docstr: compute RMSE score averaged across tasks
docstr_tok: ["compute","RMSE","score","averaged","across","tasks"]
code: def _eval_rmse(self, y_true, y_pred):
      """
      compute RMSE score averaged across tasks
      """
      rmse_list = []
  
      for i in range(y_true.shape[1]):
          # ignore nan values
          is_labeled = y_true[:, i] == y_true[:, i]
          rmse_list.append(
              np.sqrt(
                  (
                      (y_true[is_labeled, i] - y_pred[is_labeled, i])
                      ** 2
                  ).mean()
              )
          )
  
      return {"rmse": sum(rmse_list) / len(rmse_list)}
  
file_path: ogb/ogb/graphproppred/evaluate.py
imports: import os
  import numpy
  import pandas
  from sklearn.metrics import roc_auc_score, average_precision_score
label_desc: Use image node_id 8 for calling the Evaluator obj's underlying member method code with example usage: obj._eval_rmse(y_true, y_pred) and returns: dict