The problem of gtsrb dataset

[ain-soph]

The problem of gtsrb dataset

[rahulxie]

yes, it solved. Thank you!

[ain-soph]

That means your dataset element is PIL.Image rather than torch.Tensor, (99% because dataset transform is None rather than PILToTensor), which is unexpected.

---

Update: This seems to because of transform=None

trojanzoo/trojanzoo/datasets.py

Lines 449 to 450 in 51d728b

	dataset = self.get_dataset('train', transform=None)
	_, targets = dataset_to_tensor(dataset)

[ain-soph]

Would you mind reviewing the PR #150 ?
I haven't checked if it works yet, but I believe that shall solve the issue.

[rahulxie]

It works, but a new problem occur:
Traceback (most recent call last):
File "/home/itl/Documents/xrh/backdoor/trojanzoo/examples/train.py", line 36, in
model._train(**trainer)
File "/home/itl/Documents/xrh/backdoor/trojanzoo/examples/../trojanvision/models/imagemodel.py", line 560, in _train
return super()._train(epochs=epochs, optimizer=optimizer, lr_scheduler=lr_scheduler,
File "/home/itl/Documents/xrh/backdoor/trojanzoo/examples/../trojanzoo/models.py", line 1015, in _train
return train(module=self._model, num_classes=self.num_classes,
File "/home/itl/Documents/xrh/backdoor/trojanzoo/examples/../trojanzoo/utils/train.py", line 63, in train
best_validate_result = validate_fn(loader=loader_valid, get_data_fn=get_data_fn,
File "/home/itl/Documents/xrh/backdoor/trojanzoo/examples/../trojanvision/models/imagemodel.py", line 481, in _validate
return super()._validate(**kwargs)
File "/home/itl/Documents/xrh/backdoor/trojanzoo/examples/../trojanzoo/models.py", line 1056, in _validate
return validate(module=module, num_classes=num_classes, loader=loader,
File "/home/itl/Documents/xrh/backdoor/trojanzoo/examples/../trojanzoo/utils/train.py", line 246, in validate
loss = float(loss_fn(_input, _label, _output=_output, **kwargs))
File "/home/itl/Documents/xrh/backdoor/trojanzoo/examples/../trojanzoo/models.py", line 660, in loss
return criterion(_output, _label)
File "/home/itl/anaconda3/envs/trojanzoo/lib/python3.10/site-packages/torch/nn/modules/module.py", line 1110, in _call_impl
return forward_call(*input, **kwargs)
File "/home/itl/anaconda3/envs/trojanzoo/lib/python3.10/site-packages/torch/nn/modules/loss.py", line 1163, in forward
return F.cross_entropy(input, target, weight=self.weight,
File "/home/itl/anaconda3/envs/trojanzoo/lib/python3.10/site-packages/torch/nn/functional.py", line 2996, in cross_entropy
return torch._C._nn.cross_entropy_loss(input, target, weight, _Reduction.get_enum(reduction), ignore_index, label_smoothing)
RuntimeError: expected scalar type Float but found Long

[ain-soph]

That doesn't seem to be an obvious issue. Let me debug actually.

[ain-soph]

Thanks for finding the bug! Does the previous PR solve your issue?

[rahulxie]

But the loss is nan.

[ain-soph]

remove your previously saved loss_weights.npy and regenerate one. It's saved at your dataset folder

[ain-soph]

Does it work? @rahulxie

[rahulxie]

Does it work? @rahulxie

yes, it works! Thanks!

[rahulxie]

I want to konw what kinds of models used to train gtsrb dataset. Is resnet18_comp ok with the same config of cifar10 (i.e., the "Quick Start" of "Train a model" in README.md) ?

[ain-soph]

Yes, I think I use resnet18_comp in IMC paper.

You may add my WeChat?

ain-soph-aur

[rahulxie]

ain-soph-aur

okok, I have send friend request.