code: def test_MultiPrecision(self):
      multi_precision_metric = MultiPrecision()
      predict = np.random.random_sample((1000, 3))
      label = np.random.randint(0, 3, 1000)
      result = multi_precision_metric(predict, label)
      print(result.to_dict())
      self.assertEqual(result.metric_name, "multi_precision")
      self.assertAlmostEqual(
          result.result,
          precision_score(
              label, predict.argmax(axis=-1), average="micro"
          ),
          places=7,
      )
  
file_path: FATE/python/fate/ml/evaluation/test/test_classi_metrci.py
imports: import unittest
  import numpy
  from sklearn.metrics import roc_auc_score, accuracy_score, recall_score, precision_score, f1_score
  from sklearn.preprocessing import LabelBinarizer
  from fate.ml.evaluation.classification import *
label_desc: Use image node_id 4 for calling the TestMetric obj's underlying member method code with example usage: obj.test_MultiPrecision() without return types