Add packet generic ops `predux_fmin`, `predux_fmin_nan`, `predux_fmax`, and `predux_fmax_nan` that implement reductions with `PropagateNaN`, and `PropagateNumbers` semantics. Add (slow) generic implementations for most reductions.

3 files changed, 101 insertions, 56 deletions

diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorBase.h b/unsupported/Eigen/CXX11/src/Tensor/TensorBase.h
index ef332dd19..3a70d8517 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorBase.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorBase.h
@@ -682,28 +682,30 @@ class TensorBase<Derived, ReadOnlyAccessors>
       return TensorReductionOp<internal::ProdReducer<CoeffReturnType>, const DimensionList<Index, NumDimensions>, const Derived>(derived(), in_dims, internal::ProdReducer<CoeffReturnType>());
     }
 
-    template <typename Dims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    const TensorReductionOp<internal::MaxReducer<CoeffReturnType>, const Dims, const Derived>
+    template <typename Dims,int NanPropagation=PropagateFast> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorReductionOp<internal::MaxReducer<CoeffReturnType,NanPropagation>, const Dims, const Derived>
     maximum(const Dims& dims) const {
-      return TensorReductionOp<internal::MaxReducer<CoeffReturnType>, const Dims, const Derived>(derived(), dims, internal::MaxReducer<CoeffReturnType>());
+      return TensorReductionOp<internal::MaxReducer<CoeffReturnType,NanPropagation>, const Dims, const Derived>(derived(), dims, internal::MaxReducer<CoeffReturnType,NanPropagation>());
     }
 
-    const TensorReductionOp<internal::MaxReducer<CoeffReturnType>, const DimensionList<Index, NumDimensions>, const Derived>
+    template <int NanPropagation=PropagateFast>
+    const TensorReductionOp<internal::MaxReducer<CoeffReturnType,NanPropagation>, const DimensionList<Index, NumDimensions>, const Derived>
     maximum() const {
       DimensionList<Index, NumDimensions> in_dims;
-      return TensorReductionOp<internal::MaxReducer<CoeffReturnType>, const DimensionList<Index, NumDimensions>, const Derived>(derived(), in_dims, internal::MaxReducer<CoeffReturnType>());
+      return TensorReductionOp<internal::MaxReducer<CoeffReturnType,NanPropagation>, const DimensionList<Index, NumDimensions>, const Derived>(derived(), in_dims, internal::MaxReducer<CoeffReturnType,NanPropagation>());
     }
 
-    template <typename Dims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
-    const TensorReductionOp<internal::MinReducer<CoeffReturnType>, const Dims, const Derived>
+    template <typename Dims,int NanPropagation=PropagateFast> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
+    const TensorReductionOp<internal::MinReducer<CoeffReturnType,NanPropagation>, const Dims, const Derived>
     minimum(const Dims& dims) const {
-      return TensorReductionOp<internal::MinReducer<CoeffReturnType>, const Dims, const Derived>(derived(), dims, internal::MinReducer<CoeffReturnType>());
+      return TensorReductionOp<internal::MinReducer<CoeffReturnType,NanPropagation>, const Dims, const Derived>(derived(), dims, internal::MinReducer<CoeffReturnType,NanPropagation>());
     }
 
-    const TensorReductionOp<internal::MinReducer<CoeffReturnType>, const DimensionList<Index, NumDimensions>, const Derived>
+    template <int NanPropagation=PropagateFast>
+    const TensorReductionOp<internal::MinReducer<CoeffReturnType,NanPropagation>, const DimensionList<Index, NumDimensions>, const Derived>
     minimum() const {
       DimensionList<Index, NumDimensions> in_dims;
-      return TensorReductionOp<internal::MinReducer<CoeffReturnType>, const DimensionList<Index, NumDimensions>, const Derived>(derived(), in_dims, internal::MinReducer<CoeffReturnType>());
+      return TensorReductionOp<internal::MinReducer<CoeffReturnType,NanPropagation>, const DimensionList<Index, NumDimensions>, const Derived>(derived(), in_dims, internal::MinReducer<CoeffReturnType,NanPropagation>());
     }
 
     template <typename Dims> EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE
diff --git a/unsupported/Eigen/CXX11/src/Tensor/TensorFunctors.h b/unsupported/Eigen/CXX11/src/Tensor/TensorFunctors.h
index 2edc45f1a..fd8fa00fa 100644
--- a/unsupported/Eigen/CXX11/src/Tensor/TensorFunctors.h
+++ b/unsupported/Eigen/CXX11/src/Tensor/TensorFunctors.h
@@ -192,17 +192,19 @@ struct MinMaxBottomValue<T, false, false> {
 };
 
