code: def test_truncnormal(min, max, vecs, upscale, shape):
      torch.manual_seed(0)
      d = TruncatedNormal(
          *vecs,
          upscale=upscale,
          min=min,
          max=max,
      )
      for _ in range(100):
          a = d.rsample(shape)
          assert a.shape[: len(shape)] == shape
          assert (a >= d.min).all()
          assert (a <= d.max).all()
          lp = d.log_prob(a)
          assert torch.isfinite(lp).all()
  
label_desc: Use image node_id 1 for calling a global function with example usage: test_truncnormal(min, max, vecs, upscale, shape) without return types