code: def test_mat_encoder_layer():
      """Test invoking MATEncoderLayer."""
      input_smile = "CC"
      feat = dc.feat.MATFeaturizer()
      input_smile = "CC"
      out = feat.featurize(input_smile)
      node = torch.tensor(out[0].node_features).float().unsqueeze(0)
      adj = torch.tensor(out[0].adjacency_matrix).float().unsqueeze(0)
      dist = torch.tensor(out[0].distance_matrix).float().unsqueeze(0)
      mask = torch.sum(torch.abs(node), dim=-1) != 0
      layer = torch_layers.MATEncoderLayer()
      op = torch_layers.MATEmbedding()(node)
      output = layer(op, mask, adj, dist)
      assert output.shape == (1, 3, 1024)
  
imports: import deepchem
  import numpy
  import pytest
  import os
label_desc: Use image node_id 36 for calling a global function with example usage: test_mat_encoder_layer() without return types