class_docstr: Does sanity checks on pose generation.
class_docstr_tok: ["Does","sanity","checks","on","pose","generation","."]
docstr: Test that scoring model and featurizer are invoked correctly.
docstr_tok: ["Test","that","scoring","model","and","featurizer","are","invoked","correctly","."]
code: def test_scoring_model_and_featurizer(self):
      """Test that scoring model and featurizer are invoked correctly."""
  
      class DummyFeaturizer(ComplexFeaturizer):
          def featurize(self, complexes, *args, **kwargs):
              return np.zeros((len(complexes), 5))
  
      class DummyModel(Model):
          def predict(self, dataset, *args, **kwargs):
              return np.zeros(len(dataset))
  
      class DummyPoseGenerator(PoseGenerator):
          def generate_poses(self, *args, **kwargs):
              return [None]
  
      featurizer = DummyFeaturizer()
      scoring_model = DummyModel()
      pose_generator = DummyPoseGenerator()
      docker = dc.dock.Docker(pose_generator, featurizer, scoring_model)
      outputs = docker.dock(None)
      assert list(outputs) == [(None, np.array([0.0]))]
  
file_path: deepchem/deepchem/dock/tests/test_docking.py
imports: import os
  import platform
  import unittest
  import pytest
  import logging
  import numpy
  import deepchem
  from deepchem.feat import ComplexFeaturizer
  from deepchem.models import Model
  from deepchem.dock.pose_generation import PoseGenerator
label_desc: Use image node_id 7 for calling the TestDocking obj's underlying member method code with example usage: obj.test_scoring_model_and_featurizer() and returns: np, np, list