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Merged in rmlarsen/eigen2 (pull request PR-422)

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Optimize the case where broadcasting is a no-op.
This commit is contained in:
Gael Guennebaud 2018-07-14 11:42:58 +00:00
commit 23d82c1ac5
1 changed files with 26 additions and 11 deletions
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37
unsupported/Eigen/CXX11/src/Tensor/TensorBroadcasting.h
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@ -105,7 +105,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
typedef typename XprType::CoeffReturnType CoeffReturnType; typedef typename XprType::CoeffReturnType CoeffReturnType;
typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType; typedef typename PacketType<CoeffReturnType, Device>::type PacketReturnType;
static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size; static const int PacketSize = internal::unpacket_traits<PacketReturnType>::size;
bool nByOne = false, oneByN = false; bool isCopy= false, nByOne = false, oneByN = false;
enum { enum {
IsAligned = true, IsAligned = true,
@ -122,10 +122,13 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
// tensor with N >= 1 of 1 element first and then broadcast. // tensor with N >= 1 of 1 element first and then broadcast.
EIGEN_STATIC_ASSERT((NumDims > 0), YOU_MADE_A_PROGRAMMING_MISTAKE); EIGEN_STATIC_ASSERT((NumDims > 0), YOU_MADE_A_PROGRAMMING_MISTAKE);
const InputDimensions& input_dims = m_impl.dimensions(); const InputDimensions& input_dims = m_impl.dimensions();
const Broadcast& broadcast = op.broadcast(); isCopy = true;
for (int i = 0; i < NumDims; ++i) { for (int i = 0; i < NumDims; ++i) {
eigen_assert(input_dims[i] > 0); eigen_assert(input_dims[i] > 0);
m_dimensions[i] = input_dims[i] * broadcast[i]; m_dimensions[i] = input_dims[i] * m_broadcast[i];
if (m_broadcast[i] != 1) {
isCopy = false;
}
} }
if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) { if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
@ -147,7 +150,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
if (input_dims[0] == 1) { if (input_dims[0] == 1) {
oneByN = true; oneByN = true;
for (int i = 1; i < NumDims; ++i) { for (int i = 1; i < NumDims; ++i) {
if (broadcast[i] != 1) { if (m_broadcast[i] != 1) {
oneByN = false; oneByN = false;
break; break;
} }
@ -155,7 +158,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
} else if (input_dims[NumDims-1] == 1) { } else if (input_dims[NumDims-1] == 1) {
nByOne = true; nByOne = true;
for (int i = 0; i < NumDims-1; ++i) { for (int i = 0; i < NumDims-1; ++i) {
if (broadcast[i] != 1) { if (m_broadcast[i] != 1) {
nByOne = false; nByOne = false;
break; break;
} }
@ -169,7 +172,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
nByOne = true; nByOne = true;
oneByN = true; oneByN = true;
for (int i = 1; i < NumDims-1; ++i) { for (int i = 1; i < NumDims-1; ++i) {
if (broadcast[i] != 1) { if (m_broadcast[i] != 1) {
nByOne = false; nByOne = false;
oneByN = false; oneByN = false;
break; break;
@ -197,9 +200,17 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
} }
if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) { if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
return coeffColMajor(index); if (isCopy) {
return m_impl.coeff(index);
} else {
return coeffColMajor(index);
}
} else { } else {
return coeffRowMajor(index); if (isCopy) {
return m_impl.coeff(index);
} else {
return coeffRowMajor(index);
}
} }
} }
@ -272,7 +283,9 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
} }
if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) { if (static_cast<int>(Layout) == static_cast<int>(ColMajor)) {
if (oneByN && !nByOne) { if (isCopy) {
return m_impl.template packet<LoadMode>(index);
} else if (oneByN && !nByOne) {
return packetNByOne<LoadMode>(index); return packetNByOne<LoadMode>(index);
} else if (!oneByN && nByOne) { } else if (!oneByN && nByOne) {
return packetOneByN<LoadMode>(index); return packetOneByN<LoadMode>(index);
@ -282,7 +295,9 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
return packetColMajor<LoadMode>(index); return packetColMajor<LoadMode>(index);
} }
} else { } else {
if (oneByN && !nByOne) { if (isCopy) {
return m_impl.template packet<LoadMode>(index);
} else if (oneByN && !nByOne) {
return packetOneByN<LoadMode>(index); return packetOneByN<LoadMode>(index);
} else if (!oneByN && nByOne) { } else if (!oneByN && nByOne) {
return packetNByOne<LoadMode>(index); return packetNByOne<LoadMode>(index);
@ -516,7 +531,7 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorOpCost
costPerCoeff(bool vectorized) const { costPerCoeff(bool vectorized) const {
double compute_cost = TensorOpCost::AddCost<Index>(); double compute_cost = TensorOpCost::AddCost<Index>();
if (NumDims > 0) { if (!isCopy && NumDims > 0) {
for (int i = NumDims - 1; i > 0; --i) { for (int i = NumDims - 1; i > 0; --i) {
compute_cost += TensorOpCost::DivCost<Index>(); compute_cost += TensorOpCost::DivCost<Index>();
if (internal::index_statically_eq<Broadcast>(i, 1)) { if (internal::index_statically_eq<Broadcast>(i, 1)) {