PyTorchDebugUtils

Capabilities :

1. Logging
2. Model Info
3. Model validation (Not to be confused with use of validation set, just performs an initial test of the model to make sure everything is working properly)
4. Visualization of Weight Distribution
5. Callbacks to Specific Layers
6. Loss and Metric Visualization
7. Comparisons - Loss, Metric , Hyperparameters
8. Visualizing Gradients
9. Memory Footprint - Time Elapsed, RAM, GPU
10. Model Checkpointing
11. Report Generation
12. Hyperparameter Optimization
13. Backend Service to Check Current Status of Experiments
14. Support For Configuration Files