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Added static assertions to avoid misuses of padding, broadcasting and concatenation ops.

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This commit is contained in:
Benoit Steiner 2015-11-06 10:26:19 -08:00
parent 6857a35a11
commit 53432a17b2
3 changed files with 12 additions and 1 deletions
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4
unsupported/Eigen/CXX11/src/Tensor/TensorBroadcasting.h
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@ -99,6 +99,10 @@ struct TensorEvaluator<const TensorBroadcastingOp<Broadcast, ArgType>, Device>
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device) EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
: m_impl(op.expression(), device) : m_impl(op.expression(), device)
{ {
// The broadcasting op doesn't change the rank of the tensor. One can't broadcast a scalar
// and store the result in a scalar. Instead one should reshape the scalar into a a N-D
// tensor with N >= 1 of 1 element first and then broadcast.
EIGEN_STATIC_ASSERT(NumDims > 0, YOU_MADE_A_PROGRAMMING_MISTAKE);
const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions(); const typename TensorEvaluator<ArgType, Device>::Dimensions& input_dims = m_impl.dimensions();
const Broadcast& broadcast = op.broadcast(); const Broadcast& broadcast = op.broadcast();
for (int i = 0; i < NumDims; ++i) { for (int i = 0; i < NumDims; ++i) {

4
unsupported/Eigen/CXX11/src/Tensor/TensorConcatenation.h
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@ -131,7 +131,9 @@ struct TensorEvaluator<const TensorConcatenationOp<Axis, LeftArgType, RightArgTy
: m_leftImpl(op.lhsExpression(), device), m_rightImpl(op.rhsExpression(), device), m_axis(op.axis()) : m_leftImpl(op.lhsExpression(), device), m_rightImpl(op.rhsExpression(), device), m_axis(op.axis())
{ {
EIGEN_STATIC_ASSERT((static_cast<int>(TensorEvaluator<LeftArgType, Device>::Layout) == static_cast<int>(TensorEvaluator<RightArgType, Device>::Layout) || NumDims == 1), YOU_MADE_A_PROGRAMMING_MISTAKE); EIGEN_STATIC_ASSERT((static_cast<int>(TensorEvaluator<LeftArgType, Device>::Layout) == static_cast<int>(TensorEvaluator<RightArgType, Device>::Layout) || NumDims == 1), YOU_MADE_A_PROGRAMMING_MISTAKE);
EIGEN_STATIC_ASSERT(NumDims == RightNumDims, YOU_MADE_A_PROGRAMMING_MISTAKE) EIGEN_STATIC_ASSERT(NumDims == RightNumDims, YOU_MADE_A_PROGRAMMING_MISTAKE);
EIGEN_STATIC_ASSERT(NumDims > 0, YOU_MADE_A_PROGRAMMING_MISTAKE);
eigen_assert(0 <= m_axis && m_axis < NumDims); eigen_assert(0 <= m_axis && m_axis < NumDims);
const Dimensions& lhs_dims = m_leftImpl.dimensions(); const Dimensions& lhs_dims = m_leftImpl.dimensions();
const Dimensions& rhs_dims = m_rightImpl.dimensions(); const Dimensions& rhs_dims = m_rightImpl.dimensions();

5
unsupported/Eigen/CXX11/src/Tensor/TensorPadding.h
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@ -98,6 +98,11 @@ struct TensorEvaluator<const TensorPaddingOp<PaddingDimensions, ArgType>, Device
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device) EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorEvaluator(const XprType& op, const Device& device)
: m_impl(op.expression(), device), m_padding(op.padding()) : m_impl(op.expression(), device), m_padding(op.padding())
{ {
// The padding op doesn't change the rank of the tensor. Directly padding a scalar would lead
// to a vector, which doesn't make sense. Instead one should reshape the scalar into a vector
// of 1 element first and then pad.
EIGEN_STATIC_ASSERT(NumDims > 0, YOU_MADE_A_PROGRAMMING_MISTAKE);
// Compute dimensions // Compute dimensions
m_dimensions = m_impl.dimensions(); m_dimensions = m_impl.dimensions();
for (int i = 0; i < NumDims; ++i) { for (int i = 0; i < NumDims; ++i) {