code: def train_data_store(cls, value):
      value = value.upper()
      import re
  
      invalidInputError(
          value == "DRAM"
          or value == "PMEM"
          or re.match("DISK_\d+", value),
          "train_data_store must be either DRAM or PMEM or DIRECT or DISK_n",
      )
      cls._train_data_store = value
  
imports: import os
  from bigdl.dllib.nncontext import ZooContext
  from bigdl.dllib.utils.log4Error import *
  import pickle
  import hmac
  import hashlib
label_desc: Use image node_id 10 for calling the OrcaContextMeta obj's underlying member method code with example usage: obj.train_data_store(cls, value) without return types