code: def test_atomic_convolution_model():
      from deepchem.models.torch_models import AtomConvModel
  
      # For simplicity, let's assume both molecules have same number of
      # atoms.
      N_atoms = 5
      batch_size = 1
      atomic_convnet = AtomConvModel(
          n_tasks=1,
          batch_size=batch_size,
          layer_sizes=[10],
          frag1_num_atoms=N_atoms,
          frag2_num_atoms=N_atoms,
          complex_num_atoms=N_atoms * 2,
          dropouts=0.0,
          learning_rate=0.003,
      )
  
      # Creates a set of dummy features that contain the coordinate and
      # neighbor-list features required by the AtomicConvModel.
      features = []
      frag1_coords = np.random.rand(N_atoms, 3)
      frag1_nbr_list = {0: [], 1: [], 2: [], 3: [], 4: []}
      frag1_z = np.random.randint(10, size=(N_atoms))
      frag2_coords = np.random.rand(N_atoms, 3)
      frag2_nbr_list = {0: [], 1: [], 2: [], 3: [], 4: []}
      frag2_z = np.random.randint(10, size=(N_atoms))
      system_coords = np.random.rand(2 * N_atoms, 3)
      system_nbr_list = {
          0: [],
          1: [],
          2: [],
          3: [],
          4: [],
          5: [],
          6: [],
          7: [],
          8: [],
          9: [],
      }
      system_z = np.random.randint(10, size=(2 * N_atoms))
  
      features.append(
          (
              frag1_coords,
              frag1_nbr_list,
              frag1_z,
              frag2_coords,
              frag2_nbr_list,
              frag2_z,
              system_coords,
              system_nbr_list,
              system_z,
          )
      )
      features = np.asarray(features, dtype=object)
      labels = np.random.rand(batch_size)
      train = NumpyDataset(features, labels)
      atomic_convnet.fit(train, nb_epoch=200)
      preds = atomic_convnet.predict(train)
      assert np.allclose(labels, preds, atol=0.01)
  
imports: import pytest
  import numpy
  from deepchem.data import NumpyDataset
label_desc: Use image node_id 3 for calling a global function with example usage: test_atomic_convolution_model() without return types