code: def test_nonnull_sample_weight_raises(
      self, loss_scoring_fn, net_fit, data
  ):
      X, y = data
      with pytest.raises(NotImplementedError):
          loss_scoring_fn(
              net_fit, X, y, sample_weight=np.random.rand(X.shape[0])
          )
  
imports: import pytest
  import numpy
  import torch
label_desc: Use image node_id 13 for calling the TestLossScoring obj's underlying member method code with example usage: obj.test_nonnull_sample_weight_raises(loss_scoring_fn, net_fit, data) without return types