class_docstr: A regularizer for the soft orthogonality constraints from [wang2014]_.
class_docstr_tok: ["A","regularizer","for","the","soft","orthogonality","constraints","from","[","wang2014","]","_","."]
code: def forward(
      self, x: torch.FloatTensor
  ) -> torch.FloatTensor:  # noqa: D102
      raise NotImplementedError(
          f"{self.__class__.__name__} regularizer is order-sensitive!"
      )
  
imports: from __future__ import annotations
  import warnings
  from abc import ABC, abstractmethod
  from typing import Any, ClassVar, Iterable, Mapping, Optional
  import torch
  from class_resolver import ClassResolver, normalize_string
  from torch import nn
  from torch.nn import functional
  from .utils import lp_norm, powersum_norm
label_desc: Use image node_id 2 for calling the OrthogonalityRegularizer obj's underlying member method code with example usage: obj.forward(x) without return types