code: def eval(self, input_dict):
      if self.eval_metric == "rocauc":
          y_true, y_pred = self._parse_and_check_input(input_dict)
          return self._eval_rocauc(y_true, y_pred)
      elif self.eval_metric == "acc":
          y_true, y_pred = self._parse_and_check_input(input_dict)
          return self._eval_acc(y_true, y_pred)
      else:
          raise ValueError(
              "Undefined eval metric %s " % (self.eval_metric)
          )
  
file_path: ogb/ogb/nodeproppred/evaluate.py
imports: import os
  import numpy
  import pandas
  from sklearn.metrics import roc_auc_score
label_desc: Use image node_id 3 for calling the Evaluator obj's underlying member method code with example usage: obj.eval(input_dict) and returns: self, self