mlx.core.linalg.eigvals#
- eigvals(a: array, *, stream: Optional[Union[Stream, Device]] = None) array #
Compute the eigenvalues of a square matrix.
This function differs from
numpy.linalg.eigvals()
in that the return type is always complex even if the eigenvalues are all real.This function supports arrays with at least 2 dimensions. When the input has more than two dimensions, the eigenvalues are computed for each matrix in the last two dimensions.
- Parameters:
- Returns:
The eigenvalues (not necessarily in order).
- Return type:
Example
>>> A = mx.array([[1., -2.], [-2., 1.]]) >>> eigenvalues = mx.linalg.eigvals(A, stream=mx.cpu) >>> eigenvalues array([3+0j, -1+0j], dtype=complex64)