modify something (PaddlePaddle#5188)

* Update basic_usage_cn.md

* Update basic_usage_cn.md

* Update principle_cn.md

delete duplicate use of to_static

* Update principle_cn.md

docs/guides/jit/basic_usage_cn.md

@@ -964,17 +964,18 @@ paddle.jit.save(net, path='./simple_net')
                 print("Epoch {} batch {}: loss = {}".format(
                     epoch_id, batch_id, np.mean(loss.numpy())))
 
-    def set_build_strategy():
+    def get_build_strategy():
         build_strategy = paddle.static.BuildStrategy()
         # addto 策略常搭配 FLAGS_max_inplace_grad_add 变量使用
         build_strategy.enable_addto = True
         os.environ['FLAGS_max_inplace_grad_add'] = "8"
         build_strategy.fuse_elewise_add_act_ops = True
+        return build_strategy
 
     # 构建神经网络
     model = resnet50()
     # 动转静，并设置计算图优化策略
-    model = paddle.jit.to_static(model, build_strategy=set_build_strategy())
+    model = paddle.jit.to_static(model, build_strategy=get_build_strategy())
     # 设置损失函数
     loss_fn = nn.CrossEntropyLoss()
     # 设置优化器

docs/guides/jit/principle_cn.md

@@ -62,13 +62,13 @@ out = paddle.add(out, y)
 ```python
 import paddle
 from paddle.jit import to_static
+from paddle.static import InputSpec
 
 class SimpleNet(paddle.nn.Layer):
     def __init__(self):
         super(SimpleNet, self).__init__()
         self.linear = paddle.nn.Linear(10, 3)
 
-    @to_static
     def forward(self, x, y):
         out = self.linear(x)
         out = out + y
@@ -88,7 +88,7 @@ net = paddle.jit.to_static(net, input_spec=[x_spec, y_spec])  # 动静转换
 
 
 + 可以指定某些维度为 ``None`` ， 如 ``batch_size`` ，``seq_len`` 维度
-+ 可以指定 Placeholder 的 ``name`` ，方面预测时根据 ``name`` 输入数据
++ 可以指定 Placeholder 的 ``name`` ，方便预测时根据 ``name`` 输入数据
 
 > 注：``InputSpec`` 接口的详细用法，请参见 [InputSpec 的用法介绍](https://www.paddlepaddle.org.cn/documentation/docs/zh/develop/guides/jit/basic_usage_cn.html#inputspec)。