code: def test_ndarray_saveload():
      np.random.seed(0)
      maxdim = 5
      nrepeat = 10
      fname = "tmp_list.bin"
      for repeat in range(nrepeat):
          data = []
          for i in range(10):
              data.append(random_ndarray(np.random.randint(1, 5)))
          mx.nd.save(fname, data)
          data2 = mx.nd.load(fname)
          assert len(data) == len(data2)
          for x, y in zip(data, data2):
              assert np.sum(x.asnumpy() != y.asnumpy()) == 0
          dmap = {f"ndarray xx {i}": x for i, x in enumerate(data)}
          mx.nd.save(fname, dmap)
          dmap2 = mx.nd.load(fname)
          assert len(dmap2) == len(dmap)
          for k, x in dmap.items():
              y = dmap2[k]
              assert np.sum(x.asnumpy() != y.asnumpy()) == 0
      os.remove(fname)
  
imports: import os
  import mxnet
  import numpy
  import pickle
label_desc: Use image node_id 14 for calling a global function with example usage: test_ndarray_saveload() without return types