code: def params_l3():
      """
      seq = x y z, t0, t1 & n0, n1, n2
      """
      terms = [[2, 1], [1, 2], [1, 1]]
      # term4 = [[1, 1], [2, 1], [1, 2]]
      roots = [1, 1, 1]
      rule1 = [
          [1, 1, 1, 1, 1],
          [1, 1, 1, 1, 1],
          [1, 1, 1, 1, 1],
          [1, 1, 1, 1, 5],
          [1, 1, 1, 2, 1],
      ]
      rule2 = [
          [1, 1, 1, 1, 1],
          [1, 1, 1, 1, 1],
          [1, 1, 1, 1, 1],
          [1, 1, 1, 1, 6],
          [1, 1, 1, 2, 1],
      ]
      rule3 = [
          [1, 1, 1, 1, 1],
          [1, 1, 1, 4, 5],
          [1, 1, 1, 8, 9],
          [1, 1, 1, 1, 4],
          [1, 1, 1, 2, 1],
      ]
      rules = [rule1, rule2, rule3]
  
      terms = (
          torch.tensor(terms, dtype=torch.float64, requires_grad=True)
          .unsqueeze(0)
          .float()
      )
      roots = (
          torch.tensor(roots, dtype=torch.float64, requires_grad=True)
          .unsqueeze(0)
          .float()
      )
      rules = (
          torch.tensor(rules, dtype=torch.float64, requires_grad=True)
          .unsqueeze(0)
          .float()
      )
  
      length = torch.tensor([3]).long()
  
      # print('term:\n', terms, terms.shape)
      # print('root:\n', roots, roots.shape)
      # print('rule:\n', rules, rules.shape)
      return ((terms, rules, roots), length)
  
imports: import torch
  from torch_struct import SentCFG
label_desc: Use image node_id 1 for calling a global function with example usage: params_l3() and returns: terms,  rules,  roots,  length