code: def test_layer_core_act(cls):
      cls.batch_size = 5
      cls.inputs_shape = [cls.batch_size, 400, 400, 3]
      cls.input_layer = Input(cls.inputs_shape, name="input_layer")
  
      cls.n1 = tl.layers.Conv2dLayer(
          act=tf.nn.relu,
          shape=(5, 5, 3, 32),
          strides=(1, 2, 2, 1),
          padding="SAME",
          b_init=tf.constant_initializer(value=0.0),
          name="conv2dlayer",
      )(cls.input_layer)
  
      cls.n2 = tl.layers.Conv2d(
          n_filter=32,
          filter_size=(3, 3),
          strides=(2, 2),
          act="relu",
          name="conv2d",
      )(cls.n1)
  
      cls.n3 = tl.layers.Conv2d(
          n_filter=32,
          filter_size=(3, 3),
          strides=(2, 2),
          act="leaky_relu",
          b_init=None,
      )(cls.n2)
  
      cls.n4 = tl.layers.Conv2d(
          n_filter=32,
          filter_size=(3, 3),
          strides=(2, 2),
          act="lrelu",
          b_init=None,
      )(cls.n2)
  
      cls.n5 = tl.layers.Conv2d(
          n_filter=32,
          filter_size=(3, 3),
          strides=(2, 2),
          act="sigmoid",
          in_channels=32,
      )(cls.n4)
  
      cls.n6 = tl.layers.Conv2d(
          n_filter=32,
          filter_size=(3, 3),
          strides=(2, 2),
          act="tanh",
          in_channels=32,
      )(cls.n5)
  
      cls.n7 = tl.layers.Conv2d(
          n_filter=32,
          filter_size=(3, 3),
          strides=(2, 2),
          act="leaky_relu0.22",
          in_channels=32,
      )(cls.n6)
  
      cls.n8 = tl.layers.Conv2d(
          n_filter=32,
          filter_size=(3, 3),
          strides=(2, 2),
          act="lrelu0.22",
          in_channels=32,
      )(cls.n7)
  
      cls.n9 = tl.layers.Conv2d(
          n_filter=32,
          filter_size=(3, 3),
          strides=(2, 2),
          act="softplus",
          in_channels=32,
      )(cls.n8)
  
      cls.n10 = tl.layers.Conv2d(
          n_filter=32,
          filter_size=(3, 3),
          strides=(2, 2),
          act="relu6",
          in_channels=32,
      )(cls.n9)
  
      cls.model = Model(cls.input_layer, cls.n8)
  
file_path: TensorLayer/tests/layers/test_layers_core_act.py
imports: import os
  import unittest
  import tensorflow
  import tensorlayer
  from tensorlayer.layers import *
  from tensorlayer.models import *
  from tests.utils import CustomTestCase
label_desc: Use image node_id 3 for calling the Layer_Convolution_2D_Test obj's underlying member method code with example usage: obj.test_layer_core_act(cls) without return types