siamese-network-training.py

net = SiameseNetwork().cuda()
criterion = ContrastiveLoss()
optimizer = optim.Adam(net.parameters(),lr = 0.0005 )

counter = []
loss_history = [] 
iteration_number= 0

for epoch in range(0,Config.train_number_epochs):
    for i, data in enumerate(train_dataloader,0):
        img0, img1 , label = data
        img0, img1 , label = Variable(img0).cuda(), Variable(img1).cuda() , Variable(label).cuda()
        output1,output2 = net(img0,img1)
        optimizer.zero_grad()
        loss_contrastive = criterion(output1,output2,label)
        loss_contrastive.backward()
        optimizer.step()
        if i %10 == 0 :
            print("Epoch number {}\n Current loss {}\n".format(epoch,loss_contrastive.data[0]))
            iteration_number +=10
            counter.append(iteration_number)
            loss_history.append(loss_contrastive.data[0])
show_plot(counter,loss_history)