code: def test_tracking_metrics_consistency(self):
      rf_models = []
  
      # Train model with increasing max_iterations
      for ntrees in [1, 2, 3]:
          m = self.models["rf"].create(
              self.train,
              "target",
              validation_set=self.test,
              max_iterations=ntrees,
              metric=self.test_metrics,
              random_seed=1,
          )
          rf_models.append(m)
  
      m_last = rf_models[-1]
      for name in self.test_metrics:
          train_column_name = "Training %s" % self._metric_display_name(
              name
          )
          test_column_name = (
              "Validation %s" % self._metric_display_name(name)
          )
          train_evals = [
              float(x) for x in m_last.progress[train_column_name]
          ]
          test_evals = [
              float(x) for x in m_last.progress[test_column_name]
          ]
          # Check the final model's metric at iteration i against the ith model's last metric
          for i in range(len(train_evals) - 1):
              m_current = rf_models[i]
              train_expect = float(
                  m_current.progress[train_column_name][-1]
              )
              test_expect = float(
                  m_current.progress[test_column_name][-1]
              )
              self.assertAlmostEqual(
                  train_evals[i], train_expect, delta=1e-4
              )
              self.assertAlmostEqual(
                  test_evals[i], test_expect, delta=1e-4
              )
  
imports: from __future__ import print_function
  from __future__ import division
  from __future__ import absolute_import
  import unittest
  import turicreate
  from turicreate.toolkits._main import ToolkitError
  import random
label_desc: Use image node_id 9 for calling the TreeRegressionTrackingMetricsTest obj's underlying member method code with example usage: obj.test_tracking_metrics_consistency() without return types