class_docstr: The GraphSAINT random walk sampler class (see
  :class:`~torch_geometric.loader.GraphSAINTSampler`).
  
  Args:
      walk_length (int): The length of each random walk.
code: def _sample_nodes(self, batch_size):
      start = torch.randint(0, self.N, (batch_size,), dtype=torch.long)
      node_idx = self.adj.random_walk(start.flatten(), self.walk_length)
      return node_idx.view(-1)
  
imports: import os.path
  from typing import Optional
  import torch
  from tqdm import tqdm
  from torch_geometric.typing import SparseTensor
label_desc: Use image node_id 3 for calling the GraphSAINTRandomWalkSampler obj's underlying member method code with example usage: obj._sample_nodes(batch_size) and returns: node_idx