Comments (3)
yogeesh-alphaics
commented on August 11, 2024
hi ,
i am also facing the same issue. Please update as soon as possible.
from robustness.
ShibaniSanturkar
commented on August 11, 2024
Thanks for pointing this out. Our previous commit accidentally omitted the ImageNetHierarchy class. Should be fixed in #60 which will be merged with master later today.
from robustness.
andrewilyas
commented on August 11, 2024
Hi all,
Thanks for bringing up this issue! It's now fixed on the master branch and on PyPI. Feel free to re-open the issue if you encounter other issues!
from robustness.
Related Issues (20)
- Can't load 'densenet121" HOT 1
- Inquiry - running tensorboardx on store HOT 1
- Missing files for Customized ImageNet Subset. HOT 2
- Cannot load model CIFAR-10 - epsilon = 0.25 or 1.0 HOT 4
- Constant name for final feature layer for easier visualization
- How to customize the loss function
- Interpreting Top5 Accuracy
- Add validate every n epochs HOT 3
- torchvision-dependent code breaks for version `0.11.3+cu113` HOT 1
- import of `custom_modules` breaking with newer version of python/pytorch/torchvision
- The loss-aggregation for the attacker should be `sum` not `mean` HOT 3
- Pretrained imagenet_linf_16?
- ModuleNotFoundError: No module named 'robustness.model_utils'; 'robustness' is not a package HOT 4
- import robustness. dataset "No module named 'torchvision.models.utils'" HOT 2
- Architecture Types
- Robustness of ImageNet Linf-norm (ResNet50): HOT 2
- Preparing dataset takes too long..
- The Link to robust-models-transfer repo is down HOT 1
- How to use the pretrained model?
- No checkpoint found in the desired path. HOT 1
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from robustness.