class_docstr: Notes
  -----
  a graph feature generation method. This is a simple wrapper of NetLSD [#]_.
  References
  ----------
  .. [#] A. Tsitsulin, D. Mottin, P. Karras, A. Bronstein, and E. Müller, “NetLSD: Hearing the shape of a graph,”
   Proc. ACM SIGKDD Int. Conf. Knowl. Discov. Data Min., pp. 2347–2356, 2018.
code: def _transform(self, data):
      dsc = torch.FloatTensor(
          [netlsd.heat(data.G, *self._args, **self._kwargs)]
      )
      data.gf = torch.cat([data.gf, dsc], dim=1)
      return data
  
file_path: AutoGL/autogl/module/_feature/graph/netlsd.py
imports: import netlsd
  from .base import BaseGraph
  import numpy
  import torch
  from ..None import register_feature
label_desc: Use image node_id 2 for calling the SgNetLSD obj's underlying member method code with example usage: obj._transform(data) and returns: data