code: def test_graph_conv_regression_uncertainty():
      tasks, dataset, _, _ = get_dataset("regression", "GraphConv")
  
      batch_size = 10
      model = GraphConvModel(
          len(tasks),
          batch_size=batch_size,
          batch_normalize=False,
          mode="regression",
          dropout=0.1,
          uncertainty=True,
      )
  
      model.fit(dataset, nb_epoch=100)
  
      # Predict the output and uncertainty.
      pred, std = model.predict_uncertainty(dataset)
      mean_error = np.mean(np.abs(dataset.y - pred))
      mean_value = np.mean(np.abs(dataset.y))
      mean_std = np.mean(std)
      assert mean_error < 0.5 * mean_value
      assert mean_std > 0.5 * mean_error
      assert mean_std < mean_value
  
imports: import os
  import numpy
  import pytest
  from scipy import io
  from deepchem.data import NumpyDataset, CSVLoader
  from deepchem.trans import DAGTransformer
  from deepchem.molnet import load_bace_classification, load_delaney
  from deepchem.feat import ConvMolFeaturizer
  from deepchem.metrics import Metric, roc_auc_score, mean_absolute_error
  from deepchem.utils.data_utils import download_url, get_data_dir
  from flaky import flaky
label_desc: Use image node_id 5 for calling a global function with example usage: test_graph_conv_regression_uncertainty() without return types