code: def plasma_data_creator(
      meta_data, object_store_address, workers_per_node=1, batch_size=1
  ):
      def create_plasma_dataloader(config):
          dataset = PlasmaNDArrayDataset(
              meta_data,
              object_store_address,
              workers_per_node,
              batch_size,
          )
          # TODO: support more options
          loader = DataLoader(
              dataset,
              batch_size=None,
              shuffle=False,
              collate_fn=None,
          )
          return loader
  
      return create_plasma_dataloader
  
imports: import os
  import types
  import subprocess
  import cloudpickle
  from pyspark.sql import DataFrame
  from torch.utils.data import Dataset, DataLoader
  from zoo.util.utils import get_node_ip
  from zoo.orca.learn.mpi.mpi_runner import MPIRunner
  from zoo.orca.learn.mpi.utils import *
label_desc: Use image node_id 3 for calling a global function with example usage: plasma_data_creator(meta_data, object_store_address, workers_per_node, batch_size) and returns: create_plasma_dataloader, loader