code: def test_static_gin_conv():
      x = torch.randn(3, 4, 16)
      edge_index = torch.tensor(
          [[0, 0, 0, 1, 2, 3], [1, 2, 3, 0, 0, 0]]
      )
  
      nn = Seq(Lin(16, 32), ReLU(), Lin(32, 32))
      conv = GINConv(nn, train_eps=True)
      out = conv(x, edge_index)
      assert out.size() == (3, 4, 32)
  
file_path: pytorch_geometric/test/nn/conv/test_gin_conv.py
imports: import torch
  from torch.nn import Linear
  from torch.nn import ReLU
  from torch.nn import Sequential
  import torch_geometric.typing
  from torch_geometric.nn import GINConv, GINEConv
  from torch_geometric.testing import is_full_test
  from torch_geometric.typing import SparseTensor
  from torch_geometric.utils import to_torch_csc_tensor
label_desc: Use image node_id 4 for calling a global function with example usage: test_static_gin_conv() without return types