code: def np_cross_entropy(probs, labels):
      if labels.shape[-1] == 1:
          # sparse label
          n_classes = probs.shape[-1]
          result_shape = list(labels.shape[:-1]) + [n_classes]
          labels = np.eye(n_classes)[labels.reshape(-1)]
          labels = labels.reshape(result_shape)
  
      return -np.sum(labels * np.log(probs), axis=-1, keepdims=True)
  
label_desc: Use image node_id 2 for calling a global function with example usage: np_cross_entropy(probs, labels) and returns: unknown