class_docstr: generate local graphlet numbers as features. The implementation refers to [#]_ .
  
  References
  ----------
  .. [#] Ahmed, N. K., Willke, T. L., & Rossi, R. A. (2016).
      Estimation of local subgraph counts. Proceedings - 2016 IEEE International Conference on Big Data, Big Data 2016, 586–595.
      https://doi.org/10.1109/BigData.2016.7840651
code: def _extract_nodes_feature(
      self, data: autogl.data.Data
  ) -> torch.Tensor:
      result: np.ndarray = _Graphlet(data).get_gdvs()
      return torch.from_numpy(result)
  
file_path: AutoGL/autogl/module/preprocessing/feature_engineering/_generators/_graphlet.py
imports: import logging
  import numpy
  import torch
  from tqdm import tqdm
  import autogl
  from ._basic import BaseFeatureGenerator
  from ..._data_preprocessor_registry import DataPreprocessorUniversalRegistry
label_desc: Use image node_id 1 for calling the GraphletGenerator obj's underlying member method code with example usage: obj._extract_nodes_feature(data) and returns: torch