code: def test_mxmnet_sphericalbasis():
      """Test for MXMNetSphericalBasisLayer"""
  
      dist = torch.tensor([0.5, 1.0, 2.0, 3.0])
      angle = torch.tensor([0.1, 0.2, 0.3, 0.4])
      idx_kj = torch.tensor([0, 1, 2, 3])
      spherical_layer = (
          dc.models.torch_models.layers.MXMNetSphericalBasisLayer(
              envelope_exponent=2,
              num_spherical=2,
              num_radial=2,
              cutoff=2.0,
          )
      )
      output = spherical_layer(dist, angle, idx_kj)
      output = output.detach().numpy()
  
      result = np.array(
          [
              [4.2182e00, 5.9654e00, 3.8959e00, 8.6795e00],
              [1.0472e00, -9.1551e-08, 1.7717e00, 1.0400e00],
              [-0.0000e00, 0.0000e00, -0.0000e00, -0.0000e00],
              [-0.0000e00, -0.0000e00, -0.0000e00, -0.0000e00],
          ]
      )
  
      assert np.allclose(output, result, atol=1e-04)
  
imports: import deepchem
  import numpy
  import pytest
  import os
label_desc: Use image node_id 62 for calling a global function with example usage: test_mxmnet_sphericalbasis() without return types