te spectral norm. Default: ``1``.
        eps (float, optional): epsilon for numerical stability in
            calculating norms. Default: ``1e-12``.
        dim (int, optional): dimension corresponding to number of outputs.
            Default: ``0``, except for modules that are instances of
            ConvTranspose{1,2,3}d, when it is ``1``

    Returns:
        The original module with a new parametrization registered to the specified
        weight

    Example::

        >>> # xdoctest: +REQUIRES(env:TORCH_DOCTEST_LAPACK)
        >>> # xdoctest: +IGNORE_WANT("non-deterministic")
        >>> snm = spectral_norm(nn.Linear(20, 40))
        >>> snm
        ParametrizedLinear(
          in_features=20, out_features=40, bias=True
          (parametrizations): ModuleDict(
            (weight): ParametrizationList(
              (0): _SpectralNorm()
            )
          )
        )
        >>> torch.linalg.matrix_norm(snm.weight, 2)
        tensor(1.0081, grad_fn=<AmaxBackward0>)
    NrU