code: def test_depthwise_conv2d_set_weights(self):
      input_shape = (1, 10, 10, 3)
      input_data = np.random.normal(size=input_shape)
  
      model = tf.keras.models.Sequential()
  
      model.add(
          tf.keras.layers.DepthwiseConv2D(
              kernel_size=(2, 2),
              batch_input_shape=input_shape,
          )
      )
  
      expected = model.predict(input_data)
      k_weights = model.get_weights()
      k_config = model.get_config()
  
      with tf.name_scope("TFE"):
          x = tfe.define_private_input(
              "inputter", lambda: tf.convert_to_tensor(input_data)
          )
  
          tfe_model = tfe.keras.models.model_from_config(k_config)
          tfe_model.set_weights(k_weights)
          y = tfe_model(x)
          actual = y.reveal().to_native()
  
      np.testing.assert_allclose(actual, expected, rtol=1e-2, atol=1e-2)
  
imports: import unittest
  import numpy
  import pytest
  import tensorflow
  import tf_encrypted
  from tf_encrypted.keras.testing_utils import agreement_test
  from tf_encrypted.keras.testing_utils import layer_test
label_desc: Use image node_id 6 for calling the TestDepthwiseConv2d obj's underlying member method code with example usage: obj.test_depthwise_conv2d_set_weights() without return types