code: def test_infographstar_regression_semisupervised():
      from deepchem.models.torch_models.infograph import (
          InfoGraphStarModel,
      )
      import torch
  
      torch.manual_seed(123)
      dataset, metric = get_regression_dataset()
      num_feat = 30
      edge_dim = 11
      dim = 128
      model = InfoGraphStarModel(
          num_feat,
          edge_dim,
          dim,
          num_gc_layers=2,
          task="semisupervised",
      )
  
      model.fit(dataset, nb_epoch=100)
      scores = model.evaluate(dataset, [metric])
      assert scores["mean_absolute_error"] < 0.2
  
imports: import os
  import pytest
  import numpy
  import deepchem
  from deepchem.feat.molecule_featurizers import MolGraphConvFeaturizer
label_desc: Use image node_id 7 for calling a global function with example usage: test_infographstar_regression_semisupervised() without return types