Merge pull request #4 from zweien/dev

Update github actions for pypi, docker.

.github/workflows/docker.yml

@@ -2,10 +2,11 @@ name: docker-build-push
 
 on:
   push:
+    branches: [master]
   pull_request:
     branches: [master]
   release:
-    types: [published, created, edited]
+    types: [published, edited]
 
 
 jobs:
@@ -25,15 +26,8 @@ jobs:
           username: ${{ secrets.DOCKERHUB_USERNAME }}
           password: ${{ secrets.DOCKERHUB_TOKEN }}
       -
-        name: Build and push
-        id: docker_build
-        uses: docker/build-push-action@v2
-        with:
-          push: true
-          tags: ${{ secrets.DOCKERHUB_USERNAME }}/idrlnet:latest
-      -
-        name: Image digest
-        run: echo ${{ steps.docker_build.outputs.digest }}
+        name: Print event_name
+        run: echo "$GITHUB_EVENT_NAME, ${{ github.event_name }}, ${{ github.event.release.tag_name }}"
 
       -
         name: Get release version
@@ -48,3 +42,4 @@ jobs:
         with:
           push: true
           tags: ${{ secrets.DOCKERHUB_USERNAME }}/idrlnet:${{ steps.get_version.outputs.RELEASE_VERSION }}
+          file: Dockerfile

.github/workflows/pypi.yml

@@ -0,0 +1,40 @@
+# This workflow will install Python dependencies, run tests and lint with a variety of Python versions
+# For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions
+
+name: Publish to PyPI
+on:
+  release:
+    types: [published, edited]
+
+jobs:
+  build:
+
+    runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: [3.7]
+
+    steps:
+    - uses: actions/checkout@v2
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v2
+      with:
+        python-version: ${{ matrix.python-version }}
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        python -m pip install setuptools wheel twine
+    
+    - name: Publish to PyPI
+      env:
+        TWINE_USERNAME: ${{ secrets.PYPI_USERNAME }}
+        TWINE_PASSWORD: ${{ secrets.PYPI_PASSWORD }}
+      run: |
+        python setup.py sdist bdist_wheel
+        twine upload --repository-url dist/*
+      
+    - name: Install from PyPI
+      run: |
+        pip install -U idrlnet
+        pip show idrlnet

.github/workflows/python-package.yml

@@ -35,4 +35,4 @@ jobs:
         flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
     - name: Test with pytest
       run: |
-        python examples/simple_poisson/simple_poisson.py 
+        python examples/simple_poisson/simple_poisson.py 

README.md

@@ -2,33 +2,45 @@
 [![Python](https://img.shields.io/badge/python-3.8-blue.svg)](https://python.org)
 [![Documentation Status](https://readthedocs.org/projects/idrlnet/badge/?version=latest)](https://idrlnet.readthedocs.io/en/latest/?badge=latest)
 
+# IDRLnet
+
+
+**IDRLnet** is a machine learning library on top of [PyTorch](https://pytorch.org/). Use IDRLnet if you need a machine
+learning library that solves both forward and inverse differential equations via physics-informed neural
+networks (PINN). IDRLnet is a flexible framework inspired by [Nvidia Simnet](https://developer.nvidia.com/simnet>).
+
 ## Installation
 
+Choose one of the following installation methods.
+
+### PyPI
+
+Simple installation from PyPI
+
+```bash
+pip install -U idrlnet
+```
+
+Note: To avoid version conflicts, please use some tools to create a virtual environment first.
+
 ### Docker
 
 ```bash
-git clone https://github.com/idrl-lab/idrlnet
-cd idrlnet
-docker build . -t idrlnet_dev
-docker run -it -p [EXPOSED_SSH_PORT]:22 -v [CURRENT_WORK_DIR]:/root/pinnnet idrlnet_dev:latest bash
+docker pull idrl/idrlnet:latest
 ```
 
 ### Anaconda
 
-```bash
+
+
+### From Source
+
+```
 git clone https://github.com/idrl-lab/idrlnet
 cd idrlnet
-conda create -n idrlnet_dev python=3.8 -y
-conda activate idrlnet_dev
-pip install -r requirements.txt
 pip install -e .
 ```
 
-# IDRLnet
-
-IDRLnet is a machine learning library on top of [Pytorch](https://www.tensorflow.org/). Use IDRLnet if you need a machine
-learning library that solves both forward and inverse partial differential equations (PDEs) via physics-informed neural
-networks (PINN). IDRLnet is a flexible framework inspired by [Nvidia Simnet](https://developer.nvidia.com/simnet>).
 
 ## Features
 
@@ -81,3 +93,16 @@ First off, thanks for taking the time to contribute!
 
 IDRLnet was originally developed by IDRL lab.
 
+## Citation
+Feel free to cite this library.
+
+```bibtex
+@article{peng2021idrlnet,
+      title={IDRLnet: A Physics-Informed Neural Network Library}, 
+      author={Wei Peng and Jun Zhang and Weien Zhou and Xiaoyu Zhao and Wen Yao and Xiaoqian Chen},
+      year={2021},
+      eprint={2107.04320},
+      archivePrefix={arXiv},
+      primaryClass={cs.LG}
+}
+```