TODO

・demonstrates how to combine different attack and defense algorithms with Attack_SplitNN.

Hello,First of all, thank you for sharing your relevant reproducing work, but I ran the code about FSHA, but why the result was so different from the original text under the same configuration? I also modified it, but the result was still so different from the original text

The current implementation of the FSHA attack is not compatible with AbstractAttacker.

So sorry to bother you. I have some questions.
In Shredder.ipynb, the class SplitNN is not the subclass of nn.Module, and also does not define the attribute of train. So why there is a code of splitnn.train() in first line of nineteenth block, aslo the questions is the same as splitnn.zero_grads(),splitnn.backward().
The code and the reason of fault is as following.
THX
`splitnn.train()
for epoch in range(3):
epoch_loss = 0
epoch_outputs = []
epoch_labels = []
for i, data in enumerate(victim_train_dataloader):
splitnn.zero_grads()
inputs, labels = data
inputs = inputs.to(device)
labels = labels.to(device)

    outputs = splitnn(inputs)
    loss = criterion(outputs, labels)
    loss.backward()
    epoch_loss += loss.item() / len(victim_train_dataloader.dataset)
    
    epoch_outputs.append(outputs)
    epoch_labels.append(labels)
    
    splitnn.backward()
    splitnn.step()
    
print(epoch_loss, accuracy(torch.cat(epoch_labels),
                            torch.cat(epoch_outputs)))`

`---->Shredder.ipynb#ch0000013vscode-remote?line=0) splitnn.train()
Shredder.ipynb#ch0000013vscode-remote?line=1) for epoch in range(3):
Shredder.ipynb#ch0000013vscode-remote?line=2) epoch_loss = 0

AttributeError: 'SplitNN' object has no attribute 'train'`

Attack_SplitNN currently only supports two-party SplitNN.

・We have to implement a more sophisticated SplitNN which supports multi-party.