Metadata-Version: 1.1
Name: ikkuna
Version: 0.1.0
Summary: Ikkuna Neural Network Monitor
Home-page: https://peltarion.github.io/ai_ikkuna/
Author: Rasmus Diederichsen
Author-email: rasmus@peltarion.com
License: UNKNOWN
Description: <p align="center">
        <img src="./logo.png" alt="logo" width="100"/>
        </p>
        
        # Ikkuna
        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 setup.py develop` which will install the package
        with symlinks to this repository. Since all subscribers are `setuptools` plugins, they are
        not available unless `setup.py` is run.
        
        ## Documentation
        The sphinx-generated html documentation is hosted [here](https://peltarion.github.io/ai_ikkuna/).
        
        ## Working with the repository/notebooks
        1. Clone the repository.
        1. `cd` into the repository.
        1. Tell git where to find the configuration information for the iPython Notebooks with this command: `git config --add include.path $(pwd)/.gitconfig` (The path needs to point to your root git repository where the `.gitconfig` is stored).
        
        ### Adding a new notebook
        1. Create a new Jupyter Notebook.
        1. Hit `Edit -> Edit Notebook Metadata`.
        1. Add `"git": { "suppress_outputs": true },` as a top level element to the json metadata. This will be a notification to the git filter that we want to strip the metadata.
        
Keywords: deep-learning,pytorch,neural-networks,machine-learning
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Scientific/Engineering :: Visualization
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
Classifier: Programming Language :: Python :: 3.6
Classifier: License :: OSI Approved :: MIT License
Classifier: Intended Audience :: Developers
