code: def test_gluon_trainer_step():
      def check_trainer_step():
          ctx = mx.cpu(0)
          shape = (10, 1)
          x = mx.gluon.Parameter("x", shape=shape)
          x.initialize(ctx=ctx, init="ones")
          trainer = mx.gluon.Trainer(
              [x],
              "sgd",
              {"learning_rate": 1.0, "multi_precision": False},
              kvstore=kv,
          )
          with mx.autograd.record():
              w = x.data(ctx)
              y = (my_rank + 1) * w
              y.backward()
          trainer.step(1)
          expected = 1 - (1 + nworker) * nworker / 2
          assert_almost_equal(
              x.data(ctx).asnumpy(), np.full(shape, expected)
          )
  
      check_trainer_step()
      print(
          "worker " + str(my_rank) + " passed test_gluon_trainer_step"
      )
  
file_path: mxnet/tests/nightly/dist_sync_kvstore.py
imports: import sys
  import argparse
  import mxnet
  import numpy
  import numpy.random
  from mxnet.test_utils import assert_almost_equal, assert_exception
  from test_kvstore import compute_expected_quantization, compute_1bit, compute_2bit
label_desc: Use image node_id 11 for calling a global function with example usage: test_gluon_trainer_step() without return types