code: def test_trainer_save_load():
      previous_update_on_kvstore = os.getenv(
          "MXNET_UPDATE_ON_KVSTORE", "1"
      )
      os.putenv("MXNET_UPDATE_ON_KVSTORE", "1")
  
      x = gluon.Parameter("x", shape=(10,), lr_mult=1.0)
      x.initialize(ctx=[mx.cpu(0), mx.cpu(1)], init="zeros")
      trainer = gluon.Trainer([x], "sgd", {"learning_rate": 0.1})
      with mx.autograd.record():
          for w in x.list_data():
              y = w + 1
              y.backward()
      trainer.step(1)
      assert trainer._kvstore._updater.optimizer._get_lr(0) == 0.1
      trainer.save_states("test_trainer_save_load.states")
      trainer.load_states("test_trainer_save_load.states")
      x.lr_mult = 2.0
      # check if parameter dict is correctly associated with optimizer after load_state
      assert trainer._kvstore._updater.optimizer._get_lr(0) == 0.2
      os.putenv("MXNET_UPDATE_ON_KVSTORE", previous_update_on_kvstore)
  
imports: import mxnet
  import unittest
  import os
  import numpy
  from mxnet import gluon
  from mxnet.gluon import nn
  from mxnet.test_utils import assert_almost_equal
  from common import assertRaises, xfail_when_nonstandard_decimal_separator
  from copy import deepcopy
  import pytest
label_desc: Use image node_id 6 for calling a global function with example usage: test_trainer_save_load() without return types