code: def test_multigraph_convolution_layer_shape():
      from deepchem.models.torch_models.layers import (
          MolGANMultiConvolutionLayer,
      )
  
      vertices = 9
      nodes = 5
      edges = 5
      first_convolution_unit = 128
      second_convolution_unit = 64
      units = [first_convolution_unit, second_convolution_unit]
  
      layer = MolGANMultiConvolutionLayer(units=units, edges=edges)
      adjacency_tensor = torch.randn((1, vertices, vertices, edges))
      node_tensor = torch.randn((1, vertices, nodes))
      model = layer([adjacency_tensor, node_tensor])
  
      assert model.shape == (1, vertices, second_convolution_unit)
      assert layer.units == units
      assert layer.activation == torch.tanh
      assert layer.edges == 5
      assert layer.dropout_rate == 0.0
  
file_path: deepchem/deepchem/models/torch_models/tests/test_molgan_layers.py
imports: import pytest
label_desc: Use image node_id 5 for calling a global function with example usage: test_multigraph_convolution_layer_shape() without return types