old_contents: import pytest
  from keras.utils.test_utils import layer_test
  from keras import layers
  
  
  def test_leaky_relu():
      for alpha in [0., .5, -1.]:
          layer_test(layers.LeakyReLU, kwargs={'alpha': alpha},
                     input_shape=(2, 3, 4))
  
  
  def test_prelu():
      layer_test(layers.PReLU, kwargs={},
                 input_shape=(2, 3, 4))
  
  
  def test_prelu_share():
      layer_test(layers.PReLU, kwargs={'shared_axes': 1},
                 input_shape=(2, 3, 4))
  
  
  def test_elu():
      for alpha in [0., .5, -1.]:
          layer_test(layers.ELU, kwargs={'alpha': alpha},
                     input_shape=(2, 3, 4))
  
  
  def test_thresholded_relu():
      layer_test(layers.ThresholdedReLU, kwargs={'theta': 0.5},
                 input_shape=(2, 3, 4))
  
  
  def test_softmax():
      for axis in [1, -1]:
          layer_test(layers.Softmax, kwargs={'axis': axis},
                     input_shape=(2, 3, 4))
  
  
  def test_relu():
      layer_test(layers.ReLU,
                 kwargs={'max_value': 10,
                         'negative_slope': 0.2,
                         'threshold': 3.0},
                 input_shape=(2, 3, 4))
  
      # max_value of ReLU layer cannot be negative value
      with pytest.raises(ValueError):
          layer_test(layers.ReLU, kwargs={'max_value': -2.0},
                     input_shape=(2, 3, 4))
  
      # negative_slope of ReLU layer cannot be negative value
      with pytest.raises(ValueError):
          layer_test(layers.ReLU, kwargs={'negative_slope': -2.0},
                     input_shape=(2, 3, 4))
  
  
  if __name__ == '__main__':
      pytest.main([__file__])
  
new_contents: import pytest
  from keras.utils.test_utils import layer_test
  from keras import layers
  from keras import backend as K
  
  
  def test_leaky_relu():
      for alpha in [0., .5, -1.]:
          layer_test(layers.LeakyReLU, kwargs={'alpha': alpha},
                     input_shape=(2, 3, 4))
  
  
  def test_prelu():
      layer_test(layers.PReLU, kwargs={},
                 input_shape=(2, 3, 4))
  
  
  def test_prelu_share():
      layer_test(layers.PReLU, kwargs={'shared_axes': 1},
                 input_shape=(2, 3, 4))
  
  
  def test_elu():
      for alpha in [0., .5, -1.]:
          layer_test(layers.ELU, kwargs={'alpha': alpha},
                     input_shape=(2, 3, 4))
  
  
  def test_thresholded_relu():
      layer_test(layers.ThresholdedReLU, kwargs={'theta': 0.5},
                 input_shape=(2, 3, 4))
  
  
  def test_softmax():
      for axis in [1, -1]:
          layer_test(layers.Softmax, kwargs={'axis': axis},
                     input_shape=(2, 3, 4))
  
  
  def test_relu():
      layer_test(layers.ReLU,
                 kwargs={'max_value': 10,
                         'negative_slope': 0.2,
                         'threshold': 3.0},
                 input_shape=(2, 3, 4))
      layer_test(layers.ReLU,
                 kwargs={'max_value': 6},
                 input_shape=(2, 3, 4))
      layer_test(layers.ReLU,
                 kwargs={'negative_slope': 0.2},
                 input_shape=(2, 3, 4))
  
      # max_value of ReLU layer cannot be negative value
      with pytest.raises(ValueError):
          layer_test(layers.ReLU, kwargs={'max_value': -2.0},
                     input_shape=(2, 3, 4))
  
      # negative_slope of ReLU layer cannot be negative value
      with pytest.raises(ValueError):
          layer_test(layers.ReLU, kwargs={'negative_slope': -2.0},
                     input_shape=(2, 3, 4))
  
  
  @pytest.mark.skipif((K.backend() != 'tensorflow'),
                      reason='TF-specific implementation.')
  def test_relu_tf_ops():
      inputs = layers.Input((3,))
      # Test that `relu` op gets used.
      outputs = layers.ReLU()(inputs)
      assert outputs.op.name.lower().endswith('/relu')
      # Test that `leakyrelu` op gets used.
      outputs = layers.ReLU(negative_slope=0.2)(inputs)
      assert outputs.op.name.lower().endswith('/leakyrelu')
      # Test that `relu6` op gets used.
      outputs = layers.ReLU(max_value=6)(inputs)
      assert outputs.op.name.lower().endswith('/relu6')
  
  
  if __name__ == '__main__':
      pytest.main([__file__])
  
subject: Add TF-specific tests for ReLU layer.