Metadata-Version: 2.1
Name: fma-core
Version: 0.0.1
Summary: Federated Model Aggregation's Core Functionality
Home-page: https://github.com/capitalone/federated-model-aggregation
Author: Kenny Bean, Tyler Farnan, Taylor Turner, Michael Davis, Jeremy Goodsitt 
License: Apache License, Version 2.0
Keywords: Federated Learning
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Information Technology
Classifier: Intended Audience :: Science/Research
Classifier: Topic :: Education
Classifier: Topic :: Scientific/Engineering
Classifier: Topic :: Scientific/Engineering :: Information Analysis
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.8
Description-Content-Type: text/markdown
Requires-Dist: numpy (==1.22.2)

# FMA-Core

The FMA-Core component is a collection of building blocks use for agnostically building an FMA service. 
Algorithms and workflows are agnostic in the sense that users can build their own algorithms/workflows 
and use them in the FMA Service.

Quick start
-----------
For installation:

```console
pip install fma-core
```


Testing
-------

Inside a virtualenv:
```
make install
make test
```

For testing and coverage reports:
```
make test-and-coverage
```

## FMA-Algorithms

A sub-part of FMA-Core is FMA-Algorithms. 
This component is an agnostic implementation of the model aggregation function for the FMA service.

## FMA-Workflows

FMA-Workflow is the principal component of the service: gluing together the 
`aggregator`, `api`, `model`, and `metadata` connectors for the various parts of the service 
to communicate with each other. 
