code: def test_equilibrium(iter, alpha):
      batch_size = 10
      feature_channels = 3
      output_channels = 2
      x = torch.randn(batch_size, feature_channels)
      model = EquilibriumAggregation(
          feature_channels,
          output_channels,
          num_layers=[10, 10],
          grad_iter=iter,
      )
  
      assert str(model) == "EquilibriumAggregation()"
      out = model(x)
      assert out.size() == (1, 2)
  
      out = model(x, dim_size=3)
      assert out.size() == (3, 2)
      assert torch.all(out[1:, :] == 0)
  
imports: import pytest
  import torch
  from torch_geometric.nn.aggr import EquilibriumAggregation
label_desc: Use image node_id 1 for calling a global function with example usage: test_equilibrium(iter, alpha) without return types