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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.

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This commit is contained in:
Rasmus Munk Larsen
2020-10-13 21:48:31 +00:00
parent 807e51528d
commit c6953f799b
6 changed files with 395 additions and 294 deletions
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22
unsupported/Eigen/CXX11/src/Tensor/TensorBase.h
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@@ -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

41
unsupported/Eigen/CXX11/src/Tensor/TensorFunctors.h
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@@ -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);