mxnet基础到提高(37)-自定义前向操作

from mxnet import nd
from mxnet.gluon import nn

class MixMLP(nn.Block):
    def __init__(self, **kwargs):
        # Run `nn.Block`'s init method
        super(MixMLP, self).__init__(**kwargs)
        self.blk = nn.Sequential()
    def forward(self, x):
        y = nd.relu(self.blk(x))
        return y
net = MixMLP()
net.initialize()
x=nd.array([[-10,20],[20,-30]])
y=net(x)
print(y)

[[ 0. 20.]
[20. 0.]]
<NDArray 2x2 @cpu(0)>

下面计算 向量的模长

from mxnet import nd
from mxnet.gluon import nn
#code:liuxing
class computeNorm(nn.Block):
    def __init__(self, **kwargs):
        # Run `nn.Block`'s init method
        super(computeNorm, self).__init__(**kwargs)
        self.blk = nn.Sequential()
    def forward(self, x):
        y = nd.sqrt(nd.sum(nd.power(x,2),axis=1))
        return y
net = computeNorm()
net.initialize()
x=nd.array([[-10,20],[20,-30]])
y=net(x)
print(y)
x=nd.array([[-10,20,6],[20,-30,9]])
y=net(x)
print(y)

[22.36068 36.05551]
<NDArray 2 @cpu(0)>

[23.151674 37.161808]
<NDArray 2 @cpu(0)>