diff --git a/python_module/megengine/functional/nn.py b/python_module/megengine/functional/nn.py
index 2fe462a5873b91e22a64f8d01fb644e766c501d9..a194d9c656eb9ead3ec9ad92c377a8366b4076de 100644
--- a/python_module/megengine/functional/nn.py
+++ b/python_module/megengine/functional/nn.py
@@ -741,11 +741,11 @@ def dropout(inp: Tensor, drop_prob: float, rescale: bool = True) -> Tensor:
     .. testcode::
 
         import numpy as np
-        from megengine import tensor
+        import megengine as mge
+
         import megengine.functional as F
-        from megengine.random import manual_seed
+        from megengine import tensor
 
-        manual_seed(0)
         data = tensor(np.ones(10, dtype=np.float32))
         out = F.dropout(data, 1./3.)
         print(out.numpy())
@@ -753,6 +753,7 @@ def dropout(inp: Tensor, drop_prob: float, rescale: bool = True) -> Tensor:
     Outputs:
 
     .. testoutput::
+        :options: +SKIP
 
         [1.5 1.5 0.  1.5 1.5 1.5 1.5 1.5 1.5 1.5]
 
diff --git a/python_module/megengine/functional/tensor.py b/python_module/megengine/functional/tensor.py
index 570bd27f74189f885e6303a683bf51948e9803c7..270604cc0d468b220b0f1dc94a3e5b33825ac65f 100644
--- a/python_module/megengine/functional/tensor.py
+++ b/python_module/megengine/functional/tensor.py
@@ -249,6 +249,7 @@ def scatter(inp: Tensor, axis: int, index: Tensor, source: Tensor) -> Tensor:
         import numpy as np
         import megengine.functional as F
         from megengine.core import tensor
+
         inp = tensor(np.zeros(shape=(3,5),dtype=np.float32))
         source = tensor([[0.9935,0.9465,0.2256,0.8926,0.4396],[0.7723,0.0718,0.5939,0.357,0.4576]])
         index = tensor([[0,2,0,2,1],[2,0,0,1,2]])
@@ -258,6 +259,7 @@ def scatter(inp: Tensor, axis: int, index: Tensor, source: Tensor) -> Tensor:
     Outputs:
 
     .. testoutput::
+        :options: +SKIP
 
         [[0.9935 0.0718 0.5939 0.     0.    ]
          [0.     0.     0.     0.357  0.4396]
@@ -314,9 +316,9 @@ def scatter(inp: Tensor, axis: int, index: Tensor, source: Tensor) -> Tensor:
 def where(mask: Tensor, x: Tensor, y: Tensor) -> Tensor:
     r"""
     Select elements either from Tensor x or Tensor y, according to mask.
-    
+
     .. math::
-        
+
         \textrm{out}_i = x_i \textrm{ if } \textrm{mask}_i \textrm{ is True else } y_i
 
     :param mask: a mask used for choosing x or y
diff --git a/python_module/megengine/module/conv.py b/python_module/megengine/module/conv.py
index 1d10db1679549a7cbc14ee233997dea39bd6bb50..79c374cb84c7eb2f4176257e26c70231ffcb6575 100644
--- a/python_module/megengine/module/conv.py
+++ b/python_module/megengine/module/conv.py
@@ -115,7 +115,7 @@ class Conv2d(_ConvNd):
         and there would be an extra dimension at the beginning of the weight's
         shape. Specifically, the shape of weight would be ``(groups,
         out_channel // groups, in_channels // groups, *kernel_size)``.
-    :param bias: wether to add a bias onto the result of convolution. Default:
+    :param bias: whether to add a bias onto the result of convolution. Default:
         True
     :param conv_mode: Supports `CROSS_CORRELATION` or `CONVOLUTION`. Default:
         `CROSS_CORRELATION`.
diff --git a/python_module/megengine/random/distribution.py b/python_module/megengine/random/distribution.py
index cd5130ab097c91037982e3e8cee83893515047e2..1d3882cc1ad988e935fe1a52f414f74eb32022e2 100644
--- a/python_module/megengine/random/distribution.py
+++ b/python_module/megengine/random/distribution.py
@@ -42,11 +42,11 @@ def gaussian(
         import megengine as mge
         import megengine.random as rand
 
-        rand.manual_seed(0)
         x = rand.gaussian((2, 2), mean=0, std=1)
         print(x.numpy())
 
     .. testoutput::
+        :options: +SKIP
 
         [[-0.20235455 -0.6959438 ]
          [-1.4939808  -1.5824696 ]]
@@ -79,11 +79,11 @@ def uniform(
         import megengine as mge
         import megengine.random as rand
 
-        rand.manual_seed(0)
         x = rand.uniform((2, 2))
         print(x.numpy())
 
     .. testoutput::
+        :options: +SKIP
 
         [[0.76901674 0.70496535]
          [0.09365904 0.62957656]]