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Self & | base () |
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const Self & | base () const |
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EIGEN_DEVICE_FUNC const EIGEN_STRONG_INLINE Scalar & | coeff () const |
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EIGEN_DEVICE_FUNC const EIGEN_STRONG_INLINE Scalar & | coeff (const array< Index, NumIndices > &indices) const |
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EIGEN_DEVICE_FUNC const EIGEN_STRONG_INLINE Scalar & | coeff (Index index) const |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar & | coeffRef () |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar & | coeffRef (const array< Index, NumIndices > &indices) |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar & | coeffRef (Index index) |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar * | data () |
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EIGEN_DEVICE_FUNC const EIGEN_STRONG_INLINE Scalar * | data () const |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index | dimension (std::size_t n) const |
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EIGEN_DEVICE_FUNC const EIGEN_STRONG_INLINE Dimensions & | dimensions () const |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar & | operator() () |
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EIGEN_DEVICE_FUNC const EIGEN_STRONG_INLINE Scalar & | operator() () const |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar & | operator() (const array< Index, NumIndices > &indices) |
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EIGEN_DEVICE_FUNC const EIGEN_STRONG_INLINE Scalar & | operator() (const array< Index, NumIndices > &indices) const |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar & | operator() (Index i0, Index i1) |
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EIGEN_DEVICE_FUNC const EIGEN_STRONG_INLINE Scalar & | operator() (Index i0, Index i1) const |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar & | operator() (Index i0, Index i1, Index i2) |
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EIGEN_DEVICE_FUNC const EIGEN_STRONG_INLINE Scalar & | operator() (Index i0, Index i1, Index i2) const |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar & | operator() (Index i0, Index i1, Index i2, Index i3) |
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EIGEN_DEVICE_FUNC const EIGEN_STRONG_INLINE Scalar & | operator() (Index i0, Index i1, Index i2, Index i3) const |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar & | operator() (Index i0, Index i1, Index i2, Index i3, Index i4) |
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EIGEN_DEVICE_FUNC const EIGEN_STRONG_INLINE Scalar & | operator() (Index i0, Index i1, Index i2, Index i3, Index i4) const |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar & | operator() (Index index) |
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EIGEN_DEVICE_FUNC const EIGEN_STRONG_INLINE Scalar & | operator() (Index index) const |
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template<typename OtherDerived > |
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Tensor & | operator= (const OtherDerived &other) |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Tensor & | operator= (const Tensor &other) |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar & | operator[] (Index index) |
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EIGEN_DEVICE_FUNC const EIGEN_STRONG_INLINE Scalar & | operator[] (Index index) const |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index | rank () const |
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EIGEN_DEVICE_FUNC void | resize () |
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EIGEN_DEVICE_FUNC void | resize (const array< Index, NumIndices > &dimensions) |
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EIGEN_DEVICE_FUNC void | resize (const DSizes< Index, NumIndices > &dimensions) |
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template<typename std::ptrdiff_t... Indices> |
EIGEN_DEVICE_FUNC void | resize (const Sizes< Indices... > &dimensions) |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index | size () const |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE | Tensor () |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE | Tensor (const array< Index, NumIndices > &dimensions) |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE | Tensor (const Self &other) |
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template<typename OtherDerived > |
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE | Tensor (const TensorBase< OtherDerived, ReadOnlyAccessors > &other) |
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template<typename OtherDerived > |
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE | Tensor (const TensorBase< OtherDerived, WriteAccessors > &other) |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE | Tensor (Index dim1) |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE | Tensor (Index dim1, Index dim2) |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE | Tensor (Index dim1, Index dim2, Index dim3) |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE | Tensor (Index dim1, Index dim2, Index dim3, Index dim4) |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE | Tensor (Index dim1, Index dim2, Index dim3, Index dim4, Index dim5) |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorChippingOp< DimId, Tensor< Scalar_, NumIndices_, Options_, IndexType_ > > | chip (const Index offset) |
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EIGEN_DEVICE_FUNC const EIGEN_STRONG_INLINE TensorChippingOp< DimId, const Tensor< Scalar_, NumIndices_, Options_, IndexType_ > > | chip (const Index offset) const |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorChippingOp< Dynamic, Tensor< Scalar_, NumIndices_, Options_, IndexType_ > > | chip (const Index offset, const Index dim) |
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EIGEN_DEVICE_FUNC const EIGEN_STRONG_INLINE TensorChippingOp< Dynamic, const Tensor< Scalar_, NumIndices_, Options_, IndexType_ > > | chip (const Index offset, const Index dim) const |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorConcatenationOp< const Axis, Tensor< Scalar_, NumIndices_, Options_, IndexType_ >, OtherDerived > | concatenate (const OtherDerived &other, const Axis &axis) |
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EIGEN_DEVICE_FUNC const EIGEN_STRONG_INLINE TensorConcatenationOp< const Axis, const Tensor< Scalar_, NumIndices_, Options_, IndexType_ >, const OtherDerived > | concatenate (const OtherDerived &other, const Axis &axis) const |
