From cc1a9f4238a4b0ed475de4adb5955772ceaf63cf Mon Sep 17 00:00:00 2001
From: zhongpu <2013000149@qq.com>
Date: Wed, 8 Jan 2020 11:13:53 +0800
Subject: [PATCH] fix sample code in paddle/fluid/imperative/README.md (#22141)

* fix sample code, test=develop

* polish code style, test=develop
---
 paddle/fluid/imperative/README.md | 24 +++++++++++++-----------
 1 file changed, 13 insertions(+), 11 deletions(-)

diff --git a/paddle/fluid/imperative/README.md b/paddle/fluid/imperative/README.md
index 4c4d619b35a..6db74394f3e 100644
--- a/paddle/fluid/imperative/README.md
+++ b/paddle/fluid/imperative/README.md
@@ -169,30 +169,32 @@ with fluid.imperative.guard():
     dy_grad = var_inp._gradient()
 
 
-class MLP(fluid.imperative.Layer):
-    def __init__(self):
+class MLP(fluid.Layer):
+    def __init__(self, input_size):
         super(MLP, self).__init__()
-        self._fc1 = FC(3,
+        self._linear1 = Linear(input_size,
+                       3,
                        fluid.ParamAttr(
                            initializer=fluid.initializer.Constant(value=0.1)))
-        self._fc2 = FC(4,
+        self._linear2 = Linear(3,
+                       4,
                        fluid.ParamAttr(
                            initializer=fluid.initializer.Constant(value=0.1)))
 
     def forward(self, inputs):
-        x = self._fc1(inputs)
-        x = self._fc2(x)
+        x = self._linear1(inputs)
+        x = self._linear2(x)
         x = fluid.layers.reduce_sum(x)
         return x
 
 
  np_inp = np.array([[1.0, 2.0], [3.0, 4.0]], dtype=np.float32)
- with fluid.imperative.guard():
-     var_inp = fluid.imperative.base.to_variable(np_inp)
-     mlp = MLP()
+ with fluid.dygraph.guard():
+     var_inp = fluid.dygraph.base.to_variable(np_inp)
+     mlp = MLP(input_size=2)
      out = mlp(var_inp)
-     dy_out = out._numpy()
-     out._backward()
+     dy_out = out.numpy()
+     out.backward()
 ```
 
 # Plan
-- 
GitLab