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TensorEval are now typed on the device: this will make it possible to use partial template specialization to optimize the strategy of each evaluator for each device type.

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Started work on partial evaluations.
This commit is contained in:
Benoit Steiner
2014-06-10 09:14:44 -07:00
parent a77458a8ff
commit 925fb6b937
9 changed files with 129 additions and 102 deletions
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20
unsupported/Eigen/CXX11/src/Tensor/TensorConvolution.h
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@@ -94,27 +94,27 @@ class TensorConvolutionOp : public TensorBase<TensorConvolutionOp<Indices, Input
};
template<typename Indices, typename InputArgType, typename KernelArgType>
struct TensorEvaluator<const TensorConvolutionOp<Indices, InputArgType, KernelArgType> >
template<typename Indices, typename InputArgType, typename KernelArgType, typename Device>
struct TensorEvaluator<const TensorConvolutionOp<Indices, InputArgType, KernelArgType>, Device>
{
typedef TensorConvolutionOp<Indices, InputArgType, KernelArgType> XprType;
static const int NumDims = TensorEvaluator<InputArgType>::Dimensions::count;
static const int NumDims = TensorEvaluator<InputArgType, Device>::Dimensions::count;
static const int KernelDims = Indices::size;
typedef typename XprType::Index Index;
typedef DSizes<Index, NumDims> Dimensions;
enum {
IsAligned = TensorEvaluator<InputArgType>::IsAligned & TensorEvaluator<KernelArgType>::IsAligned,
IsAligned = TensorEvaluator<InputArgType, Device>::IsAligned & TensorEvaluator<KernelArgType, Device>::IsAligned,
PacketAccess = /*TensorEvaluator<InputArgType>::PacketAccess & TensorEvaluator<KernelArgType>::PacketAccess */
false,
};
TensorEvaluator(const XprType& op)
: m_inputImpl(op.inputExpression()), m_kernelImpl(op.kernelExpression()), m_dimensions(op.inputExpression().dimensions())
TensorEvaluator(const XprType& op, const Device& device)
: m_inputImpl(op.inputExpression(), device), m_kernelImpl(op.kernelExpression(), device), m_dimensions(op.inputExpression().dimensions())
{
const typename TensorEvaluator<InputArgType>::Dimensions& input_dims = m_inputImpl.dimensions();
const typename TensorEvaluator<KernelArgType>::Dimensions& kernel_dims = m_kernelImpl.dimensions();
const typename TensorEvaluator<InputArgType, Device>::Dimensions& input_dims = m_inputImpl.dimensions();
const typename TensorEvaluator<KernelArgType, Device>::Dimensions& kernel_dims = m_kernelImpl.dimensions();
for (int i = 0; i < NumDims; ++i) {
if (i > 0) {
@@ -200,8 +200,8 @@ struct TensorEvaluator<const TensorConvolutionOp<Indices, InputArgType, KernelAr
array<Index, KernelDims> m_indexStride;
array<Index, KernelDims> m_kernelStride;
Dimensions m_dimensions;
TensorEvaluator<InputArgType> m_inputImpl;
TensorEvaluator<KernelArgType> m_kernelImpl;
TensorEvaluator<InputArgType, Device> m_inputImpl;
TensorEvaluator<KernelArgType, Device> m_kernelImpl;
};