docstr: Evaluate (run-averaged) out-of-fold predictions for the repetition
docstr_tok: ["Evaluate","(","run-averaged",")","out-of-fold","predictions","for","the","repetition"]
code: def on_rep_end(self):
      """Evaluate (run-averaged) out-of-fold predictions for the repetition"""
      if G.Env.save_transformed_metrics:
          self.evaluate(
              "oof",
              self.data_oof.target.T.rep,
              self.data_oof.prediction.T.rep,
          )
      else:  # See module "Notes"
          self.evaluate(
              "oof",
              self.data_oof.target.d,
              self.data_oof.prediction.rep,
          )
      super().on_rep_end()
  
file_path: hyperparameter_hunter/hyperparameter_hunter/callbacks/evaluators.py
imports: from hyperparameter_hunter.callbacks.bases import BaseEvaluatorCallback
  from hyperparameter_hunter.data.data_core import BaseDataset
  from hyperparameter_hunter.settings import G
label_desc: Use image node_id 3 for calling the EvaluatorOOF obj's underlying member method code with example usage: obj.on_rep_end() without return types