class_docstr: SparkML Estimator implementation of an elephas model. This estimator takes all relevant arguments for model
  compilation and training.
  
  Returns a trained model in form of a SparkML Model, which is also a Transformer.
class_docstr_tok: ["SparkML","Estimator","implementation","of","an","elephas","model",".","This","estimator","takes","all","relevant","arguments","for","model","compilation","and","training",".","Returns","a","trained","model","in","form","of","a","SparkML","Model",",","which","is","also","a","Transformer","."]
code: def get_model(self):
      return model_from_json(
          self.get_keras_model_config(), self.get_custom_objects()
      )
  
imports: import copy
  import json
  import warnings
  from functools import partial
  import h5py
  import numpy
  from pyspark import keyword_only
  from pyspark.ml import Estimator, Model
  from pyspark.ml.param.shared import HasOutputCol, HasFeaturesCol, HasLabelCol
  from pyspark.ml.util import DefaultParamsReadable, DefaultParamsWritable
  from pyspark.sql import DataFrame
  from pyspark.sql.types import DoubleType, StructField, ArrayType
  from tensorflow.keras.models import model_from_json
  from tensorflow.keras.optimizers import get
  from .mllib import from_vector
  from .spark_model import SparkModel
  from .utils.model_utils import LossModelTypeMapper, ModelType, ModelTypeEncoder, as_enum
  from .ml.adapter import df_to_simple_rdd
  from .ml.params import *
label_desc: Use image node_id 5 for calling the ElephasEstimator obj's underlying member method code with example usage: obj.get_model() and returns: model_from_json