Add TF-specific tests for ReLU layer.

tests/keras/layers/advanced_activations_test.py

 import pytest
 from keras.utils.test_utils import layer_test
 from keras import layers
+from keras import backend as K
 
 
 def test_leaky_relu():
@@ -42,6 +43,12 @@ def test_relu():
                        '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):
@@ -54,5 +61,20 @@ def test_relu():
                    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__])