update test

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

@@ -80,32 +80,42 @@ def forward(self, x):
                 return x * self._w
 
         with paddle.fluid.dygraph.guard():
+            np_neg_ones = np.ones(w_shape) * -1
+
             model = MyLayer()
             x = paddle.ones([1, 3, 4])
-            loss = model(x)
             asgd = paddle.optimizer.ASGD(learning_rate=1., parameters=model.parameters(), t0=1)
-            loss.backward()
 
-            np_neg_ones = np.ones(w_shape) * -1
-            print(f'grad before step: {model._w.grad}')
-            print(f'w before step: {model._w.numpy()}')
+            loss = model(x)
+            loss.backward()
             asgd.step()
-            print(f'w after step: {model._w.numpy()}')
-            print(f'grad after step: {model._w.grad}')
             assert np.allclose(model._w.numpy(), np_neg_ones)
             assert np.allclose(asgd.averaged_parameters()[0].numpy(), np_neg_ones)
-            print(f'grad: {model._w.grad}')
-            print(f'w before step: {model._w.numpy()}')
+            asgd.clear_grad()
+
+            loss = model(x)
+            loss.backward()
             asgd.step()
-            print(f'w after step: {model._w.numpy()}')
             assert np.allclose(model._w.numpy(), np_neg_ones * 2)
             assert np.allclose(asgd.averaged_parameters()[0].numpy(), np_neg_ones * 2)
+            asgd.clear_grad()
+
+            loss = model(x)
+            loss.backward()
             asgd.step()
             assert np.allclose(model._w.numpy(), np_neg_ones * 3)
             assert np.allclose(asgd.averaged_parameters()[0].numpy(), np_neg_ones * 3)
+            asgd.clear_grad()
+
+            loss = model(x)
+            loss.backward()
             asgd.step()
             assert np.allclose(model._w.numpy(), np_neg_ones * 4)
             assert np.allclose(asgd.averaged_parameters()[0].numpy(), np_neg_ones * 3.5)
+            asgd.clear_grad()
+
+            loss = model(x)
+            loss.backward()
             asgd.step()
             assert np.allclose(model._w.numpy(), np_neg_ones * 5)
             assert np.allclose(asgd.averaged_parameters()[0].numpy(), np_neg_ones * 4)