code: def _test():
      """
      ### Test the model with fake data
      """
      chunk_len = 4
      d_model = 8
      d_ff = 32
      n_heads = 2
      d_k = 4
  
      device = torch.device("cuda:0")
  
      m = RetroModel(
          5,
          d_model,
          6,
          {2, 5},
          chunk_len,
          n_heads,
          d_k,
          d_ff,
          encoder=NearestNeighborEncoder(
              chunk_len, 2, {1}, d_model, n_heads, d_k, d_ff
          ),
      )
  
      m.to(device)
      x = [1, 2, 4, 4, 0, 1, 2, 3, 4, 3]
      ret = [
          [[0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1]],
          [[0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1]],
      ]
      res = m(
          torch.tensor([x] * 10).to(device),
          torch.tensor([ret] * 10).to(device),
      )
  
      inspect(res)
  
imports: import math
  from typing import Set
  import torch
  from torch import nn
  from labml.logger import inspect
label_desc: Use image node_id 1 for calling a global function with example usage: _test() without return types