code: def create_model_lr_schedule(self, init_lr, decay_steps, decay_rate):
      x = tf.keras.layers.Input(shape=[8])
  
      predictions = tf.keras.layers.Dense(
          1, use_bias=False, kernel_initializer=tf.ones_initializer()
      )(x)
  
      model = tf.keras.models.Model(inputs=[x], outputs=predictions)
      schedule = tf.keras.optimizers.schedules.ExponentialDecay(
          init_lr, decay_steps, decay_rate
      )
      optimizer = tf.keras.optimizers.SGD(schedule)
      model.compile(
          optimizer=optimizer,
          loss=lambda label, pred: tf.reduce_mean(pred - label),
      )
      return model
  
imports: import shutil
  from unittest import TestCase
  import tensorflow
  from bigdl.orca import OrcaContext
  from bigdl.orca.learn.trigger import SeveralIteration
  from bigdl.orca.learn.tf.estimator import Estimator
  from bigdl.dllib.nncontext import *
  from bigdl.orca.learn.utils import convert_predict_rdd_to_dataframe
  from bigdl.orca.learn.tf.estimator import save_model_dir
label_desc: Use image node_id 3 for calling the TestEstimatorForKeras obj's underlying member method code with example usage: obj.create_model_lr_schedule(init_lr, decay_steps, decay_rate) and returns: model