class_docstr: Split the dataset into `num_parts` parts and sample from the part with
  index `part_index`
  
  Parameters
  ----------
  length: int
    Number of examples in the dataset
  num_parts: int
    Partition the data into multiple parts
  part_index: int
    The index of the part to read from
code: def __len__(self):
      return self.part_len
  
imports: import os
  import argparse
  import logging
  import math
  import time
  import random
  import gluoncv
  from gluoncv.model_zoo import get_model
  from gluoncv.utils import makedirs
  import horovod.mxnet
  import mxnet
  import numpy
  from mxnet import autograd, gluon, lr_scheduler
  from mxnet.io import DataBatch, DataIter
  from mxnet.gluon.data.vision import transforms
  from PIL import Image
  from gluoncv.nn.dropblock import DropBlockScheduler
label_desc: Use image node_id 3 for calling the SplitSampler obj's underlying member method code with example usage: obj.__len__() and returns: self