FAQ & Troubleshooting
Limitations
1min
- Longer wait times (~6-8 hours) can be expected if multiple earlier jobs are running. Users can keep observing the status of the job by using the GET API or the Dashboard link.
- "Number of attack queries" parameter currently is limited to <=400000 for all tasks.
- "Number of classes" parameter should be <200 for all classification task type.
- When executing the reference implementation, it is recommended to install the per-requisite libraries with exact versions.
- The product currently supports Tensorflow version between 2.3.0 and 2.15.0.
- Tabular classification supports scikit-learn models with preferred version 1.4.0 and XGBoost model version 2.0.3.
- Image classification evasion defense might be less effective against very small perturbation.
- Image classification poisoning - Encryption strategy and use model api endpoint not supported. Also it requires two clean model and one test model.
- Tabular classification evasion analysis is only supported with a normalized dataset Between 0-1.
- The image should be in RGB format, and the model should be trained with images in this format.
- When the number of attack queries is low, such as 1000 or fewer, the system automatically generates them.
