code: def get_config(self):
      base_config = {
          "parameter_server_mode": self.parameter_server_mode,
          "mode": self.mode,
          "frequency": self.frequency,
          "num_workers": self.num_workers,
          "batch_size": self.batch_size,
      }
      config = base_config.copy()
      config.update(self.kwargs)
      return config
  
imports: import json
  from functools import partial
  from itertools import tee
  from typing import Union
  import h5py
  import numpy
  import pyspark
  from pyspark import RDD
  from tensorflow.keras.models import load_model
  from tensorflow.keras.models import model_from_json
  from tensorflow.keras.optimizers import get
  from tensorflow.keras.optimizers import serialize, deserialize
  from .mllib import to_matrix, from_matrix, to_vector, from_vector
  from .parameter.factory import ClientServerFactory
  from .utils import lp_to_simple_rdd, to_simple_rdd
  from .utils import model_to_dict
  from .utils import subtract_params, divide_by
  from .worker import AsynchronousSparkWorker, SparkWorker
label_desc: Use image node_id 2 for calling the SparkModel obj's underlying member method code with example usage: obj.get_config() and returns: config