code: def inference_forward(self, collate_data, KG_graph):
      e1_tensor = collate_data["e1_tensor"]
      rel_tensor = collate_data["rel_tensor"]
      if self.cfg["cuda"]:
          e1_tensor = e1_tensor.to("cuda")
          rel_tensor = rel_tensor.to("cuda")
      return self.model(e1_tensor, rel_tensor, KG_graph)
  
imports: import argparse
  import os
  import numpy
  import torch
  import torch.backends.cudnn
  import torch.nn
  from torch.utils.data import DataLoader
  from graph4nlp.pytorch.datasets.kinship import KinshipDataset
  from graph4nlp.pytorch.modules.utils.config_utils import get_yaml_config
  from graph4nlp.pytorch.modules.utils.logger import Logger
  from .model import Complex, ConvE, Distmult, GCNComplex, GCNDistMult, GGNNDistMult
label_desc: Use image node_id 5 for calling the KGC obj's underlying member method code with example usage: obj.inference_forward(collate_data, KG_graph) and returns: self