code: def create_model_with_clip(self):
      user = tf.keras.layers.Input(shape=[1])
      item = tf.keras.layers.Input(shape=[1])
  
      feat = tf.keras.layers.concatenate([user, item], axis=1)
      predictions = tf.keras.layers.Dense(2, activation="softmax")(feat)
  
      model = tf.keras.models.Model(
          inputs=[user, item], outputs=predictions
      )
      optimizer = tf.keras.optimizers.RMSprop(
          learning_rate=0.001,
          rho=0.9,
          momentum=0.0,
          epsilon=1e-07,
          centered=False,
          name="RMSprop",
          clipnorm=1.2,
          clipvalue=0.2,
      )
      model.compile(
          optimizer=optimizer,
          loss="sparse_categorical_crossentropy",
          metrics=["accuracy"],
      )
      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 4 for calling the TestEstimatorForKeras obj's underlying member method code with example usage: obj.create_model_with_clip() and returns: model