cnn.py

import mxnet as mx
from mxnet import nd, gluon, autograd
from mxnet.gluon import nn
import mxnet.ndarray as F

class Net(gluon.Block):
    def __init__(self, **kwargs):
        super(Net, self).__init__(**kwargs)
        with self.name_scope():
            
            self.cnn1 = nn.Conv2D(20,kernel_size=(4,4))
            self.mxp1 = nn.MaxPool2D((2,2))
            
            self.cnn2 = nn.Conv2D(25,kernel_size=(2,2))
            self.mxp2 = nn.MaxPool2D((2,2))
            
            self.cnn3 = nn.Conv2D(30,kernel_size=(2,2))
            self.mxp3 = nn.MaxPool2D((2,2))
            
            self.flat = nn.Flatten()
            
            self.fc = nn.Dense(128)
            self.out = nn.Dense(10)
            
    def forward(self,x):
        
        x = F.relu(self.mxp1(self.cnn1(x)))
        x = F.relu(self.mxp2(self.cnn2(x)))
        x = F.relu(self.mxp3(self.cnn3(x)))
        x = self.flat(x)
        x = F.relu(self.fc(x))
        x = self.out(x)
        
        return x
    
cnn = Net()
print(cnn)