Eigenunsupported
3.4.90 (git rev e3e74001f7c4bf95f0dde572e8a08c5b2918a3ab)

The tensor class.
The Tensor class is the workhorse for all dense tensors within Eigen.
The Tensor class encompasses only dynamicsize objects so far.
The first two template parameters are required:
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.
Options_  A combination of either RowMajor or ColMajor, and of either AutoAlign or DontAlign. The former controls storage order, and defaults to columnmajor. 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:
Public Member Functions  
void  resize (const array< Index, NumIndices > &dimensions) 
template<typename std::ptrdiff_t... Indices>  
void  resize (const Sizes< Indices... > &dimensions) 
Tensor (const array< Index, NumIndices > &dimensions)  

inlineexplicit 
Normal Dimension

inline 
Normal Dimension

inline 
Custom Dimension