code: def test_chemception_regression():
      n_tasks = 5
      dataset, metric = get_dataset(
          mode="regression", featurizer="smiles2img", n_tasks=n_tasks
      )
      model = ChemCeption(
          n_tasks=n_tasks,
          img_spec="engd",
          model_dir=None,
          mode="regression",
      )
      model.fit(dataset, nb_epoch=300)
      scores = model.evaluate(dataset, [metric], [])
      assert scores["mean_absolute_error"] < 0.1
  
file_path: deepchem/deepchem/models/tests/test_chemnet_models.py
imports: import os
  import numpy
  import tempfile
  import pytest
  from flaky import flaky
  import deepchem
  from deepchem.feat import create_char_to_idx, SmilesToSeq, SmilesToImage
  from deepchem.molnet.load_function.chembl25_datasets import CHEMBL25_TASKS
label_desc: Use image node_id 2 for calling a global function with example usage: test_chemception_regression() without return types