Swaps the content of two sparse matrices of the same type. * This is a fast operation that simply swaps the underlying pointers and parameters.

Constructs a read-write Map to a sparse matrix of size \a rows x \a cols, containing \a nnz non-zero coefficients, * stored as a sparse format a

Apply group operator

* Empty the pointer list */

\returns a const expression of the diagonal coefficients. */

Load a model from a checkpoint file. ### Parameters: - `pretrained_model_name_or_path`: path to the checkpoint file or repo

\returns a view of the upper triangular matrix U */

group multiplication

Checks if 'input_tensor' contains inf or nan values and clamps extreme values. Args: input_tensor (torch.Tensor): The loss tenso

\returns the inner-stride of the underlying dense matrix * \sa DenseCoeffsBase::innerStride() */

group inverse

Load model from file. Args: path (str): file path

convert element to 4x4 matrix

\returns the stored value of the symbol */

Initialize the MLP.

Applies radial or OpenCV distortion to the given 2D points. Args: extra_params (torch.Tensor or numpy.ndarray): Distortion parameter

\returns the norm of the quaternion's coefficients * \sa QuaternionBase::squaredNorm(), MatrixBase::norm() */

\internal * Resize the nonzero vector to \a size */

\sa MatrixBase::setIdentity() */

\brief Returns the y-translation by value. **/

\brief Returns the z-translation by value. **/

Resize an image using the specified backend.

Resizes the matrix to a \a rows x \a cols matrix and initializes it to zero. * * This function does not free the currently allocated memo

Args: index: [0, 1, 2, 3] 1D Tensor representing the position index of the token

Sets *this to the identity matrix. * This function also turns the matrix into compressed mode, and drop any reserved memory. */