Add relu layer for lenet (#24874)

* add relu for lenet, test=develop

* fix test model, test=develop

python/paddle/incubate/hapi/tests/test_model.py

@@ -23,8 +23,7 @@ import shutil
 import tempfile
 
 from paddle import fluid
-from paddle.fluid.dygraph.nn import Conv2D, Pool2D, Linear
-from paddle.fluid.dygraph.container import Sequential
+from paddle.nn import Conv2D, Pool2D, Linear, ReLU, Sequential
 from paddle.fluid.dygraph.base import to_variable
 
 from paddle.incubate.hapi.model import Model, Input, set_device
@@ -42,9 +41,11 @@ class LeNetDygraph(fluid.dygraph.Layer):
         self.features = Sequential(
             Conv2D(
                 1, 6, 3, stride=1, padding=1),
+            ReLU(),
             Pool2D(2, 'max', 2),
             Conv2D(
                 6, 16, 5, stride=1, padding=0),
+            ReLU(),
             Pool2D(2, 'max', 2))
 
         if num_classes > 0:

python/paddle/incubate/hapi/vision/models/lenet.py

@@ -13,8 +13,7 @@
 #limitations under the License.
 
 import paddle.fluid as fluid
-from paddle.fluid.dygraph.nn import Conv2D, BatchNorm, Pool2D, Linear
-from paddle.fluid.dygraph.container import Sequential
+from paddle.nn import Conv2D, Pool2D, Linear, ReLU, Sequential
 
 from ...model import Model
 
@@ -44,9 +43,11 @@ class LeNet(Model):
         self.features = Sequential(
             Conv2D(
                 1, 6, 3, stride=1, padding=1),
+            ReLU(),
             Pool2D(2, 'max', 2),
             Conv2D(
                 6, 16, 5, stride=1, padding=0),
+            ReLU(),
             Pool2D(2, 'max', 2))
 
         if num_classes > 0: