Can anyone please help me resolve this error. about object-detection-using-cnn HOT 1 OPEN

for epoch in range(10):
    for i, data in enumerate(dataloader):
        optimizer.zero_grad()

        inputs, labels = data
        inputs, labels = inputs.view(batchSize, 1, 100, 100), labels.view(batchSize, 4)

        outputs = net(inputs)
        loss = criterion(outputs, labels)
        loss.backward()
        optimizer.step()

        pbox = outputs.detach().numpy()
        gbox = labels.detach().numpy()
        score, _ = overlapScore(pbox, gbox)

        print('[epoch %5d, step: %d, loss: %f, Average Score = %f' % (epoch+1, i+1, loss.item(), score/batchSize))

    scheduler.step()  # Move this line here to update learning rate after each epoch

print('Finish Training')

trainingdataset = training_dataset()
dataLoader = DataLoader(
    dataset=trainingdataset,
    batch_size=batch,
    shuffle=shuffle,
    num_workers=no_of_workers
)

model = cnn_model()
model.train()

optimizer = optim.SGD(model.parameters(), lr=learning_rate, momentum=momentum)
scheduler = optim.lr_scheduler.StepLR(optimizer, step_size=30, gamma=0.1)

train_model(model, dataLoader, batch, learning_rate, momentum, optimizer, scheduler)

# Ensure the directory exists before saving the model
model_directory = './Model/'
os.makedirs(model_directory, exist_ok=True)  # This line creates the directory if it does not exist

torch.save(model.state_dict(), os.path.join(model_directory, 'cnn_model.pth'))