| Name | Modified | Size | Downloads / Week |
|---|---|---|---|
| Parent folder | |||
| README.md | 2025-06-10 | 2.1 kB | |
| v1.1.0 source code.tar.gz | 2025-06-10 | 121.6 MB | |
| v1.1.0 source code.zip | 2025-06-10 | 122.7 MB | |
| Totals: 3 Items | 244.3 MB | 0 | |
PhysicsNeMo (Core) General Release v1.1.0
Added
- Added ReGen score-based data assimilation example
- General purpose patching API for patch-based diffusion
- New positional embedding selection strategy for CorrDiff SongUNet models
- Added Multi-Storage Client to allow checkpointing to/from Object Storage
Changed
- Simplified CorrDiff config files, updated default values
- Refactored CorrDiff losses and samplers to use the patching API
- Support for non-square images and patches in patch-based diffusion
- ERA5 download example updated to use current file format convention and restricts global statistics computation to the training set
- Support for training custom StormCast models and various other improvements for StormCast
- Updated CorrDiff training code to support multiple patch iterations to amortize
regression cost and usage of
torch.compile - Refactored
physicsnemo/models/diffusion/layers.pyto optimize data type casting workflow, avoiding unnecessary casting under autocast mode - Refactored Conv2d to enable fusion of conv2d with bias addition
- Refactored GroupNorm, UNetBlock, SongUNet, SongUNetPosEmbd to support usage of Apex GroupNorm, fusion of activation with GroupNorm, and AMP workflow.
- Updated SongUNetPosEmbd to avoid unnecessary HtoD Memcpy of
pos_embd - Updated
from_checkpointto accommodate conversion between Apex optimized ckp and non-optimized ckp - Refactored CorrDiff NVTX annotation workflow to be configurable
- Refactored
ResidualLossto support patch-accumlating training for amortizing regression costs - Explicit handling of Warp device for ball query and sdf
- Merged SongUNetPosLtEmb with SongUNetPosEmb, add support for batch>1
- Add lead time embedding support for
positional_embedding_selector. Enable
arbitrary positioning of probabilistic variables - Enable lead time aware regression without CE loss
- Bumped minimum PyTorch version from 2.0.0 to 2.4.0, to minimize
support surface for
physicsnemo.distributedfunctionality.
Dependencies
- Made
nvidia.dalian optional dependency