code: def report(results, n_top=3):
      for i in range(1, n_top + 1):
          candidates = np.flatnonzero(results["rank_test_score"] == i)
          for candidate in candidates:
              print("Model with rank: {0}".format(i))
              print(
                  "Mean validation score: {0:.3f} (std: {1:.3f})".format(
                      results["mean_test_score"][candidate],
                      results["std_test_score"][candidate],
                  )
              )
              print(
                  "Parameters: {0}".format(results["params"][candidate])
              )
              print("")
  
imports: from time import time
  import numpy
  import scipy.stats
  from sklearn.datasets import load_digits
  from sklearn.linear_model import SGDClassifier
  from sklearn.model_selection import GridSearchCV, RandomizedSearchCV
label_desc: Use image node_id 1 for calling a global function with example usage: report(results, n_top) without return types