code: def test_no_grad_trunc_normal(self, device="cpu", seed=0):
      torch.manual_seed(seed)
      tensor = torch.rand((8, 16)).to(device)
      a = -2
      b = 2
      _no_grad_trunc_normal(tensor, mean=0, std=1, a=-2, b=2)
      self.assertTrue(tensor.min() >= a)
      self.assertTrue(tensor.max() <= b)
  
imports: import copy
  import unittest
  import torch
  import torch.nn
  from lightly.models import utils
  from lightly.models.utils import _no_grad_trunc_normal, activate_requires_grad, batch_shuffle, batch_unshuffle, deactivate_requires_grad, nearest_neighbors, normalize_weight, update_momentum
label_desc: Use image node_id 6 for calling the TestModelUtils obj's underlying member method code with example usage: obj.test_no_grad_trunc_normal(device, seed) without return types