class_docstr: ```
  Link preprocessing base class
  ```
class_docstr_tok: ["``","`","Link","preprocessing","base","class","``","`"]
docstr: ```
  preprocess training set
  Args:
    G (networkx graph): networkx graph
    edge_ids(list): list of tuples representing edge ids
    edge_labels(list): edge labels (1 or 0 to indicated whether it is a true edge in original graph or not)
  ```
docstr_tok: ["``","`","preprocess","training","set","Args",":","G","(","networkx","graph",")",":","networkx","graph","edge_ids","(","list",")",":","list","of","tuples","representing","edge","ids","edge_labels","(","list",")",":","edge","labels","(","1","or","0","to","indicated","whether","it","is","a","true","edge","in","original","graph","or","not",")","``","`"]
code: def preprocess_valid(self, G, edge_ids, edge_labels):
      """
      ```
      preprocess training set
      Args:
        G (networkx graph): networkx graph
        edge_ids(list): list of tuples representing edge ids
        edge_labels(list): edge labels (1 or 0 to indicated whether it is a true edge in original graph or not)
      ```
      """
      return self.preprocess_train(
          G, edge_ids, edge_labels, mode="valid"
      )
  
imports: from ..None import utils
  from ..imports import *
  from ..preprocessor import Preprocessor
label_desc: Use image node_id 6 for calling the LinkPreprocessor obj's underlying member method code with example usage: obj.preprocess_valid(G, edge_ids, edge_labels) and returns: self