code: def test_gat_conv_empty_edge_index(device):
      x = torch.randn(0, 8, device=device)
      edge_index = torch.empty(2, 0, dtype=torch.long, device=device)
  
      conv = GATConv(8, 32, heads=2).to(device)
      out = conv(x, edge_index)
      assert out.size() == (0, 64)
  
file_path: pytorch_geometric/test/nn/conv/test_gat_conv.py
imports: from typing import Optional, Tuple
  import pytest
  import torch
  from torch import Tensor
  import torch_geometric.typing
  from torch_geometric.nn import GATConv
  from torch_geometric.testing import is_full_test, withCUDA
  from torch_geometric.typing import Adj, Size, SparseTensor
  from torch_geometric.utils import to_torch_csc_tensor
label_desc: Use image node_id 3 for calling a global function with example usage: test_gat_conv_empty_edge_index(device) without return types