def METHOD_NAME(self):
    if version.parse(tf.version.VERSION) >= version.parse("2.00"):
        tf.keras.backend.clear_session()
        # Load the  model to test layer selection
        model = get_model()
        conv1_op = model.layers[1]
        conv2_op = model.layers[2]
        conv3_op = model.layers[3]
        matmul1_op = model.layers[5]
        conv1_op_output_shape = conv1_op.output_shape
        conv2_op_output_shape = conv2_op.output_shape
        conv3_op_output_shape = conv3_op.output_shape
        matmul1_op_output_shape = matmul1_op.output_shape
        layer1 = Layer(conv1_op, conv1_op.name, output_shape=conv1_op_output_shape)
        layer2 = Layer(conv2_op, conv2_op.name, output_shape=conv2_op_output_shape)
        layer3 = Layer(conv3_op, conv3_op.name, output_shape=conv3_op_output_shape)
        layer4 = Layer(matmul1_op, matmul1_op.name, output_shape=matmul1_op_output_shape)
        layer_db = MagicMock()
        layer_db.__iter__.return_value = [layer1, layer2, layer3, layer4]
        layer_selector = ConvNoDepthwiseLayerSelector()
        layer_selector.select(layer_db, [])
        layer_db.mark_picked_layers.assert_called_once_with([layer1, layer2])
        # Two regular conv layers - one in ignore list
        layer_db.mark_picked_layers.reset_mock()
        layer_selector.select(layer_db, [layer2.module])
        layer_db.mark_picked_layers.assert_called_once_with([layer1])