code: def test_scored_net_matches_criterion_value(
      self, scored_net_fit, data
  ):
      X, y = data
      y_val_proba = torch.as_tensor(scored_net_fit.predict_proba(X))
      loss_value = scored_net_fit.get_loss(y_val_proba, y)
      score_value = scored_net_fit.score(X, y)
      assert np.allclose(score_value, loss_value.item())
  
imports: import pytest
  import numpy
  import torch
label_desc: Use image node_id 16 for calling the TestLossScoring obj's underlying member method code with example usage: obj.test_scored_net_matches_criterion_value(scored_net_fit, data) without return types