ptrblck how I improve this code in order to find a good result at 50 iterations?
class Net(nn.Module):
    def __init__(self):
        super(Net,self).__init__()
        

        self.cnn1 = nn.Conv2d(in_channels=1, out_channels=8, kernel_size=3,stride=1, padding=1)
        self.batchnorm1 = nn.BatchNorm2d(8)        #Batch normalization
        self.relu = nn.ReLU()                 #RELU Activation
        self.maxpool1 = nn.MaxPool2d(kernel_size=2)   
      
        self.cnn2 = nn.Conv2d(in_channels=8, out_channels=10, kernel_size=5, stride=1, padding=2)
        self.batchnorm2 = nn.BatchNorm2d(10)
        self.relu = nn.ReLU() 
        self.maxpool2 = nn.MaxPool2d(kernel_size=2) 
        
        self.cnn3 = nn.Conv2d(in_channels=10, out_channels=32, kernel_size=5, stride=1, padding=2)
        self.batchnorm3 = nn.BatchNorm2d(32)
        self.relu = nn.ReLU() 
        #self.maxpool3 = nn.MaxPool2d(kernel_size=2) 
        
       
         
        
        self.fc1 = nn.Linear(in_features=32, out_features=20)   
       
        self.fc2 = nn.Linear(in_features=20, out_features=10)
       
        self.fc3 = nn.Linear(in_features=10, out_features=2)
       
      
       
        
    def forward(self,x):
        out = self.cnn1(x)
        out = self.batchnorm1(out)
        out = self.relu(out)
        out = self.maxpool1(out)
        out = self.cnn2(out)
        out = self.batchnorm2(out)
        out = self.relu(out)
        out = self.maxpool2(out)
        out = self.cnn3(out)
        out = self.batchnorm3(out)
        out = self.relu(out)
        #out = self.maxpool3(out)
        #out = self.maxpool3(out)
        #Flattening is done here with .view() -> (batch_size, 32*16*16) = (100, 8192)
        out = out.view(out.size(0),-1)  
       
        out = self.fc1(out)
        out = self.relu(out)
        out = self.fc2(out)
        out = self.relu(out)
        out = self.fc3(out)
        out = self.relu(out)
       
        return out

plz help me thanks