docstr: Predict probabilities for an RDD of features
          
docstr_tok: ["Predict","probabilities","for","an","RDD","of","features"]
code: def predict(self, mllib_data):
      """Predict probabilities for an RDD of features"""
      if isinstance(mllib_data, pyspark.mllib.linalg.Matrix):
          return to_matrix(
              self._master_network.predict(from_matrix(mllib_data))
          )
      elif isinstance(mllib_data, pyspark.mllib.linalg.Vector):
          return to_vector(
              self._master_network.predict(from_vector(mllib_data))
          )
      else:
          raise ValueError(
              "Provide either an MLLib matrix or vector, got {}".format(
                  mllib_data.__name__
              )
          )
  
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 3 for calling the SparkMLlibModel obj's underlying member method code with example usage: obj.predict(mllib_data) and returns: to_matrix, to_vector