add unittest of get_weights set_weights with create_parameter (#262)

parl/core/fluid/tests/model_base_test.py

@@ -690,6 +690,43 @@ class ModelBaseTest(unittest.TestCase):
             self.executor.run(
                 pred_program, feed={'obs': x}, fetch_list=[model_output])
 
+    def test_get_weights_set_weights_with_create_parameter(self):
+        model1 = TestModel2()
+        model2 = TestModel2()
+
+        pred_program = fluid.Program()
+        with fluid.program_guard(pred_program):
+            obs = layers.data(name='obs', shape=[100], dtype='float32')
+            model1_output = model1.predict(obs)
+            model2_output = model2.predict(obs)
+
+        self.executor.run(fluid.default_startup_program())
+
+        N = 10
+        random_obs = np.random.random(size=(N, 100)).astype('float32')
+        for i in range(N):
+            x = np.expand_dims(random_obs[i], axis=0)
+            outputs = self.executor.run(
+                pred_program,
+                feed={'obs': x},
+                fetch_list=[model1_output, model2_output])
+            self.assertNotEqual(
+                np.sum(outputs[0].flatten()), np.sum(outputs[1].flatten()))
+
+        # pass parameters of self.model to model2
+        params = model1.get_weights()
+        model2.set_weights(params)
+
+        random_obs = np.random.random(size=(N, 100)).astype('float32')
+        for i in range(N):
+            x = np.expand_dims(random_obs[i], axis=0)
+            outputs = self.executor.run(
+                pred_program,
+                feed={'obs': x},
+                fetch_list=[model1_output, model2_output])
+            self.assertEqual(
+                np.sum(outputs[0].flatten()), np.sum(outputs[1].flatten()))
+
 
 if __name__ == '__main__':
     unittest.main()