code: def get_dataloader(val_dataset, data_shape, batch_size, num_workers):
      """Get dataloader."""
      width, height = data_shape, data_shape
      batchify_fn = Tuple(Stack(), Pad(pad_val=-1))
      val_loader = gluon.data.DataLoader(
          val_dataset.transform(
              CenterNetDefaultValTransform(width, height)
          ),
          batch_size,
          False,
          last_batch="keep",
          num_workers=num_workers,
          batchify_fn=batchify_fn,
      )
      return val_loader
  
imports: from __future__ import division
  from __future__ import print_function
  import argparse
  import logging
  import time
  import numpy
  import mxnet
  from tqdm import tqdm
  from mxnet import nd
  from mxnet import gluon
  import gluoncv
  from gluoncv import data
  from gluoncv.data.batchify import Tuple, Stack, Pad
  from gluoncv.data.transforms.presets.center_net import CenterNetDefaultValTransform, get_post_transform
  from gluoncv.utils.metrics.voc_detection import VOC07MApMetric
  from gluoncv.utils.metrics.coco_detection import COCODetectionMetric
label_desc: Use image node_id 3 for calling a global function with example usage: get_dataloader(val_dataset, data_shape, batch_size, num_workers) and returns: val_loader