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.cpu().numpy(), idx.cpu().numpy())
      )
      return int(mask.sum()) == mask.numel()
  
imports: import os.path
  import numpy
  import pytest
  import torch
  import torch_geometric.typing
  from torch_geometric import EdgeIndex
  from torch_geometric.data import Data, HeteroData
  from torch_geometric.loader import NeighborLoader
  from torch_geometric.nn import GraphConv, to_hetero
  from torch_geometric.sampler.base import SubgraphType
  from torch_geometric.testing import MyFeatureStore, MyGraphStore, get_random_edge_index, get_random_tensor_frame, onlyLinux, onlyNeighborSampler, onlyOnline, withCUDA, withPackage
  from torch_geometric.typing import WITH_EDGE_TIME_NEIGHBOR_SAMPLE, WITH_PYG_LIB, WITH_TORCH_SPARSE, WITH_WEIGHTED_NEIGHBOR_SAMPLE, TensorFrame
  from torch_geometric.utils import is_undirected, sort_edge_index, to_torch_csr_tensor, to_undirected
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