docstr: Get prediction probabilities for a numpy array of features
          
docstr_tok: ["Get","prediction","probabilities","for","a","numpy","array","of","features"]
code: def predict(self, data: Union[RDD, np.array]):
      """Get prediction probabilities for a numpy array of features"""
      if isinstance(data, (np.ndarray,)):
          from pyspark.sql import SparkSession
  
          sc = SparkSession.builder.getOrCreate().sparkContext
          data = sc.parallelize(data)
      return self._predict(data)
  
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 9 for calling the SparkModel obj's underlying member method code with example usage: obj.predict(data) and returns: self