code: def test_track_multiple_layers(self):
      temp_filepath = os.path.join(
          self.get_temp_dir(), "exported_model"
      )
      layer_1 = layers.Dense(2)
      ref_input_1 = tf.random.normal((3, 4))
      ref_output_1 = layer_1(ref_input_1)
      layer_2 = layers.Dense(3)
      ref_input_2 = tf.random.normal((3, 5))
      ref_output_2 = layer_2(ref_input_2)
  
      export_archive = export_lib.ExportArchive()
      export_archive.add_endpoint(
          "call_1",
          layer_1.call,
          input_signature=[
              tf.TensorSpec(
                  shape=(None, 4),
                  dtype=tf.float32,
              ),
          ],
      )
      export_archive.add_endpoint(
          "call_2",
          layer_2.call,
          input_signature=[
              tf.TensorSpec(
                  shape=(None, 5),
                  dtype=tf.float32,
              ),
          ],
      )
      export_archive.write_out(temp_filepath)
      revived_layer = tf.saved_model.load(temp_filepath)
      self.assertAllClose(
          ref_output_1,
          revived_layer.call_1(ref_input_1),
          atol=1e-6,
      )
      self.assertAllClose(
          ref_output_2,
          revived_layer.call_2(ref_input_2),
          atol=1e-6,
      )
  
imports: import os
  import numpy
  import pytest
  import tensorflow
  from keras import backend
  from keras import layers
  from keras import models
  from keras import testing
  from keras import utils
  from keras.export import export_lib
  from keras.saving import saving_lib
label_desc: Use image node_id 6 for calling the ExportArchiveTest obj's underlying member method code with example usage: obj.test_track_multiple_layers() without return types