code: def is_subset(subedge_index, edge_index, src_idx, dst_idx):
      num_nodes = int(edge_index.max()) + 1
      idx = num_nodes * edge_index[0] + edge_index[1]
      subidx = (
          num_nodes * src_idx[subedge_index[0]]
          + dst_idx[subedge_index[1]]
      )
      mask = torch.from_numpy(np.isin(subidx, idx))
      return int(mask.sum()) == mask.numel()
  
file_path: pytorch_geometric/test/loader/test_hgt_loader.py
imports: import numpy
  import torch
  from torch_geometric.data import HeteroData
  from torch_geometric.loader import HGTLoader
  from torch_geometric.nn import GraphConv, to_hetero
  from torch_geometric.testing import get_random_edge_index, onlyOnline, withPackage
  from torch_geometric.typing import SparseTensor
  from torch_geometric.utils import k_hop_subgraph
label_desc: Use image node_id 1 for calling a global function with example usage: is_subset(subedge_index, edge_index, src_idx, dst_idx) and returns: unknown