Automated Neural-graph Toolkit: A Tensorflow wrapper for common deep learning tasks and rapid development of innovativemodels. Developed at Hutch Research, Western Washington University.Support for multiple input and output neural network graphs. Model visualizations and extensively documented interface. Explore tensorflow functionality and deep learning fundamentals.
Project description
Purpose
Automated Neural Graph Toolkit is an extension library for Google’s Tensorflow. It is designed to facilitate rapid prototyping of Neural Network models which may consist of multiple models chained together. Multiple input streams and and or multiple output predictions are well supported.
Documentation for ANTk
You will find complete documentation for ANTk at the ANTk readthedocs page.
Platform
ANTk is compatible with linux 64 bit operating systems.
Python Distribution
ANTk is written in python 2. Most functionality should be forwards compatible.
Install
A virtual environment is recommended for installation. Make sure that tensorflow is installed in your virtual environment and graphviz is installed on your system.
From the terminal:
(venv)$ pip install antk
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