Removed run_all_in_graph_and_eager_mode in polynomial_test.py (#1337)

* Removed run_all_in_eager_and_graph_mode.

* Add the decorator to run in eager mode too.

Author: gabrieldemarmiesse

tensorflow_addons/layers/polynomial_test.py

@@ -21,41 +21,43 @@
 import tensorflow as tf
 
 from tensorflow_addons.layers.polynomial import PolynomialCrossing
-from tensorflow_addons.utils import test_utils
-
-
-@test_utils.run_all_in_graph_and_eager_modes
-class PolynomialCrossingTest(tf.test.TestCase):
-    # Do not use layer_test due to multiple inputs.
-
-    def test_full_matrix(self):
-        x0 = np.asarray([[0.1, 0.2, 0.3]]).astype(np.float32)
-        x = np.asarray([[0.4, 0.5, 0.6]]).astype(np.float32)
-        layer = PolynomialCrossing(projection_dim=None, kernel_initializer="ones")
-        output = layer([x0, x])
-        self.evaluate(tf.compat.v1.global_variables_initializer())
-        self.assertAllClose(np.asarray([[0.55, 0.8, 1.05]]), output)
-
-    def test_invalid_proj_dim(self):
-        with self.assertRaisesRegexp(ValueError, r"is not supported yet"):
-            x0 = np.random.random((12, 5))
-            x = np.random.random((12, 5))
-            layer = PolynomialCrossing(projection_dim=6)
-            layer([x0, x])
-
-    def test_invalid_inputs(self):
-        with self.assertRaisesRegexp(ValueError, r"must be a tuple or list of size 2"):
-            x0 = np.random.random((12, 5))
-            x = np.random.random((12, 5))
-            x1 = np.random.random((12, 5))
-            layer = PolynomialCrossing(projection_dim=6)
-            layer([x0, x, x1])
-
-    def test_serialization(self):
-        layer = PolynomialCrossing(projection_dim=None)
-        serialized_layer = tf.keras.layers.serialize(layer)
-        new_layer = tf.keras.layers.deserialize(serialized_layer)
-        self.assertEqual(layer.get_config(), new_layer.get_config())
+
+
+@pytest.mark.usefixtures("maybe_run_functions_eagerly")
+def test_full_matrix():
+    x0 = np.asarray([[0.1, 0.2, 0.3]]).astype(np.float32)
+    x = np.asarray([[0.4, 0.5, 0.6]]).astype(np.float32)
+    layer = PolynomialCrossing(projection_dim=None, kernel_initializer="ones")
+    output = layer([x0, x])
+    np.testing.assert_allclose([[0.55, 0.8, 1.05]], output)
+
+
+@pytest.mark.usefixtures("maybe_run_functions_eagerly")
+def test_invalid_proj_dim():
+    with pytest.raises(ValueError) as exception_info:
+        x0 = np.random.random((12, 5))
+        x = np.random.random((12, 5))
+        layer = PolynomialCrossing(projection_dim=6)
+        layer([x0, x])
+    assert "is not supported yet" in str(exception_info.value)
+
+
+@pytest.mark.usefixtures("maybe_run_functions_eagerly")
+def test_invalid_inputs():
+    with pytest.raises(ValueError) as exception_info:
+        x0 = np.random.random((12, 5))
+        x = np.random.random((12, 5))
+        x1 = np.random.random((12, 5))
+        layer = PolynomialCrossing(projection_dim=6)
+        layer([x0, x, x1])
+    assert "must be a tuple or list of size 2" in str(exception_info.value)
+
+
+def test_serialization():
+    layer = PolynomialCrossing(projection_dim=None)
+    serialized_layer = tf.keras.layers.serialize(layer)
+    new_layer = tf.keras.layers.deserialize(serialized_layer)
+    assert layer.get_config() == new_layer.get_config()
 
 
 if __name__ == "__main__":