code: def test_loss(params, loss_desired):
      """Test that the actual loss is equal to the expected loss."""
      loss_actual = _loss(
          X_bin,
          y_bin,
          n_classes,
          shapelets=shapelets,
          lengths=lengths,
          alpha=-100,
          intercept_scaling=1,
          **params,
      )
      np.testing.assert_allclose(
          loss_actual, loss_desired, atol=1e-5, rtol=0.0
      )
  
imports: import numpy
  import pytest
  import re
  from sklearn.exceptions import ConvergenceWarning
  from pyts.classification.learning_shapelets import CrossEntropyLearningShapelets
  from pyts.classification import LearningShapelets
  from pyts.classification.learning_shapelets import _expit, _xlogy, _softmin, _softmin_grad, _softmax, _derive_shapelet_distances, _derive_all_squared_distances, _reshape_list_shapelets, _reshape_array_shapelets, _loss, _grad_weights, _grad_shapelets
label_desc: Use image node_id 12 for calling a global function with example usage: test_loss(params, loss_desired) without return types