code: def test_vina_free_energy():
      """Test invoking VinaFreeEnergy."""
      n_atoms = 5
      m_nbrs = 1
      ndim = 3
      nbr_cutoff = 1
      start = 0
      stop = 4
      X = np.random.rand(n_atoms, ndim).astype(np.float32)
      Z = np.random.randint(0, 2, (n_atoms)).astype(np.float32)
      layer = layers.VinaFreeEnergy(
          n_atoms, m_nbrs, ndim, nbr_cutoff, start, stop
      )
      result = layer([X, Z])
      assert len(layer.trainable_variables) == 6
      assert result.shape == tuple()
  
      # Creating a second layer should produce different results, since it has
      # different random weights.
  
      layer2 = layers.VinaFreeEnergy(
          n_atoms, m_nbrs, ndim, nbr_cutoff, start, stop
      )
      result2 = layer2([X, Z])
      assert not np.allclose(result, result2)
  
      # But evaluating the first layer again should produce the same result as before.
  
      result3 = layer([X, Z])
      assert np.allclose(result, result3)
  
imports: import deepchem
  import numpy
  import pytest
  import os
label_desc: Use image node_id 16 for calling a global function with example usage: test_vina_free_energy() without return types