code: def __init__(self, include_top=True):
      super(basic_dynamic_model, self).__init__()
      self.include_top = include_top
      self.conv1 = Conv2d(
          16,
          (5, 5),
          (1, 1),
          padding="SAME",
          act=tf.nn.relu,
          in_channels=3,
          name="conv1",
      )
      self.pool1 = MaxPool2d(
          (3, 3), (2, 2), padding="SAME", name="pool1"
      )
  
      self.conv2 = Conv2d(
          16,
          (5, 5),
          (1, 1),
          padding="SAME",
          act=tf.nn.relu,
          in_channels=16,
          name="conv2",
      )
      self.pool2 = MaxPool2d(
          (3, 3), (2, 2), padding="SAME", name="pool2"
      )
  
      self.flatten = Flatten(name="flatten")
      self.dense1 = Dense(100, act=None, in_channels=576, name="dense1")
      if include_top is True:
          self.dense2 = Dense(
              10, act=None, in_channels=100, name="dense2"
          )
  
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 1 to create a new basic_dynamic_model object from inherited base classes: Model with example: obj = basic_dynamic_model(include_top)