code: def test_lambda_layer_keras_layer(self):
      input_shape = [100, 5]
      in_1 = tl.layers.Input(input_shape, name="input")
      denselayer = tf.keras.layers.Dense(10, activation=tf.nn.relu)
      # in order to compile keras model and get trainable_variables of the keras model
      _ = denselayer(np.random.random(input_shape).astype(np.float32))
      dlambdalayer = tl.layers.Lambda(
          denselayer, denselayer.trainable_variables
      )(in_1)
      M1 = tl.models.Model(inputs=in_1, outputs=dlambdalayer)
  
      M1.save("M1_keras.hdf5")
      M3 = Model.load("M1_keras.hdf5")
  
      M1.eval()
      M3.eval()
      npInput = np.zeros(input_shape) + 3
      output1 = M1(npInput).numpy()
      output3 = M3(npInput).numpy()
  
      M1_config = RemoveDateInConfig(M1.config)
      M3_config = RemoveDateInConfig(M3.config)
  
      self.assertEqual((output1 == output3).all(), True)
      self.assertEqual(M1_config, M3_config)
  
      ori_weights = M3.all_weights
      ori_val = ori_weights[1].numpy()
      modify_val = np.zeros_like(ori_val) + 10
      M3.all_weights[1].assign(modify_val)
      M3 = Model.load("M1_keras.hdf5")
  
      self.assertLess(
          np.max(np.abs(ori_val - M3.all_weights[1].numpy())), 1e-7
      )
  
imports: import os
  import unittest
  import numpy
  import tensorflow
  import tensorlayer
  from tensorlayer.layers import *
  from tensorlayer.models import *
  from tests.utils import CustomTestCase
label_desc: Use image node_id 5 for calling the Lambda_layer_test obj's underlying member method code with example usage: obj.test_lambda_layer_keras_layer() without return types