code: def test_log_loss(gt, probs):
      gt = np.array(gt, dtype=np.int64)
      probs = np.array(probs, dtype=np.float32)
      ag_loss = log_loss(gt, probs)
      expected = np.log(probs[np.arange(probs.shape[0]), gt]).mean()
      np.testing.assert_allclose(ag_loss, expected)
  
imports: import numpy
  import pytest
  import sklearn
  from autogluon.core.metrics import confusion_matrix, log_loss, quadratic_kappa, roc_auc
  from autogluon.core.metrics.softclass_metrics import soft_log_loss
label_desc: Use image node_id 11 for calling a global function with example usage: test_log_loss(gt, probs) without return types