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High energy physics, python based, neural network framework

Project description

Hepynet

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

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Introduction

The 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 the 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_example to see how to set up the workspace of hepynet.

Release Note - v0.4.2

  • Re-implement auto-tuning functions with Ray (currently, support three hyperparameter-tuning algorithms: Ax, HyperOpt and HEBO)
  • Minor issues fixes and improvements

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