class_docstr: An implementation of `"GL2Vec" <https://link.springer.com/chapter/10.1007/978-3-030-36718-3_1>`_
  from the ICONIP '19 paper "GL2vec: Graph Embedding Enriched by Line Graphs with Edge Features".
  First, the algorithm creates the line graph of each graph in the graph dataset.
  The procedure creates Weisfeiler-Lehman tree features for nodes in graphs. Using
  these features a document (graph) - feature co-occurrence matrix is decomposed in order
  to generate representations for the graphs.
  
  Args:
      wl_iterations (int): Number of Weisfeiler-Lehman iterations. Default is 2.
      dimensions (int): Dimensionality of embedding. Default is 128.
      workers (int): Number of cores. Default is 4.
      down_sampling (float): Down sampling frequency. Default is 0.0001.
      epochs (int): Number of epochs. Default is 10.
      learning_rate (float): HogWild! learning rate. Default is 0.025.
      min_count (int): Minimal count of graph feature occurrences. Default is 5.
      seed (int): Random seed for the model. Default is 42.
      erase_base_features: (bool): Whether to delete the base features.
docstr: Getting the embedding of graphs.
  
  Return types:
      * **embedding** *(Numpy array)* - The embedding of graphs.
docstr_tok: ["Getting","the","embedding","of","graphs",".","Return","types",":","*","*","*","embedding","*","*","*","(","Numpy","array",")","*","-","The","embedding","of","graphs","."]
code: def get_embedding(self) -> np.array:
      r"""Getting the embedding of graphs.
  
      Return types:
          * **embedding** *(Numpy array)* - The embedding of graphs.
      """
      return np.array(self._embedding)
  
file_path: karateclub/karateclub/graph_embedding/gl2vec.py
imports: from typing import Optional
  import numpy
  import networkx
  from typing import List
  from karateclub.estimator import Estimator
  from gensim.models.doc2vec import Doc2Vec, TaggedDocument
  from karateclub.utils.treefeatures import WeisfeilerLehmanHashing
label_desc: Use image node_id 4 for calling the GL2Vec obj's underlying member method code with example usage: obj.get_embedding() and returns: np