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import numpy as np
def cb_multi_fi(items):
from sklearn.metrics import f1_score
preds, golds = zip(*items)
preds = np.array(preds)
golds = np.array(golds)
f11 = f1_score(y_true=golds == 0, y_pred=preds == 0)
f12 = f1_score(y_true=golds == 1, y_pred=preds == 1)
f13 = f1_score(y_true=golds == 2, y_pred=preds == 2)
avg_f1 = np.mean([f11, f12, f13])
return avg_f1