code: def create_batches(self, samps):
      if self.dataset is not None:
          self.it = iter(self.dataset)
      res = filter(lambda o: o is not None, map(self.do_item, samps))
      yield from map(self.do_batch, self.chunkify(res))
  
imports: from __future__ import annotations
  from ..torch_basics import *
  from torch.utils.data.dataloader import _MultiProcessingDataLoaderIter, _SingleProcessDataLoaderIter, _DatasetKind
label_desc: Use image node_id 6 for calling the DataLoader obj's underlying member method code with example usage: obj.create_batches(samps) without return types