 
-template <typename T> struct MaxReducer
+template <typename T, int NaNPropagation=PropagateFast> struct MaxReducer
 {
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reduce(const T t, T* accum) const {
-    if (t > *accum) { *accum = t; }
+    scalar_max_op<T, T, NaNPropagation> op;
+    *accum = op(t, *accum);
   }
   template <typename Packet>
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reducePacket(const Packet& p, Packet* accum) const {
-    (*accum) = pmax<Packet>(*accum, p);
+    scalar_max_op<T, T, NaNPropagation> op;
+    (*accum) = op.packetOp(*accum, p);
   }
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T initialize() const {
-    return MinMaxBottomValue<T, true, Eigen::NumTraits<T>::IsInteger>::bottom_value();
+    return MinMaxBottomValue<T, /*IsMax=*/true, Eigen::NumTraits<T>::IsInteger>::bottom_value();
   }
   template <typename Packet>
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet initializePacket() const {
@@ -217,32 +219,34 @@ template <typename T> struct MaxReducer
   }
   template <typename Packet>
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T finalizeBoth(const T saccum, const Packet& vaccum) const {
-    return numext::maxi(saccum, predux_max(vaccum));
+    scalar_max_op<T, T, NaNPropagation> op;
+    return op(saccum, op.predux(vaccum));
   }
 };
 
-template <typename T, typename Device>
-struct reducer_traits<MaxReducer<T>, Device> {
+template <typename T, typename Device, int NaNPropagation>
+    struct reducer_traits<MaxReducer<T, NaNPropagation>, Device> {
   enum {
     Cost = NumTraits<T>::AddCost,
     PacketAccess = PacketType<T, Device>::HasMax,
     IsStateful = false,
-    IsExactlyAssociative = true
+    IsExactlyAssociative = (NaNPropagation!=PropagateFast)
   };
 };
 
-
-template <typename T> struct MinReducer
+template <typename T, int NaNPropagation=PropagateFast> struct MinReducer
 {
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reduce(const T t, T* accum) const {
-    if (t < *accum) { *accum = t; }
+    scalar_min_op<T, T, NaNPropagation> op;
+    *accum = op(t, *accum);
   }
   template <typename Packet>
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reducePacket(const Packet& p, Packet* accum) const {
-    (*accum) = pmin<Packet>(*accum, p);
+    scalar_min_op<T, T, NaNPropagation> op;
+    (*accum) = op.packetOp(*accum, p);
   }
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T initialize() const {
-    return MinMaxBottomValue<T, false, Eigen::NumTraits<T>::IsInteger>::bottom_value();
+    return MinMaxBottomValue<T, /*IsMax=*/false, Eigen::NumTraits<T>::IsInteger>::bottom_value();
   }
   template <typename Packet>
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet initializePacket() const {
@@ -257,21 +261,21 @@ template <typename T> struct MinReducer
   }
   template <typename Packet>
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T finalizeBoth(const T saccum, const Packet& vaccum) const {
-    return numext::mini(saccum, predux_min(vaccum));
+    scalar_min_op<T, T, NaNPropagation> op;
+    return op(saccum, op.predux(vaccum));
   }
 };
 
-template <typename T, typename Device>
-struct reducer_traits<MinReducer<T>, Device> {
+template <typename T, typename Device, int NaNPropagation>
+    struct reducer_traits<MinReducer<T, NaNPropagation>, Device> {
   enum {
     Cost = NumTraits<T>::AddCost,
     PacketAccess = PacketType<T, Device>::HasMin,
     IsStateful = false,
-    IsExactlyAssociative = true
+    IsExactlyAssociative = (NaNPropagation!=PropagateFast)
   };
 };
 
-
 template <typename T> struct ProdReducer
 {
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reduce(const T t, T* accum) const {
@@ -282,7 +286,6 @@ template <typename T> struct ProdReducer
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void reducePacket(const Packet& p, Packet* accum) const {
     (*accum) = pmul<Packet>(*accum, p);
   }
-
   EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T initialize() const {
     internal::scalar_cast_op<int, T> conv;
     return conv(1);
diff --git a/unsupported/test/cxx11_tensor_expr.cpp b/unsupported/test/cxx11_tensor_expr.cpp
index 7fac3b4ed..556d01d4d 100644
--- a/unsupported/test/cxx11_tensor_expr.cpp
+++ b/unsupported/test/cxx11_tensor_expr.cpp
@@ -302,12 +302,17 @@ static void test_select()
 template <typename Scalar>
 void test_minmax_nan_propagation_templ() {
   for (int size = 1; size < 17; ++size) {
-    const Scalar kNan = std::numeric_limits<Scalar>::quiet_NaN();
+    std::cout << "size = " << size << std::endl;
+    const Scalar kNaN = std::numeric_limits<Scalar>::quiet_NaN();
+    const Scalar kInf = std::numeric_limits<Scalar>::infinity();
     const Scalar kZero(0);
-    Tensor<Scalar, 1> vec_nan(size);
+    Tensor<Scalar, 1> vec_all_nan(size);
+    Tensor<Scalar, 1> vec_one_nan(size);
     Tensor<Scalar, 1> vec_zero(size);
-    vec_nan.setConstant(kNan);
+    vec_all_nan.setConstant(kNaN);
     vec_zero.setZero();
+    vec_one_nan.setZero();
+    vec_one_nan(size/2) = kNaN;
 
