code: def test_group_kvstore(kv_type, stype):
      print(kv_type)
      kv = mx.kv.create(kv_type)
      kv.set_optimizer(mx.optimizer.create("test", learning_rate=-lr))
      kv.init(keys, [mx.nd.zeros(s) for s in shapes])
      res = [np.zeros(s) for s in shapes]
      out = [
          [mx.nd.zeros(s, mx.gpu(g)) for g in range(nworker)]
          for s in shapes
      ]
      for i in range(nrepeat):
          kv.push(
              keys,
              [
                  [
                      mx.nd.array(data[i][j][g], mx.gpu(g)).tostype(
                          stype
                      )
                      for g in range(nworker)
                  ]
                  for j in range(len(keys))
              ],
          )
  
          kv.pull(keys, out=out)
          res = [
              a + b * lr for a, b in zip(res, [sum(d) for d in data[i]])
          ]
          for a, b in zip(res, out):
              err = [np.sum(np.abs(o.asnumpy() - a)) for o in b]
              err = sum(err) / np.sum(np.abs(a))
              assert err < 1e-6, (err, a.shape)
  
file_path: mxnet/tests/nightly/test_kvstore.py
imports: import sys
  import mxnet
  import numpy
  import numpy.random
  import copy
  from mxnet.test_utils import assert_almost_equal
label_desc: Use image node_id 7 for calling a global function with example usage: test_group_kvstore(kv_type, stype) without return types