From 4a01d23631ef5298f073634d0fc08c3e779a1a64 Mon Sep 17 00:00:00 2001
From: Megvii Engine Team <megengine@megvii.com>
Date: Wed, 5 Aug 2020 10:53:08 +0800
Subject: [PATCH] ci(mgb/python_module): fix doctest syntax error

GitOrigin-RevId: e98ca810ea7ca46de473ac14ae9078cfc9a4bd32
---
 python_module/megengine/core/function.py     |  2 +-
 python_module/megengine/module/sequential.py | 21 ++++++++++----------
 2 files changed, 12 insertions(+), 11 deletions(-)

diff --git a/python_module/megengine/core/function.py b/python_module/megengine/core/function.py
index 1219b21e2..c6fb7d438 100644
--- a/python_module/megengine/core/function.py
+++ b/python_module/megengine/core/function.py
@@ -82,7 +82,7 @@ class Function(metaclass=ABCMeta):
                 self.save_for_backward(y)
                 return y
 
-            def backward(self. output_grads):
+            def backward(self, output_grads):
                 (y, ) = self.saved_tensors
                 return output_grads * y * (1-y)
 
diff --git a/python_module/megengine/module/sequential.py b/python_module/megengine/module/sequential.py
index 42d43d844..01291e98a 100644
--- a/python_module/megengine/module/sequential.py
+++ b/python_module/megengine/module/sequential.py
@@ -21,26 +21,27 @@ class Sequential(Module):
     .. testcode::
         from collections import OrderedDict
         import numpy as np
-        import megengine.nn as nn
-        import megengine.nn.functional as F
+        import megengine.functional as F
+        from megengine.module import Sequential, Linear
+        from megengine import tensor
 
         batch_size = 64
-        data = nn.Input("data", shape=(batch_size, 1, 28, 28), dtype=np.float32, value=np.zeros((batch_size, 1, 28, 28)))
-        label = nn.Input("label", shape=(batch_size,), dtype=np.int32, value=np.zeros(batch_size,))
+        data = tensor(np.zeros((batch_size, 1, 28, 28)), dtype=np.float32)
+        label = tensor(np.zeros(batch_size,), dtype=np.int32)
 
         data = data.reshape(batch_size, -1)
 
-        net0 = nn.Sequential(
-                nn.Linear(28 * 28, 320),
-                nn.Linear(320, 10)
+        net0 = Sequential(
+                Linear(28 * 28, 320),
+                Linear(320, 10)
             )
 
         pred0 = net0(data)
 
         modules = OrderedDict()
-        modules["fc0"] = nn.Linear(28 * 28, 320)
-        modules["fc1"] = nn.Linear(320, 10)
-        net1 = nn.Sequential(modules)
+        modules["fc0"] = Linear(28 * 28, 320)
+        modules["fc1"] = Linear(320, 10)
+        net1 = Sequential(modules)
 
         pred1 = net1(data)
     """
-- 
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