code: def default_pad_batchify_fn(data):
      """Collate data into batch, labels are padded to same shape"""
      if isinstance(data[0], nd.NDArray):
          return nd.stack(*data)
      elif isinstance(data[0], tuple):
          data = zip(*data)
          return [default_pad_batchify_fn(i) for i in data]
      else:
          data = np.asarray(data)
          pad = max(
              [l.shape[0] for l in data]
              + [
                  1,
              ]
          )
          buf = np.full(
              (len(data), pad, data[0].shape[-1]),
              -1,
              dtype=data[0].dtype,
          )
          for i, l in enumerate(data):
              buf[i][: l.shape[0], :] = l
          return nd.array(buf, dtype=data[0].dtype)
  
imports: import io
  import pickle
  import multiprocessing
  from multiprocessing.reduction import ForkingPickler
  import numpy
  from mxnet import nd
  from mxnet import context
  from mxnet.gluon.data.dataloader import DataLoader, _MultiWorkerIter
  from mxnet.gluon.data.dataloader import default_mp_batchify_fn, default_batchify_fn
label_desc: Use image node_id 1 for calling a global function with example usage: default_pad_batchify_fn(data) and returns: nd, unknown, nd