Eigenunsupported
3.3.90 (mercurial changeset f3a22f35b044)

This module provides a Tensor class for storing arbitrarily indexed objects.
Classes  
class  Eigen::Tensor< Scalar_, NumIndices_, Options_, IndexType_ > 
The tensor class. More...  
class  TensorAssign 
The tensor assignment class. More...  
class  Eigen::TensorBase< Derived, AccessLevel > 
The tensor base class. More...  
class  TensorBroadcasting 
Tensor broadcasting class. More...  
class  Eigen::TensorConcatenationOp< Axis, LhsXprType, RhsXprType > 
Tensor concatenation class. More...  
class  TensorContraction 
Tensor contraction class. More...  
class  Eigen::TensorConversionOp< TargetType, XprType > 
Tensor conversion class. This class makes it possible to vectorize type casting operations when the number of scalars per packet in the source and the destination type differ. More...  
class  TensorConvolution 
Tensor convolution class. More...  
class  Eigen::TensorCustomBinaryOp< CustomBinaryFunc, LhsXprType, RhsXprType > 
Tensor custom class. More...  
class  Eigen::TensorCustomUnaryOp< CustomUnaryFunc, XprType > 
Tensor custom class. More...  
class  Eigen::TensorDevice< ExpressionType, DeviceType > 
Pseudo expression providing an operator = that will evaluate its argument on the specified computing 'device' (GPU, thread pool, ...) More...  
class  Eigen::TensorEvaluator< Derived, Device > 
A cost model used to limit the number of threads used for evaluating tensor expression. More...  
class  TensorExecutor 
The tensor executor class. More...  
class  TensorExpr 
Tensor expression classes. More...  
class  Eigen::TensorFixedSize< Scalar_, Dimensions_, Options_, IndexType > 
The fixed sized version of the tensor class. More...  
class  TensorForcedEval 
Tensor reshaping class. More...  
class  TensorGenerator 
Tensor generator class. More...  
class  TensorImagePatch 
Patch extraction specialized for image processing. This assumes that the input has a least 3 dimensions ordered as follow: 1st dimension: channels (of size d) 2nd dimension: rows (of size r) 3rd dimension: columns (of size c) There can be additional dimensions such as time (for video) or batch (for bulk processing after the first 3. Calling the image patch code with patch_rows and patch_cols is equivalent to calling the regular patch extraction code with parameters d, patch_rows, patch_cols, and 1 for all the additional dimensions. More...  
class  TensorIndexTuple 
Tensor + Index Tuple class. More...  
class  TensorInflation 
Tensor inflation class. More...  
class  TensorKChippingReshaping 
A chip is a thin slice, corresponding to a column or a row in a 2d tensor. More...  
class  TensorLayoutSwap 
Swap the layout from colmajor to rowmajor, or rowmajor to colmajor, and invert the order of the dimensions. More...  
class  Eigen::TensorMap< PlainObjectType, Options_, MakePointer_ > 
A tensor expression mapping an existing array of data. More...  
class  TensorPadding 
Tensor padding class. At the moment only padding with a constant value is supported. More...  
class  TensorPatch 
Tensor patch class. More...  
class  TensorReduction 
Tensor reduction class. More...  
class  Eigen::TensorRef< PlainObjectType > 
A reference to a tensor expression The expression will be evaluated lazily (as much as possible). More...  
class  TensorReshaping 
Tensor reshaping class. More...  
class  TensorReverse 
Tensor reverse elements class. More...  
class  TensorScan 
Tensor scan class. More...  
class  TensorShuffling 
Tensor shuffling class. More...  
class  TensorSlicing 
Tensor slicing class. More...  
class  TensorStriding 
Tensor striding class. More...  
class  TensorTupleIndex 
Converts to Tensor<Tuple<Index, Scalar> > and reduces to Tensor<Index>. More...  
class  TensorVolumePatch 
Patch extraction specialized for processing of volumetric data. This assumes that the input has a least 4 dimensions ordered as follows: More...  