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Class List
Here are the classes, structs, unions and interfaces with brief descriptions:
[detail level 1234]
 NEigenNamespace containing all symbols from the Eigen library
 CTensorAssignThe tensor assignment class
 CTensorBroadcastingTensor broadcasting class
 CTensorContractionTensor contraction class
 CTensorConvolutionTensor convolution class
 CTensorExecutorThe tensor executor class
 CTensorExprTensor expression classes
 CTensorFFTTensor FFT class
 CTensorForcedEvalTensor reshaping class
 CTensorImagePatchPatch 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
 CTensorIndexTupleTensor + Index Tuple class
 CTensorInflationTensor inflation class
 CTensorKChippingReshapingA chip is a thin slice, corresponding to a column or a row in a 2-d tensor
 CTensorLayoutSwapSwap the layout from col-major to row-major, or row-major to col-major, and invert the order of the dimensions
 CTensorPaddingTensor padding class. At the moment only padding with a constant value is supported
 CTensorPatchTensor patch class
 CTensorReductionTensor reduction class
 CTensorReshapingTensor reshaping class
 CTensorReverseTensor reverse elements class
 CTensorScanTensor scan class
 CTensorShufflingTensor shuffling class
 CTensorSlicingTensor slicing class
 CTensorStridingTensor striding class
 CTensorTraceTensor Trace class
 CTensorTupleIndexConverts to Tensor<Tuple<Index, Scalar> > and reduces to Tensor<Index>
 CTensorVolumePatchPatch extraction specialized for processing of volumetric data. This assumes that the input has a least 4 dimensions ordered as follows: