Skip to main content

NeuroFade

Live Forgetting Visualizer — see your neural network forget in real time.

Example

What

Tracks per-neuron activation retention across training tasks and renders the forgetting process as animated heatmaps. Watch your model lose knowledge in real time.

Install

pip install neurofade

Quick Start

from neurofade import ForgettingVisualizer

viz = ForgettingVisualizer(model, baseline_task=train_task_1_loader)

# Wraps your training loop
with viz.watch():
    trainer.fit(task_2_loader)

viz.export("forgetting.mp4")
viz.share()  # Upload to public URL

Why

Catastrophic forgetting is invisible until it tanks your model. NeuroFade makes it undeniable.

  • Layers fade in real-time — see which neurons die first
  • Export as GIF/MP4 — shareable artifacts
  • Per-task baselines — measures retention against any previous task
  • Framework-agnostic — works with PyTorch, TensorFlow, JAX

The Vibe

Your model is dying. Now you can see it.

Release files for neurofade 0.1.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for neurofade 0.1.0
File Size Uploaded
neurofade-0.1.0.tar.gz 5.7 kB Details

Built distribution (wheel)

Table of built distributions (wheels) for neurofade 0.1.0
File Interpreter ABI Platform
neurofade-0.1.0-py3-none-any.whl Python 3 none any Details

Total release size: 11.9 kB

Release files / neurofade-0.1.0.tar.gz

Download URL neurofade-0.1.0.tar.gz
Size 5.7 kB
Tags Source
SHA-256 checksum
How to use checksums
a71ef66185698507d8da850c99b34f6faad00cc1955a60bfb36d11c8fc3d98f9
BLAKE2b-256 checksum
How to use checksums
5903ddeaa97a94d2460db9af50ba5c71c510750cd47b7e0d011d4a649e365668
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.3

Release files / neurofade-0.1.0-py3-none-any.whl

Download URL neurofade-0.1.0-py3-none-any.whl
Size 6.2 kB
Tags Python 3
SHA-256 checksum
How to use checksums
f4083297b544eb48c135cc7dd5a4ba18762a8fbf4b011bad60d95a48306e1f9c
BLAKE2b-256 checksum
How to use checksums
1bfdf04845adf3085831496d8165112505ad2b3ead7fab1b0c36cd027729ee03
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.3

Release history Release notifications | RSS feed

This release

0.1.0 This release

2 release files

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page