code: def get_batch():
      s = torch.from_numpy(
          np.random.choice(
              np.arange(
                  args.data_size - args.batch_time, dtype=np.int64
              ),
              args.batch_size,
              replace=False,
          )
      )
      batch_y0 = true_y[s]  # (M, D)
      batch_t = t[: args.batch_time]  # (T)
      batch_y = torch.stack(
          [true_y[s + i] for i in range(args.batch_time)], dim=0
      )  # (T, M, D)
      return batch_y0.to(device), batch_t.to(device), batch_y.to(device)
  
imports: import os
  import argparse
  import time
  import numpy
  import torch
  import torch.nn
  import torch.optim
label_desc: Use image node_id 1 for calling a global function with example usage: get_batch() and returns: batch_y0,  batch_t,  batch_y