v2025.2.0

Major Updates

• Documentation has been significantly updated.
• Rollouts on ERA5 and GFS have been significantly streamlined.
• Physics constraints as postblocks have been added.
• Vertical interpolation to pressure and height levels.
• Experimental ensemble capabilities.
• Many bug fixes and code cleanups.

What's Changed

• Addition of new multi-step dataset that allows batch size > 1 by @jsschreck in #135
• Multistep training with batch_size >=1 per GPU by @jsschreck in #139
• Fix train/valid split read in dataset by @kanz76 in #140
• Gradscaler for grap clipping fix by @kanz76 in #141
• Major update for the inference routine + QoL improvements by @yingkaisha in #134
• Added valid_forecast_len to the result_dict by @kanz76 in #143
• Refactored validate method in trainerERA5_multistep_grad_acum.py for new dataset by @kanz76 in #145
• Minor bugfix on credit.parser by @yingkaisha in #144
• Bug fix on the original multi-step dataset by @jsschreck in #146
• Minor bugfix on credit.data by @yingkaisha in #147
• bugfix: removed deprecated ERA5Dataset and Bridgescaler_dataset from train.py by @dkimpara in #148
• Ensemble capability by @dkimpara in #137
• Predict scripts support batch size >= 1 by @jsschreck in #142
• rollouts enabled for ensemble, cftime, skebs. train_universal enabled for partial model loading. debugger model for dev support by @dkimpara in #149
• Updates to grad clipping, seed, and checkpointing by @jsschreck in #152
• CREDIT physcis for hybrid simga-pressure level configurations by @yingkaisha in #129
• Fixed trainer classes to actually use DDP by @kanz76 in #153
• Added std to printer log when using ensemble > 1 by @jsschreck in #154
• Docs, requirements, and some code formatting by @djgagne in #155
• Fix rollou_*_batcher.py by @kanz76 in #156
• Fixed varnum_diag bug by @kanz76 in #159
• FSDP to regular model or model weights by @jsschreck in #157
• Fixes to interpolation to pressure levels by @djgagne in #158
• Small fixes so option none works on casper using python and not torchrun by @jsschreck in #161
• Cleaning up saving + multiprocessing in rollout_to_netcdf.py script by @jsschreck in #162
• Updating packaging support by @djgagne in #163
• Documentation improvement of example-v2025.2.0.yml by @yingkaisha in #164
• Renaming scripts by @jsschreck in #165
• Updates to data loader and solar by @djgagne in #169
• Add regridding tools + minor bugfix on the inference dataset by @yingkaisha in #166
• Updating config/ by @jsschreck in #167
• Pulled out garbage collection from rollout_metrics by @jsschreck in #172
• Fix unit testing and removed garbage collection by @djgagne in #171
• Documentation updates by @djgagne in #170
• configuration explaination to READtheDocs by @WillyChap in #168
• Detached and re-assigned y_pred to discard computational graph by @kanz76 in #174
• Small temporary update to pbs.py to fix newer cudnn settings on Derecho by @jsschreck in #175
• Realtime Rollout and Predict + Interpolation Updates by @djgagne in #176
• rollout bugfix + documentation by @yingkaisha in #177
• Camulator v01.00 by @WillyChap in #179
• bunch of small fixes, features, comments by @dkimpara in #180
• Updates to bred vector implementation and noisy WXFormer by @jsschreck in #178
• GFS initial conditions by @charlie-becker in #173
• documentation updates by @ggantos in #183
• Skebs v 1.0 by @dkimpara in #182
• Trainer documentation by @jsschreck in #181
• Parallel version of CRPS by @jsschreck in #186
• Documentation hackathon by @djgagne in #184

New Contributors

• @charlie-becker made their first contribution in #173
• @ggantos made their first contribution in #183

Full Changelog: v2024.1.0...v2025.2.0