code: def clone_model(model):
      """Clone any tf.keras.Model into a tfe.keras.Sequenial model.
  
      Arguments:
        model: tf.keras.Sequential or tf.keras.Model instance.
  
      Returns:
        A TFE Keras model instance reproducing the behavior of the
        original model using newly instantiated weights.
      """
  
      config = model.get_config()
      weights = model.get_weights()
  
      tfe_model = model_from_config(config)
      tfe_model.set_weights(weights)
  
      return tfe_model
  
file_path: tf-encrypted/tf_encrypted/keras/models/sequential.py
imports: import tensorflow
  import tf_encrypted
  from tf_encrypted.keras import optimizers
  from tf_encrypted.keras.engine import Layer
  from tf_encrypted.keras.engine.input_layer import Input
  from tf_encrypted.keras.engine.input_layer import InputLayer
  from .base_model import BaseModel
label_desc: Use image node_id 2 for calling a global function with example usage: clone_model(model) and returns: tfe_model