression>::value,
           bool Tileable = IsTileable<Device, Expression>::value>
 class TensorAsyncExecutor;

unsupported/test/cxx11_tensor_executor.cpp

@@ -578,11 +578,15 @@ static void test_async_execute_unary_expr(Device d)
   src.setRandom();
   const auto expr = src.square();
 
-  using Assign = TensorAssignOp<decltype(dst), const decltype(expr)>;
-  using Executor = internal::TensorAsyncExecutor<const Assign, Device,
-                                                 Vectorizable, Tileable>;
   Eigen::Barrier done(1);
-  Executor::runAsync(Assign(dst, expr), d, [&done]() { done.Notify(); });
+  auto on_done = [&done]() { done.Notify(); };
+
+  using Assign = TensorAssignOp<decltype(dst), const decltype(expr)>;
+  using DoneCallback = decltype(on_done);
+  using Executor = internal::TensorAsyncExecutor<const Assign, Device, DoneCallback,
+                                                 Vectorizable, Tileable>;
+
+  Executor::runAsync(Assign(dst, expr), d, on_done);
   done.Wait();
 
   for (Index i = 0; i < dst.dimensions().TotalSize(); ++i) {
@@ -610,12 +614,15 @@ static void test_async_execute_binary_expr(Device d)
 
   const auto expr = lhs + rhs;
 
+  Eigen::Barrier done(1);
+  auto on_done = [&done]() { done.Notify(); };
+
   using Assign = TensorAssignOp<decltype(dst), const decltype(expr)>;
-  using Executor = internal::TensorAsyncExecutor<const Assign, Device,
+  using DoneCallback = decltype(on_done);
+  using Executor = internal::TensorAsyncExecutor<const Assign, Device, DoneCallback,
                                                  Vectorizable, Tileable>;
 
-  Eigen::Barrier done(1);
+  Executor::runAsync(Assign(dst, expr), d, on_done);
-  Executor::runAsync(Assign(dst, expr), d, [&done]() { done.Notify(); });
   done.Wait();
 
   for (Index i = 0; i < dst.dimensions().TotalSize(); ++i) {

unsupported/test/cxx11_tensor_thread_pool.cpp

@@ -683,34 +683,39 @@ EIGEN_DECLARE_TEST(cxx11_tensor_thread_pool)
   CALL_SUBTEST_3(test_multithread_contraction_agrees_with_singlethread<RowMajor>());
   CALL_SUBTEST_3(test_multithread_contraction_with_output_kernel<ColMajor>());
   CALL_SUBTEST_3(test_multithread_contraction_with_output_kernel<RowMajor>());
-  CALL_SUBTEST_3(test_async_multithread_contraction_agrees_with_singlethread<ColMajor>());
+
-  CALL_SUBTEST_3(test_async_multithread_contraction_agrees_with_singlethread<RowMajor>());
+  CALL_SUBTEST_4(test_async_multithread_contraction_agrees_with_singlethread<ColMajor>());
+  CALL_SUBTEST_4(test_async_multithread_contraction_agrees_with_singlethread<RowMajor>());
 
   // Test EvalShardedByInnerDimContext parallelization strategy.
-  CALL_SUBTEST_4(test_sharded_by_inner_dim_contraction<ColMajor>());
+  CALL_SUBTEST_5(test_sharded_by_inner_dim_contraction<ColMajor>());
-  CALL_SUBTEST_4(test_sharded_by_inner_dim_contraction<RowMajor>());
+  CALL_SUBTEST_5(test_sharded_by_inner_dim_contraction<RowMajor>());
-  CALL_SUBTEST_4(test_sharded_by_inner_dim_contraction_with_output_kernel<ColMajor>());
+  CALL_SUBTEST_5(test_sharded_by_inner_dim_contraction_with_output_kernel<ColMajor>());
-  CALL_SUBTEST_4(test_sharded_by_inner_dim_contraction_with_output_kernel<RowMajor>());
+  CALL_SUBTEST_5(test_sharded_by_inner_dim_contraction_with_output_kernel<RowMajor>());
-  CALL_SUBTEST_4(test_async_sharded_by_inner_dim_contraction<ColMajor>());
+
-  CALL_SUBTEST_4(test_async_sharded_by_inner_dim_contraction<RowMajor>());
+  CALL_SUBTEST_6(test_async_sharded_by_inner_dim_contraction<ColMajor>());
-  CALL_SUBTEST_4(test_async_sharded_by_inner_dim_contraction_with_output_kernel<ColMajor>());
+  CALL_SUBTEST_6(test_async_sharded_by_inner_dim_contraction<RowMajor>());
-  CALL_SUBTEST_4(test_async_sharded_by_inner_dim_contraction_with_output_kernel<RowMajor>());
+  CALL_SUBTEST_6(test_async_sharded_by_inner_dim_contraction_with_output_kernel<ColMajor>());
+  CALL_SUBTEST_6(test_async_sharded_by_inner_dim_contraction_with_output_kernel<RowMajor>());
 
   // Exercise various cases that have been problematic in the past.
-  CALL_SUBTEST_5(test_contraction_corner_cases<ColMajor>());
+  CALL_SUBTEST_7(test_contraction_corner_cases<ColMajor>());
-  CALL_SUBTEST_5(test_contraction_corner_cases<RowMajor>());
+  CALL_SUBTEST_7(test_contraction_corner_cases<RowMajor>());
 
-  CALL_SUBTEST_6(test_full_contraction<ColMajor>());
+  CALL_SUBTEST_8(test_full_contraction<ColMajor>());
-  CALL_SUBTEST_6(test_full_contraction<RowMajor>());
+  CALL_SUBTEST_8(test_full_contraction<RowMajor>());
 
-  CALL_SUBTEST_7(test_multithreaded_reductions<ColMajor>());
+  CALL_SUBTEST_9(test_multithreaded_reductions<ColMajor>());
-  CALL_SUBTEST_7(test_multithreaded_reductions<RowMajor>());
+  CALL_SUBTEST_9(test_multithreaded_reductions<RowMajor>());
 
-  CALL_SUBTEST_7(test_memcpy());
+  CALL_SUBTEST_10(test_memcpy());
-  CALL_SUBTEST_7(test_multithread_random());
+  CALL_SUBTEST_10(test_multithread_random());
 
   TestAllocator test_allocator;
-  CALL_SUBTEST_7(test_multithread_shuffle<ColMajor>(NULL));
+  CALL_SUBTEST_11(test_multithread_shuffle<ColMajor>(NULL));
-  CALL_SUBTEST_7(test_multithread_shuffle<RowMajor>(&test_allocator));
+  CALL_SUBTEST_11(test_multithread_shuffle<RowMajor>(&test_allocator));
-  CALL_SUBTEST_7(test_threadpool_allocate(&test_allocator));
+  CALL_SUBTEST_11(test_threadpool_allocate(&test_allocator));
+
+  // Force CMake to split this test.
+  // EIGEN_SUFFIXES;1;2;3;4;5;6;7;8;9;10;11
 }