mgm79 / modulus-sym

An abstracted framework for training AI surrogates of physical systems using physics-based symbolic loss functions

Modulus Symbolic (Beta)

Modulus Symbolic (Modulus Sym) provides an abstraction layer for using PDE-based symbolic loss functions. Additional information can be found in the Modulus documentation. Users of Modulus versions older than 23.05 can refer to the migration guide for updating to the latest version.

Modulus Packages

• Modulus (Beta)
• Modulus Launch (Beta)
• Modulus Symbolic (Beta)
• Modulus Tool-Chain (Beta)

Installation

PyPi

The recommended method for installing the latest version of Modulus Symbolic is using PyPi:

pip install nvidia-modulus.sym

Note, the above method only works for x86/amd64 based architectures. For installing Modulus Sym on Arm based systems using pip, Install VTK from source as shown here and then install Modulus-Sym and other dependencies

pip install nvidia-modulus.sym --no-deps
pip install "hydra-core>=1.2.0" "termcolor>=2.1.1" "chaospy>=4.3.7" "Cython==0.29.28" "numpy-stl==2.16.3" "opencv-python==4.5.5.64" \
    "scikit-learn==1.0.2" "symengine>=0.10.0" "sympy==1.5.1" "timm==0.5.4" "torch-optimizer==0.3.0" "transforms3d==0.3.1" \
    "typing==3.7.4.3" "pillow==9.3.0" "notebook==6.4.12" "mistune==2.0.3" "pint==0.19.2" "tensorboard>=2.8.0"

Container

The recommended Modulus docker image can be pulled from the NVIDIA Container Registry:

docker pull nvcr.io/nvidia/modulus/modulus:23.09

From Source

Package

For a local build of the Modulus Symbolic Python package from source use:

git clone [e-mail]:NVIDIA/modulus-sym.git && cd modulus-sym

pip install --upgrade pip
pip install .

Source Container

To build release image, you will need to do the below preliminary steps:

Clone this repo, and download the Optix SDK from https://developer.nvidia.com/designworks/optix/downloads/legacy.

git clone https://github.com/NVIDIA/modulus-sym.git
cd modulus-sym/ && mkdir deps

Currently Modulus supports v7.0. Place the Optix file in the deps directory and make it executable. Also clone the pysdf library in the deps folder (NVIDIA Internal)

chmod +x deps/NVIDIA-OptiX-SDK-7.0.0-linux64.sh 
git clone <internal pysdf repo>

Then to build the image, insert next tag and run below:

docker build -t modulus-sym:deploy \
    --build-arg TARGETPLATFORM=linux/amd64 --target deploy -f Dockerfile .

Alternatively, if you want to skip pysdf installation, you can run the following:

docker build -t modulus-sym:deploy \
    --build-arg TARGETPLATFORM=linux/amd64 --target no-pysdf -f Dockerfile .

Currently only linux/amd64 and linux/arm64 platforms are supported.

Contributing

For guidance on making a contribution to Modulus, see the contributing guidelines.

Communication

• Github Discussions: Discuss architectures, implementations, Physics-ML research, etc.
• GitHub Issues: Bug reports, feature requests, install issues, etc.
• Modulus Forum: The Modulus Forum hosts an audience of new to moderate level users and developers for general chat, online discussions, collaboration, etc.

License

Modulus Symbolic is provided under the Apache License 2.0, please see LICENSE.txt for full license text.