     auto verify_all_nan = [&](const Tensor<Scalar, 1>& v) {
       for (int i = 0; i < size; ++i) {
@@ -326,12 +331,12 @@ void test_minmax_nan_propagation_templ() {
     // max(nan, 0) = nan
     // max(0, nan) = nan
     // max(0, 0) = 0
-    verify_all_nan(vec_nan.template cwiseMax<PropagateNaN>(kNan));
-    verify_all_nan(vec_nan.template cwiseMax<PropagateNaN>(vec_nan));
-    verify_all_nan(vec_nan.template cwiseMax<PropagateNaN>(kZero));
-    verify_all_nan(vec_nan.template cwiseMax<PropagateNaN>(vec_zero));
-    verify_all_nan(vec_zero.template cwiseMax<PropagateNaN>(kNan));
-    verify_all_nan(vec_zero.template cwiseMax<PropagateNaN>(vec_nan));
+    verify_all_nan(vec_all_nan.template cwiseMax<PropagateNaN>(kNaN));
+    verify_all_nan(vec_all_nan.template cwiseMax<PropagateNaN>(vec_all_nan));
+    verify_all_nan(vec_all_nan.template cwiseMax<PropagateNaN>(kZero));
+    verify_all_nan(vec_all_nan.template cwiseMax<PropagateNaN>(vec_zero));
+    verify_all_nan(vec_zero.template cwiseMax<PropagateNaN>(kNaN));
+    verify_all_nan(vec_zero.template cwiseMax<PropagateNaN>(vec_all_nan));
     verify_all_zero(vec_zero.template cwiseMax<PropagateNaN>(kZero));
     verify_all_zero(vec_zero.template cwiseMax<PropagateNaN>(vec_zero));
 
@@ -340,12 +345,12 @@ void test_minmax_nan_propagation_templ() {
     // max(nan, 0) = 0
     // max(0, nan) = 0
     // max(0, 0) = 0
-    verify_all_nan(vec_nan.template cwiseMax<PropagateNumbers>(kNan));
-    verify_all_nan(vec_nan.template cwiseMax<PropagateNumbers>(vec_nan));
-    verify_all_zero(vec_nan.template cwiseMax<PropagateNumbers>(kZero));
-    verify_all_zero(vec_nan.template cwiseMax<PropagateNumbers>(vec_zero));
-    verify_all_zero(vec_zero.template cwiseMax<PropagateNumbers>(kNan));
-    verify_all_zero(vec_zero.template cwiseMax<PropagateNumbers>(vec_nan));
+    verify_all_nan(vec_all_nan.template cwiseMax<PropagateNumbers>(kNaN));
+    verify_all_nan(vec_all_nan.template cwiseMax<PropagateNumbers>(vec_all_nan));
+    verify_all_zero(vec_all_nan.template cwiseMax<PropagateNumbers>(kZero));
+    verify_all_zero(vec_all_nan.template cwiseMax<PropagateNumbers>(vec_zero));
+    verify_all_zero(vec_zero.template cwiseMax<PropagateNumbers>(kNaN));
+    verify_all_zero(vec_zero.template cwiseMax<PropagateNumbers>(vec_all_nan));
     verify_all_zero(vec_zero.template cwiseMax<PropagateNumbers>(kZero));
     verify_all_zero(vec_zero.template cwiseMax<PropagateNumbers>(vec_zero));
 
