code: def test_log_loss_single_binary_class():
      gt = np.array([1, 1, 1])
      probs = np.array([0.1, 0.2, 0.3])
      np.testing.assert_allclose(
          log_loss(gt, probs), np.log(probs).mean()
      )
      np.testing.assert_allclose(
          log_loss(1 - gt, probs), np.log(1 - probs).mean()
      )
  
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 13 for calling a global function with example usage: test_log_loss_single_binary_class() without return types