Source for the paper "Universal Activation Function for machine learning"

Related tags

Deep Learning Universal_Activation_Function
Overview

Universal Activation Function

Tensorflow and Pytorch source code for the paper

Yuen, Brosnan, Minh Tu Hoang, Xiaodai Dong, and Tao Lu. "Universal activation function for machine learning." Scientific reports 11, no. 1 (2021): 1-11.

Getting the code

Requires Docker

Use git to pull this repo

git clone https://github.com/SensorOrgNet/Universal_Activation_Function.git

Running the Tensorflow 2 version

Install CUDA 11.2 container

docker run --name UAF --gpus all  -v /home/username/UAF/:/workspace  -w /workspace    -it  nvcr.io/nvidia/cuda:11.2.0-cudnn8-devel-ubuntu20.04   bash

Install python

apt update
apt install python3-pip

Install pytorch and pytorch geometric

pip3 install tensorflow==2.7.0

Run the MLP with UAF for MNIST dataset

cd   Universal_Activation_Function/tensorflow/
python3   ./mnist_UAF.py

Running the Pytorch version

Install CUDA 11.3 container

docker run --name UAF --gpus all  -v /home/username/UAF/:/workspace  -w /workspace    -it  nvcr.io/nvidia/cuda:11.3.0-cudnn8-devel-ubuntu20.04   bash

Install python

apt update
apt install python3-pip

Install pytorch and pytorch geometric

pip3 install torch==1.10.0+cu113 torchvision==0.11.1+cu113 torchaudio==0.10.0+cu113 -f https://download.pytorch.org/whl/cu113/torch_stable.html
pip3 install torch-scatter -f https://data.pyg.org/whl/torch-1.10.0+cu113.html
pip3 install torch-sparse -f https://data.pyg.org/whl/torch-1.10.0+cu113.html
pip3 install torch-cluster -f https://data.pyg.org/whl/torch-1.10.0+cu113.html
pip3 install torch-spline-conv -f https://data.pyg.org/whl/torch-1.10.0+cu113.html
pip3 install torch-geometric

Run the CNN with UAF for MNIST dataset

cd   Universal_Activation_Function/pytorch/
python3   ./mnist_UAF.py

Run the GCN2 with UAF for CORA dataset. The fold number is represented by the number at the end

cd   Universal_Activation_Function/pytorch/
python3   ./gcn2_cora_UAF.py  0

Run the PNA with UAF for ZNC dataset. The fold number is represented by the number at the end

cd   Universal_Activation_Function/pytorch/
python3   ./pna_UAF.py  0
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