@@ -354,12 +359,12 @@ void test_minmax_nan_propagation_templ() {
     // min(nan, 0) = nan
     // min(0, nan) = nan
     // min(0, 0) = 0
-    verify_all_nan(vec_nan.template cwiseMin<PropagateNaN>(kNan));
-    verify_all_nan(vec_nan.template cwiseMin<PropagateNaN>(vec_nan));
-    verify_all_nan(vec_nan.template cwiseMin<PropagateNaN>(kZero));
-    verify_all_nan(vec_nan.template cwiseMin<PropagateNaN>(vec_zero));
-    verify_all_nan(vec_zero.template cwiseMin<PropagateNaN>(kNan));
-    verify_all_nan(vec_zero.template cwiseMin<PropagateNaN>(vec_nan));
+    verify_all_nan(vec_all_nan.template cwiseMin<PropagateNaN>(kNaN));
+    verify_all_nan(vec_all_nan.template cwiseMin<PropagateNaN>(vec_all_nan));
+    verify_all_nan(vec_all_nan.template cwiseMin<PropagateNaN>(kZero));
+    verify_all_nan(vec_all_nan.template cwiseMin<PropagateNaN>(vec_zero));
+    verify_all_nan(vec_zero.template cwiseMin<PropagateNaN>(kNaN));
+    verify_all_nan(vec_zero.template cwiseMin<PropagateNaN>(vec_all_nan));
     verify_all_zero(vec_zero.template cwiseMin<PropagateNaN>(kZero));
     verify_all_zero(vec_zero.template cwiseMin<PropagateNaN>(vec_zero));
 
@@ -368,14 +373,49 @@ void test_minmax_nan_propagation_templ() {
     // min(nan, 0) = 0
     // min(0, nan) = 0
     // min(0, 0) = 0
-    verify_all_nan(vec_nan.template cwiseMin<PropagateNumbers>(kNan));
-    verify_all_nan(vec_nan.template cwiseMin<PropagateNumbers>(vec_nan));
-    verify_all_zero(vec_nan.template cwiseMin<PropagateNumbers>(kZero));
-    verify_all_zero(vec_nan.template cwiseMin<PropagateNumbers>(vec_zero));
-    verify_all_zero(vec_zero.template cwiseMin<PropagateNumbers>(kNan));
-    verify_all_zero(vec_zero.template cwiseMin<PropagateNumbers>(vec_nan));
+    verify_all_nan(vec_all_nan.template cwiseMin<PropagateNumbers>(kNaN));
+    verify_all_nan(vec_all_nan.template cwiseMin<PropagateNumbers>(vec_all_nan));
+    verify_all_zero(vec_all_nan.template cwiseMin<PropagateNumbers>(kZero));
+    verify_all_zero(vec_all_nan.template cwiseMin<PropagateNumbers>(vec_zero));
+    verify_all_zero(vec_zero.template cwiseMin<PropagateNumbers>(kNaN));
+    verify_all_zero(vec_zero.template cwiseMin<PropagateNumbers>(vec_all_nan));
     verify_all_zero(vec_zero.template cwiseMin<PropagateNumbers>(kZero));
     verify_all_zero(vec_zero.template cwiseMin<PropagateNumbers>(vec_zero));
+
+    // Test min and max reduction
+    Tensor<Scalar, 0> val;
+    val = vec_zero.minimum();
+    VERIFY_IS_EQUAL(val(), kZero);
+    val = vec_zero.template minimum<PropagateNaN>();
+    VERIFY_IS_EQUAL(val(), kZero);
+    val = vec_zero.template minimum<PropagateNumbers>();
+    VERIFY_IS_EQUAL(val(), kZero);
+    val = vec_zero.maximum();
+    VERIFY_IS_EQUAL(val(), kZero);
+    val = vec_zero.template maximum<PropagateNaN>();
+    VERIFY_IS_EQUAL(val(), kZero);
+    val = vec_zero.template maximum<PropagateNumbers>();
+    VERIFY_IS_EQUAL(val(), kZero);
+
+    // Test NaN propagation for tensor of all NaNs.
+    val = vec_all_nan.template minimum<PropagateNaN>();
+    VERIFY((numext::isnan)(val()));
+    val = vec_all_nan.template minimum<PropagateNumbers>();
+    VERIFY_IS_EQUAL(val(), kInf);
+    val = vec_all_nan.template maximum<PropagateNaN>();
+    VERIFY((numext::isnan)(val()));
+    val = vec_all_nan.template maximum<PropagateNumbers>();
+    VERIFY_IS_EQUAL(val(), -kInf);
+
+    // Test NaN propagation for tensor with a single NaN.
+    val = vec_one_nan.template minimum<PropagateNaN>();
+    VERIFY((numext::isnan)(val()));
+    val = vec_one_nan.template minimum<PropagateNumbers>();
+    VERIFY_IS_EQUAL(val(), (size == 1 ? kInf : kZero));
+    val = vec_one_nan.template maximum<PropagateNaN>();
+    VERIFY((numext::isnan)(val()));
+    val = vec_one_nan.template maximum<PropagateNumbers>();
+    VERIFY_IS_EQUAL(val(), (size == 1 ? -kInf : kZero));
   }
 }