code: def test_aggregation_layer_shape():
      from deepchem.models.torch_models.layers import (
          MolGANAggregationLayer,
      )
  
      vertices = 9
      units = 128
  
      layer = MolGANAggregationLayer(units=units)
      hidden_tensor = torch.randn((1, vertices, units))
      output = layer(hidden_tensor)
      output_tf = (
          1,
          128,
      )  # None has been converted to 1 as batch size is taken as 1 in torch
  
      # Testing Shapes with TF Model Output
      assert output.shape == output_tf
  
      # Testing Shapes
      assert output.shape == (1, units)
      assert layer.units == units
      assert layer.activation == torch.tanh
      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 3 for calling a global function with example usage: test_aggregation_layer_shape() without return types