code: def test_rw_large(device):
      row = tensor([0, 1, 1, 1, 2, 2, 3, 3, 4, 4], torch.long, device)
      col = tensor([1, 0, 2, 3, 1, 4, 1, 4, 2, 3], torch.long, device)
      start = tensor([0, 1, 2, 3, 4], torch.long, device)
      walk_length = 10
  
      out = random_walk(row, col, start, walk_length)
      assert out[:, 0].tolist() == start.tolist()
  
      for n in range(start.size(0)):
          cur = start[n].item()
          for i in range(1, walk_length):
              assert out[n, i].item() in col[row == cur].tolist()
              cur = out[n, i].item()
  
imports: import pytest
  import torch
  from torch_cluster import random_walk
  from torch_cluster.testing import devices, tensor
label_desc: Use image node_id 1 for calling a global function with example usage: test_rw_large(device) without return types