Source code for geotorch.glp

from .fixedrank import FixedRank
from .exceptions import VectorError, NonSquareError
from .utils import _extra_repr

[docs]class GLp(FixedRank): def __init__(self, size, f="softplus", triv="expm"): r""" Manifold of invertible matrices Args: size (torch.size): Size of the tensor to be parametrized f (str or callable or pair of callables): Optional. Either: - ``"softplus"`` - A callable that maps real numbers to the interval :math:`(0, \infty)` - A pair of callables such that the first maps the real numbers to :math:`(0, \infty)` and the second is a (right) inverse of the first Default: ``"softplus"`` triv (str or callable): Optional. A map that maps skew-symmetric matrices onto the orthogonal matrices surjectively. This is used to optimize the :math:`U` and :math:`V` in the SVD. It can be one of ``["expm", "cayley"]`` or a custom callable. Default: ``"expm"`` """ super().__init__(size, GLp.rank(size), f, triv) @classmethod def rank(cls, size): if len(size) < 2: raise VectorError(cls.__name__, size) n, k = size[-2:] if n != k: raise NonSquareError(cls.__name__, size) return n def extra_repr(self): return _extra_repr(n=self.n, tensorial_size=self.tensorial_size)