code: def test_prelu_3(self):
      inputs = tl.layers.Input([10, 10, 5])
      prelulayer = tl.layers.PRelu(in_channels=5)
      prelu = prelulayer(inputs)
      model = tl.models.Model(inputs=inputs, outputs=prelu)
      out = model(self.data2, is_train=True)
  
      print(prelulayer)
  
      gt = np.zeros(shape=self.data2.shape)
      for i in range(len(gt)):
          for k in range(len(gt[i])):
              for j in range(len(gt[i][k])):
                  if self.data2[i][k][j] >= 0:
                      gt[i][k][j] = self.data2[i][k][j]
                  else:
                      gt[i][k][j] = (
                          prelulayer.alpha_var_constrained.numpy()[j]
                          * self.data2[i][k][j]
                      )
  
      self.assertTrue(np.array_equal(out.numpy(), gt))
  
file_path: TensorLayer/tests/layers/test_layers_activation.py
imports: import os
  import unittest
  import numpy
  import tensorflow
  import tensorlayer
  from tests.utils import CustomTestCase
label_desc: Use image node_id 5 for calling the Activation_Layer_Test obj's underlying member method code with example usage: obj.test_prelu_3() without return types