code: def logloss(y, p):
      """Bounded log loss error.
      Args:
          y (numpy.array): target
          p (numpy.array): prediction
      Returns:
          bounded log loss error
      """
  
      p[p < EPS] = EPS
      p[p > 1 - EPS] = 1 - EPS
      return log_loss(y, p)
  
imports: import logging
  from sklearn.metrics import log_loss, roc_auc_score
  from .const import EPS
  from .regression import regression_metrics
label_desc: Use image node_id 1 for calling a global function with example usage: logloss(y, p) and returns: log_loss