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Perspic

A tool to study neural network training dynamics.

What is Perspic?

Perspic provides efficient computation and logging of the loss-network-position (LNP) decomposition. Each of the components helps us to understand how neural networks learn. It integrates seamlessly with PyTorch Lightning by wrapping existing code, adding the analysis.

Quick Start

from perspic import analyzer
from pytorch_lightning import Trainer

# Wrap your Lightning module class
model = analyzer(
    lightning_module=YourLightningModule, # class
    model=your_model,
    sample_wise_engine="opacus"
)

trainer = Trainer(...)
trainer.fit(model, train_dataloader, val_dataloader)

Installation

Note: Perspic is not yet published on PyPI. Install it locally with dependencies:

git clone https://github.com/zincware/perspic.git
cd perspic
python -m pip install .

Learning & Examples

Start with examples/README.md for comprehensive tutorials on core workflows, advanced features, and expert topics using CIFAR-10 and Vision Transformers.

Documentation

  • Examples — Jupyter notebooks demonstrating key features
  • Tests — Unit and integration tests

License

See LICENSE

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