code: def gini_macro_f1(truth, predictions):
      return f1_score(
          truth, predictions.argmax(axis=1), average="macro"
      )
  
imports: import numpy
  from sklearn import model_selection
  from sklearn.metrics import confusion_matrix, mean_squared_error
  from sklearn import metrics
  from sklearn import model_selection, metrics
  from sklearn.metrics import accuracy_score, f1_score, roc_auc_score, log_loss
  from sklearn.metrics import mean_squared_error, median_absolute_error, mean_absolute_error
  from sklearn.metrics import classification_report, confusion_matrix, mean_squared_log_error
  from sklearn.metrics import precision_recall_curve
  from sklearn.model_selection import cross_val_score, StratifiedKFold, KFold
  from sklearn.metrics import make_scorer
  from sklearn.metrics import accuracy_score
  from sklearn.metrics import average_precision_score
  from sklearn.metrics import f1_score
  from sklearn.metrics import log_loss
  from sklearn.metrics import precision_score
  from sklearn.metrics import recall_score
  from sklearn.metrics import roc_auc_score
  from sklearn.metrics import fbeta_score
  from sklearn.metrics import confusion_matrix
label_desc: Use image node_id 22 for calling a global function with example usage: gini_macro_f1(truth, predictions) and returns: f1_score