Skip to main content

Ikkuna Neural Network Monitor

Project description



A tool for monitoring neural network training.

Ikkuna provides a framework for adding live training metrics to your PyTorch model with minimal configuration. It is a PubSub framework which allows practitioners to quickly test metrics implemented against a simple API. The following data is provided

  • Activations
  • Gradients w.r.t weights and biases
  • Gradients w.r.t layer outputs
  • Weights
  • Biases
  • Weight updates
  • Bias updates
  • Metadata such as current step in the training, current labels and current perdictions

Subscribers consume this data and distill it into metrics. Different backends can be used

  • Matplotlib
  • Tensorboard

Working with this repository

You should create a conda envorinment from the provided torch.yaml file and pip install -r the provided requirements.txt file. You will also have to install numba for building the documentation until I have the time to figure out how to optionally turn off parts of a doc build.

You should also run python develop which will install the package with symlinks to this repository. Since all subscribers are setuptools plugins, they are not available unless is run.


The sphinx-generated html documentation is hosted here.

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for ikkuna, version 0.1.0.post2
Filename, size File type Python version Upload date Hashes
Filename, size ikkuna-0.1.0.post2-py3-none-any.whl (53.6 kB) File type Wheel Python version py3 Upload date Hashes View
Filename, size ikkuna-0.1.0.post2.tar.gz (38.2 kB) File type Source Python version None Upload date Hashes View

Supported by

Pingdom Pingdom Monitoring Google Google Object Storage and Download Analytics Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN DigiCert DigiCert EV certificate StatusPage StatusPage Status page