code: def get_classification_dataset():
      import numpy as np
      import deepchem as dc
      from deepchem.feat.molecule_featurizers.conformer_featurizer import (
          RDKitConformerFeaturizer,
      )
  
      dir = os.path.dirname(os.path.abspath(__file__))
  
      featurizer = RDKitConformerFeaturizer()
      input_file = os.path.join(
          dir, "assets/example_classification.csv"
      )
      loader = dc.data.CSVLoader(
          tasks=["outcome"],
          feature_field="smiles",
          featurizer=featurizer,
      )
      dataset = loader.create_dataset(input_file)
      metric = dc.metrics.Metric(
          dc.metrics.roc_auc_score, np.mean, mode="classification"
      )
      return dataset, metric
  
file_path: deepchem/deepchem/models/tests/test_gnn3d.py
imports: import os
  import pytest
label_desc: Use image node_id 2 for calling a global function with example usage: get_classification_dataset() and returns: dataset,  metric