v0.5.0

Modulus (core) general release v0.5.0

Added

• Distributed process group configuration mechanism.
• DistributedManager utility to instantiate process groups based on a process group config.
• Helper functions to facilitate distributed training with shared parameters.
• Brain anomaly detection example.
• Updated Frechet Inception Distance to use Wasserstein 2-norm with improved stability.
• Molecular Dynamics example.
• Improved usage of GraphPartition, added more flexible ways of defining a partitioned graph.
• Physics-Informed Stokes Flow example.

Changed

• MLFLow logging such that only proc 0 logs to MLFlow.
• FNO given separate methods for constructing lift and spectral encoder layers.

Removed

• The experimental SFNO

Dependencies

• Removed experimental SFNO dependencies
• Added CorrDiff dependencies (cftime, einops, pyspng)
• Made tqdm a required dependency

v0.4.0

Modulus (core) general release v0.4.0

Added

• Added Stokes flow dataset
• An experimental version of SFNO to be used in unified training recipe for weather models.
• Added distributed FFT utility.
• Added ruff as a linting tool.
• Ported utilities from Modulus Launch to main package.
• EDM diffusion models and recipes for training and sampling.
• NGC model registry download integration into package/filesystem.
• Added distributed process group configuration mechanism.
• Added DistributedManager utility to instantiate process groups based on thier process group config.

Changed

• The AFNO input argument img_size to inp_shape.
• Integrated the network architecture layers from Modulus-Sym.

Fixed

• Fixed modulus.Module from_checkpoint to work from custom model classes.

Security

• Updated the base container to PyTorch 23.10.

v0.3.0

Modulus (core) general release v0.3.0

Added

• Added distributed utilities to create process groups and orthogonal process groups
• Added distributed AFNO model implementation
• Added distributed utilities for communication of buffers of varying size per rank
• Added instructions for docker build on ARM architecture
• Added batching support and fix the input time step for the DLWP wrapper
• Improved model checkpointing functionality with new '.mdlus' file type

Changed

• Updating file system cache location to modulus folder

Fixed

• Fixed modulus uninstall in CI docker image

Security

• Handle the tar ball extracts in a safer way.

Dependencies

• Updated the base container to latest PyTorch 23.07
• Update DGL version
• Updated require installs for python wheel
• Added optional dependency list for python wheel

v0.2.1

Modulus (core) hotfix release v0.2.1

Fixed

• Added a workaround fix for the CUDA graphs error in multi-node runs

Security

• Update certifi package version

v0.2.0

Modulus (core) general release v0.2.0

Added

• Added a CHANGELOG.md
• Added build support for internal DGL
• 4D Fourier Neural Operator model
• Ahmed body dataset

Changed

• DGL install changed from pypi to source
• Updated SFNO to add support for super resolution, flexible checkpoining, etc.

Fixed

• Fixed issue with torch-harmonics version locking
• Fixed the Modulus editable install
• Fixed AMP bug in static capture

Security

• Fixed security issues with subprocess and urllib in filesystem.py

Dependencies

• Updated the base container to latest PyTorch base container which is based on torch 2.0
• Container now supports CUDA 12, Python 3.10

v0.1.0

Modulus (core) general release v0.1.0

(Initial OSS release)