code: def randomk(x, k, state):
      y = x.flatten()
      low = np.uint64(0)
      high = np.uint64(len(y))
      indices = np.array(
          [randint(low, high, state) for _ in range(k)], dtype=np.uint64
      )
      vals = y[indices]
      y.fill(0)
      for idx, val in zip(indices, vals):
          y[idx] = val
      return y.reshape(x.shape)
  
file_path: byteps/tests/test_randomk.py
imports: import itertools
  import unittest
  import byteps.mxnet
  import mxnet
  import mxnet.ndarray
  import numpy
  from gluoncv.model_zoo import get_model
  from mxnet import autograd, gluon
  from numba import jit
  from parameterized import parameterized
  from tqdm import tqdm
  from meta_test import MetaTest
  from utils import fake_data, randint
label_desc: Use image node_id 1 for calling a global function with example usage: randomk(x, k, state) and returns: y