Merge pull request #16636 from panyx0718/imperative

add a simple test

python/paddle/fluid/tests/unittests/test_imperative_basic.py

@@ -348,6 +348,55 @@ class TestImperative(unittest.TestCase):
         self.assertEqual(mlp._fc2, sublayers[1])
         self.assertEqual(len(sublayers), 2)
 
+    def test_dygraph_vs_static(self):
+        inp1 = np.random.rand(4, 3, 3)
+        inp2 = np.random.rand(4, 3, 3)
+
+        # dynamic graph
+        with fluid.dygraph.guard():
+            if np.sum(inp1) < np.sum(inp2):
+                x = fluid.layers.elementwise_add(inp1, inp2)
+            else:
+                x = fluid.layers.elementwise_sub(inp1, inp2)
+            dygraph_result = x._numpy()
+
+        # static graph
+        with new_program_scope():
+            inp_data1 = fluid.layers.data(
+                name='inp1', shape=[3, 3], dtype=np.float32)
+            inp_data2 = fluid.layers.data(
+                name='inp2', shape=[3, 3], dtype=np.float32)
+
+            a = fluid.layers.expand(
+                fluid.layers.reshape(
+                    fluid.layers.reduce_sum(inp_data1), [1, 1]), [4, 1])
+            b = fluid.layers.expand(
+                fluid.layers.reshape(
+                    fluid.layers.reduce_sum(inp_data2), [1, 1]), [4, 1])
+            cond = fluid.layers.less_than(x=a, y=b)
+
+            ie = fluid.layers.IfElse(cond)
+            with ie.true_block():
+                d1 = ie.input(inp_data1)
+                d2 = ie.input(inp_data2)
+                d3 = fluid.layers.elementwise_add(d1, d2)
+                ie.output(d3)
+
+            with ie.false_block():
+                d1 = ie.input(inp_data1)
+                d2 = ie.input(inp_data2)
+                d3 = fluid.layers.elementwise_sub(d1, d2)
+                ie.output(d3)
+            out = ie()
+
+            exe = fluid.Executor(fluid.CPUPlace(
+            ) if not core.is_compiled_with_cuda() else fluid.CUDAPlace(0))
+            static_result = exe.run(fluid.default_main_program(),
+                                    feed={'inp1': inp1,
+                                          'inp2': inp2},
+                                    fetch_list=out)[0]
+        self.assertTrue(np.allclose(dygraph_result, static_result))
+
     def test_rnn(self):
         np_inp = np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0],
                            [10.0, 11.0, 12.0]])