Create a new tensor of the same type and device.

Stack a list of objects with the same type and shape.

Create a new tensor of the same type and device.

Convert the underlying tensor to a numpy array.

Split the input into small patches with sliding window.

\returns the number of rows */

Resize the frame to a given size.

\returns a vector expression of the \a i -th column, * only the meaningful part is returned. * \warning the internal storage must be colum

Return file-like object for 'name'. name is a string for the file name within the ZIP file, or a ZipInfo object. mode should

Construct identity element with batch shape

\returns the value of the current coefficient.

\brief Reports whether previous computation was successful. * * \returns \c Success if computation was successful, * \c Num

\returns the row index of the current coefficient.

Size (width height) of the images, with shape (..., 2).

\returns the number of transpositions */

\returns the dimension in which the box holds */

Cast the underlying tensor to float.

\returns an expression of the transposed of the factored matrix. * * A typical usage is to solve for the transposed problem A^T x = b:

logarithm map

exponential map: x -> X

\returns the value of the matrix at position \a i, \a j * This function returns Scalar(0) if the element is an explicit \em zero */

\returns an expression of the adjoint of the factored matrix * * A typical usage is to solve for the adjoint problem A' x = b: * \co