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README.md
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README.md
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[![License](https://img.shields.io/github/license/analysiscenter/pydens.svg)](https://www.apache.org/licenses/LICENSE-2.0)
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[![Python](https://img.shields.io/badge/python-3.8-blue.svg)](https://python.org)
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[![Documentation Status](https://readthedocs.org/projects/idrlnet/badge/?version=latest)](https://idrlnet.readthedocs.io/en/latest/?badge=latest)
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# IDRLnet
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[![License](https://img.shields.io/github/license/analysiscenter/pydens.svg)](https://www.apache.org/licenses/LICENSE-2.0)
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[![Python](https://img.shields.io/badge/python-3.7/3.8/3.9-blue.svg)](https://python.org)
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[![Documentation Status](https://readthedocs.org/projects/idrlnet/badge/?version=latest)](https://idrlnet.readthedocs.io/en/latest/?badge=latest)
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[![PyPI version](https://badge.fury.io/py/idrlnet.svg)](https://badge.fury.io/py/idrlnet)
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[![DockerHub](https://img.shields.io/docker/pulls/idrl/idrlnet.svg)](https://hub.docker.com/r/idrl/idrlnet)
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[![CodeFactor](https://www.codefactor.io/repository/github/idrl-lab/idrlnet/badge/master)](https://www.codefactor.io/repository/github/idrl-lab/idrlnet/overview/master)
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**IDRLnet** is a machine learning library on top of [PyTorch](https://pytorch.org/). Use IDRLnet if you need a machine
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learning library that solves both forward and inverse differential equations via physics-informed neural
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networks (PINN). IDRLnet is a flexible framework inspired by [Nvidia Simnet](https://developer.nvidia.com/simnet>).
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## Docs
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- [Full docs](https://idrlnet.readthedocs.io/en/latest/)
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- [Tutorial](https://idrlnet.readthedocs.io/en/latest/user/get_started/tutorial.html)
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## Installation
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Choose one of the following installation methods.
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```bash
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docker pull idrl/idrlnet:latest
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docker run idrl/idrlnet:latest
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```
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### Anaconda
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```bash
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conda create -n idrlnet_dev python=3.8 -y
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conda activate idrlnet_dev
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pip install idrlnet
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```
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### From Source
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@ -12,8 +12,8 @@ Welcome to idrlnet's documentation!
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Features
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--------
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IDRLnet is a machine learning library on top of `Pytorch <https://www.tensorflow.org/>`_. Use IDRLnet if you need a machine
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learning library that solves both forward and inverse partial differential equations (PDEs) via physics-informed neural
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IDRLnet is a machine learning library on top of `PyTorch <https://pytorch.org/>`_. Use IDRLnet if you need a machine
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learning library that solves both forward and inverse differential equations via physics-informed neural
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networks (PINN). IDRLnet is a flexible framework inspired by `Nvidia Simnet <https://developer.nvidia.com/simnet>`_.
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IDRLnet supports
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We recommend using conda to manage the environment.
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Other methods may also work well such like using docker or virtual env.
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Choose one of the following installation methods.
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## PyPI
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Simple installation from PyPI
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```bash
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pip install -U idrlnet
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```
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Note: To avoid version conflicts, please use some tools to create a virtual environment first.
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## Docker
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```bash
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docker pull idrl/idrlnet:latest
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docker run idrl/idrlnet:latest
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```
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## Anaconda
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```bash
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git clone https://git.idrl.site/pengwei/idrlnet
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cd idrlnet
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conda create -n idrlnet_dev python=3.8 -y
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conda activate idrlnet_dev
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pip install -r requirements.txt
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pip install idrlnet
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```
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## From Source
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```
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git clone https://github.com/idrl-lab/idrlnet
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cd idrlnet
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pip install -e .
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```
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@ -17,5 +17,5 @@ sympy==1.5.1
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pyevtk==1.1.1
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flask==1.1.2
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requests==2.25.0
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torch==1.7.1
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torch>=1.7.1
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networkx==2.5.1
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