code: def test_set_gather():
      """Test invoking the Torch Equivalent of SetGather."""
      # total_n_atoms = 4
      # n_atom_feat = 4
      # atom_feat = np.random.rand(total_n_atoms, n_atom_feat)
      atom_feat = np.load(
          os.path.join(
              os.path.dirname(__file__),
              "assets",
              "atom_feat_SetGather.npy",
          )
      )
      atom_split = np.array([0, 0, 1, 1], dtype=np.int32)
      torch_layer = torch_layers.SetGather(2, 2, 4)
      weights = np.load(
          os.path.join(
              os.path.dirname(__file__),
              "assets",
              "weights_SetGather_tf.npy",
          )
      )
      torch_layer.U = torch.nn.Parameter(torch.from_numpy(weights))
      torch_result = torch_layer([atom_feat, atom_split])
      tf_result = np.load(
          os.path.join(
              os.path.dirname(__file__),
              "assets",
              "result_SetGather_tf.npy",
          )
      )
      assert np.allclose(
          np.array(tf_result), np.array(torch_result), atol=1e-4
      )
  
imports: import deepchem
  import numpy
  import pytest
  import os
label_desc: Use image node_id 48 for calling a global function with example usage: test_set_gather() without return types