code: def test_prelu(self, init_alpha):
      import lasagne
  
      input_shape = (3, 28)
      input = np.random.randn(*input_shape).astype(theano.config.floatX)
  
      l_in = lasagne.layers.input.InputLayer(input_shape)
      l_dense = lasagne.layers.dense.DenseLayer(l_in, num_units=100)
      l_prelu = lasagne.layers.prelu(l_dense, alpha=init_alpha)
      output = lasagne.layers.get_output(l_prelu, input)
  
      assert l_dense.nonlinearity == lasagne.nonlinearities.identity
  
      W = l_dense.W.get_value()
      b = l_dense.b.get_value()
      alpha_v = l_prelu.alpha.get_value()
      expected = np.dot(input, W) + b
      expected = (
          np.maximum(expected, 0) + np.minimum(expected, 0) * alpha_v
      )
      assert np.allclose(output.eval(), expected, atol=1e-07)
  
imports: from mock import Mock
  import numpy
  import pytest
  import theano
  from lasagne.layers import InputLayer, standardize, get_output, get_all_params
  from lasagne.utils import floatX
label_desc: Use image node_id 6 for calling the TestParametricRectifierLayer obj's underlying member method code with example usage: obj.test_prelu(init_alpha) without return types