code: def calc_all_ic(
      pred_dict_all, label, date_col="datetime", dropna=False, n_jobs=-1
  ):
      """calc_all_ic.
  
      Parameters
      ----------
      pred_dict_all :
          A dict like {<method_name>:  <prediction>}
      label:
          A pd.Series of label values
  
      Returns
      -------
      {'Q2+IND_z': {'ic': <ic series like>
                            2016-01-04   -0.057407
                            ...
                            2020-05-28    0.183470
                            2020-05-29    0.171393
                    'ric': <rank ic series like>
                            2016-01-04   -0.040888
                            ...
                            2020-05-28    0.236665
                            2020-05-29    0.183886
                    }
      ...}
      """
      pred_all_ics = {}
      for k, pred in pred_dict_all.items():
          pred_all_ics[k] = DelayedDict(
              ["ic", "ric"],
              delayed(calc_ic)(
                  pred, label, date_col=date_col, dropna=dropna
              ),
          )
      pred_all_ics = complex_parallel(
          Parallel(n_jobs=n_jobs, verbose=10), pred_all_ics
      )
      return pred_all_ics
  
file_path: qlib/qlib/contrib/eva/alpha.py
imports: import pandas
  from typing import Tuple
  from qlib import get_module_logger
  from qlib.utils.paral import complex_parallel, DelayedDict
  from joblib import Parallel, delayed
label_desc: Use image node_id 6 for calling a global function with example usage: calc_all_ic(pred_dict_all, label, date_col, dropna, n_jobs) and returns: pred_all_ics