code: def test_prelu_output_by_dense_input(self):
      prelu_layer = layers.PRelu(alpha=0.25)
      prelu_layer.create_variables((None, 1))
  
      X = np.array([[10, 1, 0.1, 0, -0.1, -1]]).T
      expected_output = np.array([[10, 1, 0.1, 0, -0.025, -0.25]]).T
      actual_output = self.eval(prelu_layer.activation_function(X))
  
      np.testing.assert_array_almost_equal(
          expected_output, actual_output
      )
  
imports: import math
  import six
  import numpy
  import tensorflow
  from neupy.utils import asfloat
  from neupy.exceptions import LayerConnectionError, WeightInitializationError
  from neupy import layers, algorithms, init
  from base import BaseTestCase
  from helpers import simple_classification
label_desc: Use image node_id 5 for calling the PReluTestCase obj's underlying member method code with example usage: obj.test_prelu_output_by_dense_input() without return types