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TensorDevice< Tensor< Scalar_, NumIndices_, Options_, IndexType_ >, DeviceType > | device (const DeviceType &dev) |
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TensorAsyncDevice< Tensor< Scalar_, NumIndices_, Options_, IndexType_ >, DeviceType, DoneCallback > | device (const DeviceType &dev, DoneCallback done) |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Tensor< Scalar_, NumIndices_, Options_, IndexType_ > & | operator*= (const OtherDerived &other) |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Tensor< Scalar_, NumIndices_, Options_, IndexType_ > & | operator+= (const OtherDerived &other) |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Tensor< Scalar_, NumIndices_, Options_, IndexType_ > & | operator-= (const OtherDerived &other) |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Tensor< Scalar_, NumIndices_, Options_, IndexType_ > & | operator/= (const OtherDerived &other) |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorReshapingOp< const NewDimensions, Tensor< Scalar_, NumIndices_, Options_, IndexType_ > > | reshape (const NewDimensions &newDimensions) |
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EIGEN_DEVICE_FUNC const EIGEN_STRONG_INLINE TensorReshapingOp< const NewDimensions, const Tensor< Scalar_, NumIndices_, Options_, IndexType_ > > | reshape (const NewDimensions &newDimensions) const |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorReverseOp< const ReverseDimensions, Tensor< Scalar_, NumIndices_, Options_, IndexType_ > > | reverse (const ReverseDimensions &rev) |
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EIGEN_DEVICE_FUNC const EIGEN_STRONG_INLINE TensorReverseOp< const ReverseDimensions, const Tensor< Scalar_, NumIndices_, Options_, IndexType_ > > | reverse (const ReverseDimensions &rev) const |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Tensor< Scalar_, NumIndices_, Options_, IndexType_ > & | setConstant (const Scalar &val) |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Tensor< Scalar_, NumIndices_, Options_, IndexType_ > & | setRandom () |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Tensor< Scalar_, NumIndices_, Options_, IndexType_ > & | setRandom () |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Tensor< Scalar_, NumIndices_, Options_, IndexType_ > & | setZero () |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorShufflingOp< const Shuffle, Tensor< Scalar_, NumIndices_, Options_, IndexType_ > > | shuffle (const Shuffle &shfl) |
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EIGEN_DEVICE_FUNC const EIGEN_STRONG_INLINE TensorShufflingOp< const Shuffle, const Tensor< Scalar_, NumIndices_, Options_, IndexType_ > > | shuffle (const Shuffle &shfl) const |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorSlicingOp< const StartIndices, const Sizes, Tensor< Scalar_, NumIndices_, Options_, IndexType_ > > | slice (const StartIndices &startIndices, const Sizes &sizes) |
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EIGEN_DEVICE_FUNC const EIGEN_STRONG_INLINE TensorSlicingOp< const StartIndices, const Sizes, const Tensor< Scalar_, NumIndices_, Options_, IndexType_ > > | slice (const StartIndices &startIndices, const Sizes &sizes) const |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorStridingOp< const Strides, Tensor< Scalar_, NumIndices_, Options_, IndexType_ > > | stride (const Strides &strides) |
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EIGEN_DEVICE_FUNC const EIGEN_STRONG_INLINE TensorStridingOp< const Strides, const Tensor< Scalar_, NumIndices_, Options_, IndexType_ > > | stride (const Strides &strides) const |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorStridingSlicingOp< const StartIndices, const StopIndices, const Strides, Tensor< Scalar_, NumIndices_, Options_, IndexType_ > > | stridedSlice (const StartIndices &startIndices, const StopIndices &stopIndices, const Strides &strides) |
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EIGEN_DEVICE_FUNC const EIGEN_STRONG_INLINE TensorStridingSlicingOp< const StartIndices, const StopIndices, const Strides, const Tensor< Scalar_, NumIndices_, Options_, IndexType_ > > | stridedSlice (const StartIndices &startIndices, const StopIndices &stopIndices, const Strides &strides) const |
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EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TensorLayoutSwapOp< Tensor< Scalar_, NumIndices_, Options_, IndexType_ > > | swap_layout () |
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EIGEN_DEVICE_FUNC const EIGEN_STRONG_INLINE TensorLayoutSwapOp< const Tensor< Scalar_, NumIndices_, Options_, IndexType_ > > | swap_layout () const |
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template<typename Scalar_, int NumIndices_, int Options_, typename IndexType_>
class Eigen::Tensor< Scalar_, NumIndices_, Options_, IndexType_ >
The tensor class.
The Tensor class is the work-horse for all dense tensors within Eigen.
The Tensor class encompasses only dynamic-size objects so far.
The first two template parameters are required:
- Template Parameters
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Scalar_ | Numeric type, e.g. float, double, int or std::complex<float> . User defined scalar types are supported as well (see here). |
NumIndices_ | Number of indices (i.e. rank of the tensor) |
The remaining template parameters are optional – in most cases you don't have to worry about them.
- Template Parameters
-
Options_ | A combination of either RowMajor or ColMajor, and of either AutoAlign or DontAlign. The former controls storage order, and defaults to column-major. The latter controls alignment, which is required for vectorization. It defaults to aligning tensors. Note that tensors currently do not support any operations that profit from vectorization. Support for such operations (i.e. adding two tensors etc.) is planned. |
You can access elements of tensors using normal subscripting:
This class can be extended with the help of the plugin mechanism described on the page Extending MatrixBase (and other classes) by defining the preprocessor symbol EIGEN_TENSOR_PLUGIN
.
Some notes:
- Relation to other parts of Eigen:
- The midterm development goal for this class is to have a similar hierarchy as Eigen uses for matrices, so that taking blocks or using tensors in expressions is easily possible, including an interface with the vector/matrix code by providing .asMatrix() and .asVector() (or similar) methods for rank 2 and 1 tensors. However, currently, the Tensor class does not provide any of these features and is only available as a stand-alone class that just allows for coefficient access. Also, when fixed-size tensors are implemented, the number of template arguments is likely to change dramatically.
TopicStorageOrders
Definition at line 63 of file Tensor.h.