code: def test_net2(self):
      print("-" * 20, "test_net2", "-" * 20)
  
      def get_unstack_model(input_shape):
          ni = Input(input_shape)
  
          nn = Dropout(keep=0.9)(ni)
  
          a, b, c = UnStack(axis=-1)(nn)
  
          b = Flatten()(b)
          b = Dense(10)(b)
  
          c = Flatten()(c)
  
          M = Model(inputs=ni, outputs=[a, b, c])
          return M
  
      net = get_unstack_model([None, 24, 24, 3])
  
      for k, v in enumerate(net._node_by_depth):
          print(k, [x.name for x in v], [x.in_tensors_idxes for x in v])
  
      data = np.random.normal(size=[2, 24, 24, 3]).astype(np.float32)
      out = net(data, is_train=True)
  
      self.assertEqual(len(out), 3)
  
file_path: TensorLayer/tests/layers/test_layernode.py
imports: import os
  import unittest
  import numpy
  import tensorflow
  from tensorflow.python.ops.rnn_cell import LSTMCell
  import tensorlayer
  from tensorlayer.layers import *
  from tensorlayer.models import Model
  from tests.utils import CustomTestCase
label_desc: Use image node_id 4 for calling the LayerNode_Test obj's underlying member method code with example usage: obj.test_net2() and returns: M