code: def sk_log_loss(
      y_true: Union[List[List[float]], List[List[int]], np.ndarray],
      y_predicted: Union[
          List[List[float]], List[List[int]], np.ndarray
      ],
  ) -> float:
      """
      Calculates log loss.
  
      Args:
          y_true: list or array of true values
          y_predicted: list or array of predicted values
  
      Returns:
          Log loss
  
      Alias:
          log_loss
      """
      return log_loss(y_true, y_predicted)
  
imports: from typing import List, Union
  import numpy
  from sklearn.metrics import log_loss
  from deeppavlov.core.common.metrics_registry import register_metric
label_desc: Use image node_id 1 for calling a global function with example usage: sk_log_loss(y_true, y_predicted) and returns: log_loss