code: def DISABLED_test_saving_lambda(self):
      mean = np.random.random((4, 2, 3))
      std = np.abs(np.random.random((4, 2, 3))) + 1e-5
      inputs = tf_keras.layers.Input(shape=(4, 2, 3))
      output = tf_keras.layers.Lambda(
          lambda image, mu, std: (image - mu) / std,
          arguments={"mu": mean, "std": std},
          output_shape=inputs.shape,
      )(inputs)
      tf_keras_model = tf_keras.Model(inputs, output)
      tf_keras_model.compile(
          loss="mse", optimizer="sgd", metrics=["acc"]
      )
  
      temp_filepath = os.path.join(
          self.get_temp_dir(), "lambda_model.h5"
      )
      tf_keras_model.save(temp_filepath)
      loaded = legacy_h5_format.load_model_from_hdf5(temp_filepath)
  
      self.assertAllClose(mean, loaded.layers[1].arguments["mu"])
      self.assertAllClose(std, loaded.layers[1].arguments["std"])
  
imports: import os
  import numpy
  import pytest
  import keras
  from keras import layers
  from keras import models
  from keras import ops
  from keras import testing
  from keras.legacy.saving import legacy_h5_format
  from keras.saving import object_registration
  from keras.saving import serialization_lib
label_desc: Use image node_id 5 for calling the LegacyH5BackwardsCompatTest obj's underlying member method code with example usage: obj.DISABLED_test_saving_lambda() without return types