code: def test_metapath2vec_empty_edges():
      num_nodes_dict = {"a": 3, "b": 4}
      edge_index_dict = {
          ("a", "to", "b"): torch.empty((2, 0), dtype=torch.long),
          ("b", "to", "a"): torch.empty((2, 0), dtype=torch.long),
      }
      metapath = [("a", "to", "b"), ("b", "to", "a")]
  
      model = MetaPath2Vec(
          edge_index_dict,
          embedding_dim=16,
          metapath=metapath,
          walk_length=10,
          context_size=7,
          walks_per_node=5,
          num_negative_samples=5,
          num_nodes_dict=num_nodes_dict,
      )
      loader = model.loader(batch_size=16, shuffle=True)
      next(iter(loader))
  
imports: import torch
  from torch_geometric.nn import MetaPath2Vec
  from torch_geometric.testing import withCUDA
label_desc: Use image node_id 2 for calling a global function with example usage: test_metapath2vec_empty_edges() without return types