Additional custom callbacks for Weights & Biases
Project description
Weights & Biases Callbacks
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
Sample Implementation
Can be found in notebooks/sample_implementation.ipynb
.
Project details
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
wandb-callbacks-0.2.0.tar.gz
(5.6 kB
view hashes)
Built Distribution
Close
Hashes for wandb_callbacks-0.2.0-py3-none-any.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | b7c7d21b4930da4ad615930403cef384faf7b05d867d30ba59b02a109a76d59f |
|
MD5 | 34a835f47abeb02c855ed2e8b8164fcc |
|
BLAKE2b-256 | a2271d6755ab54019be973e3b01e1c54d638b0fe8f87700c759ff83fd50c4b04 |