hepynet 0.4.0

High energy physics, python based, neural network framework

Hepynet

High energy physics, python-based, neural-network assistant framework

Introduction

Goal of the hepynet: perform DNN related high energy physics analysis tasks with simple config files

• for ATLAS Analysis: include supports for various ATLAS analysis jobs

• Config Driven: all tasks defined by a simple config file

• Python Based: codes are written in Python, which is the mainstream language for DNN studies

Installation

pip install hepynet

GPU support

• You can refer to Tensorflow GPU support to set up environment to use GPU for training

• This is not mandatory, CPU alone is enough to run hepynet

Set Up the Workspace

Please refer to hepynet_workspace to see how to set up workspace of hepynet.

Release Note - v0.4.0

• This is the first public release, totally re-written to simplify the workflow and optimize the memory usage.

• Part of the utilities (Bayesian optimization, k-fold training ... ) are disabled to reduce the test/debug work load, will be added back in the coming releases.