encoding a neural network in a json file

Question

i am building a federated learning model, i would need to json encode my model so that i can exchange it with new workers i add to the network.

could you help me? is it possible to encode a model in a json file so that it can be sent?

below i put my net class i tried with the class methods but of course i get the error: object not serialisable in json.

thanks for your help

class net(nn.Module):
    def __init__(self):
      super( net, self).__init__()
      self.c1 = nn.Conv2d(3, 32, 3)
      self.b1 = nn.BatchNorm2d(32)
      self.c2 = nn.Conv2d(32, 64, 3)
      self.p1 = nn.MaxPool2d(2, 2)
      self.c3 = nn.Conv2d(64, 128, 3)
      self.d1 = nn.Dropout(0.5)
      self.c4 = nn.Conv2d(128, 256, 5)
      self.p2 = nn.MaxPool2d(2, 2)
      self.c5 = nn.Conv2d(256, 128, 3)
      self.p3 = nn.MaxPool2d(2, 2)
      self.d2 = nn.Dropout(0.2)
      self.l1 = nn.Linear(29*29*128, 128)
      self.l2 = nn.Linear(128, 32)
      self.l3 = nn.Linear(32 , 10)

      self.weights_initialization()

    def forward(self, x):
      x = F.relu(self.c1(x))
      x = self.b1(x)
      x = F.relu(self.c2(x))
      x = self.p1(x)
      x = F.relu(self.c3(x))
      x = self.d1(x)
      x = F.relu(self.c4(x))
      x = self.p2(x)
      x = F.relu(self.c5(x))
      x = self.p3(x)
      x = self.d2(x)
      x = x.view(x.size(0), -1)
      x = F.relu(self.l1(x))
      x = self.d2(x)
      x = F.relu(self.l2(x))
      x = self.l3(x)
    
    def forward(self, x):
        out = F.relu(self.fc1(x))
        out = F.relu(self.fc2(out))
        return self.output(out)
    
    
    def weights_initialization(self):
       
        for m in self.modules():
            if isinstance(m, nn.Linear):
                nn.init.xavier_normal_(m.weight)
                nn.init.constant_(m.bias, 0)


model = net()

I have tried the classical methods but have not succeeded in any way in doing this encoding. I currently have no idea how to do this, can you help me?