wandb-callbacks provides some additional Callbacks for Weights & Biases.
Callbacks currently implemented:
ActivationCallback- visualizes the activations of a layer
- activations are computed for a sample of each class
DeadReluCallback- logs the number of dead relus in each layer
- prints warning if the percentage is higher than a threshold
GradCAMCallback- Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization
- produces a coarse localization map highlighting the important regions in the image for predicting the class of the image
pip install wandb-callbacksgit clone https://github.com/FabianGroeger96/wandb-callbacksCan be found in notebooks/sample_implementation.ipynb.
Open to ideas and for helpers to develop the package further.
