code: def test_multitask_regressor_delaney_uncertainty():
      """Test computing uncertainty on a larger dataset."""
      tasks, datasets, transformers = dc.molnet.load_delaney("ECFP")
      train_dataset, valid_dataset, test_dataset = datasets
      model = dc.models.MultitaskRegressor(
          len(tasks), 1024, uncertainty=True
      )
      model.fit(train_dataset, nb_epoch=20)
      metric = dc.metrics.Metric(dc.metrics.pearsonr)
      scores = model.evaluate(test_dataset, [metric], transformers)
      assert scores["pearsonr"] > 0.5
  
imports: import os
  import numpy
  import pytest
  from flaky import flaky
  from sklearn.ensemble import RandomForestClassifier
  from sklearn.ensemble import RandomForestRegressor
  import deepchem
  from deepchem.models.optimizers import Adam
label_desc: Use image node_id 23 for calling a global function with example usage: test_multitask_regressor_delaney_uncertainty() without return types