TF-MELT

TF-MELT (TensorFlow Machine Learning Toolbox) is a collection of architectures, processing, and utilities that are transferable over a range of ML applications.

A toolbox for researchers to use for machine learning applications in the TensorFlow language. The goal of this software is to enable fast start-up of machine learning tasks and to provide a reliable and flexible framework for development and deployment. The toolbox contains generalized methods for every aspect of the machine learning workflow while simultaneously providing routines that can be tailored to specific application spaces.

Environment

First, create a new conda environment and activate:

conda create -n tf-melt python=3.11
conda activate tf-melt

Finally, install the tfmelt as a package through pip either through a local install from a git clone

Local git clone

If you cloned the repo and would like to install from the local git repo, navigate to the head directory where setup.py is located and type:

pip install .

If you want to update the pip install to make sure dependencies are current:

pip install --upgrade .

Directly from github

To install the tfmelt package directly from github simply type:

pip install git+https://github.com/NREL/tf-melt.git

Example Notebooks

If you want to run the example notebooks, they require a couple additional packages which can all be pip installed:

1. scikit-learn
2. ipykernel
3. matplotlib

Contributing

All code committed to the main branch of this repo should first pass through auto-formatters black and isort and should have all flake8 issues resolved. This is to prevent cluttering the commit history with formatting updates and to provide a consistent code format across implementations.

These tools can be installed with via pip:

pip install black isort flake8

Related repo

There is a parallel repo for implementation in PyTorch:

https://github.com/nrel/pt-melt