code: def test_get_weight_decay_parameters() -> None:
      linear = nn.Linear(10, 10)
      batch_norm1d = nn.BatchNorm1d(10)
      conv = nn.Conv2d(3, 3, 3)
      batch_norm2d = nn.BatchNorm2d(3)
      sequential = nn.Sequential(
          linear, batch_norm1d, conv, batch_norm2d
      )
      (
          params,
          params_no_weight_decay,
      ) = utils.get_weight_decay_parameters(modules=[sequential])
      assert len(params) == 2
      assert len(params_no_weight_decay) == 6
      assert params[0] is linear.weight
      assert params[1] is conv.weight
      assert params_no_weight_decay[0] is linear.bias
      assert params_no_weight_decay[1] is batch_norm1d.weight
      assert params_no_weight_decay[2] is batch_norm1d.bias
      assert params_no_weight_decay[3] is conv.bias
      assert params_no_weight_decay[4] is batch_norm2d.weight
      assert params_no_weight_decay[5] is batch_norm2d.bias
  
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 2 for calling a global function with example usage: test_get_weight_decay_parameters() without return types