code: def _get_iter(path, data_shape, batch_size):
      data_train = mx.io.LibSVMIter(
          data_libsvm=path, data_shape=data_shape, batch_size=batch_size
      )
      data_iter = iter(data_train)
      return data_iter
  
file_path: mxnet/benchmark/python/sparse/dot.py
imports: import ctypes
  import os
  import time
  import argparse
  import subprocess
  import scipy.sparse
  import mxnet
  import numpy
  import numpy.random
  from mxnet.test_utils import rand_ndarray, set_default_device, assert_almost_equal, get_bz2_data
  from mxnet.base import check_call, _LIB
  from util import estimate_density
label_desc: Use image node_id 2 for calling a global function with example usage: _get_iter(path, data_shape, batch_size) and returns: data_iter