code: def test_ndarray_elementwise():
      np.random.seed(0)
      nrepeat = 10
      maxdim = 4
      all_type = [
          np.float32,
          np.float64,
          np.float16,
          np.uint8,
          np.int32,
      ]
      real_type = [np.float32, np.float64, np.float16]
      for repeat in range(nrepeat):
          for dim in range(1, maxdim):
              check_with_uniform(
                  lambda x, y: x + y, 2, dim, type_list=all_type
              )
              check_with_uniform(
                  lambda x, y: x - y, 2, dim, type_list=all_type
              )
              check_with_uniform(
                  lambda x, y: x * y, 2, dim, type_list=all_type
              )
              check_with_uniform(
                  lambda x, y: x / y, 2, dim, type_list=real_type
              )
              check_with_uniform(
                  lambda x, y: x / y, 2, dim, rmin=1, type_list=all_type
              )
              check_with_uniform(mx.nd.sqrt, 1, dim, np.sqrt, rmin=0)
              check_with_uniform(
                  mx.nd.square, 1, dim, np.square, rmin=0
              )
              check_with_uniform(
                  lambda x: mx.nd.norm(x).asscalar(),
                  1,
                  dim,
                  np.linalg.norm,
              )
  
imports: import os
  import mxnet
  import numpy
  import pickle
label_desc: Use image node_id 6 for calling a global function with example usage: test_ndarray_elementwise() without return types