v2.0.0

Major Changes

• SoloSeq inference: Single Sequence Inference using ESM-1b embeddings with template features is now supported. Check out SoloSeq in the README for more information.
• Multimer : Inference in multimer mode using the AlphaFold-Multimer weights is now supported. Check out Multimer in the README for more instructions, or try out multimer inference in the Colab notebook.
• Addition of a custom DeepSpeed DS4Sci_EvoformerAttention kernel for 13X reduced peak device memory requirement, leading to 15% faster training and 4x speedup during inference. Test it out using the use_deepspeed_evo_attention option in openfold/config.py. More information in the README.

All Changes

• add long_sequence_inference option to command line by @decarboxy in #253
• Fix for CPU only install by @p-durandin in #252
• Obsolete parsing and File not found fix by @l-bick in #264
• Load pretrained jax weights by @l-bick in #263
• Fix --cpus_per_task argument in README by @awaelchli in #278
• Add a .gitignore file by @awaelchli in #279
• Add missing warmup_num_steps parameters to DeepSpeed config generation script. by @jonathanking in #290
• Fix notebook: Colab now has python 3.8, fix imports, mitigate UTF-8 glitch by @vaclavhanzl in #285
• New option to output in ModelCIF format instead of PDB format by @josemduarte in #287
• Fix comparison for max_seqlen when downloading CAMEO. by @jonathanking in #292
• Resolving torch cuda availability for cpu-only installation by @zrqiao in #275
• Improve TriangularMultiplicativeUpdate stability in fp16 mode by @nikitos9000 in #295
• Advance python version to 3.9 to build docker in Ubuntu Lunar Lobster by @vaclavhanzl in #309
• add comment about the interpretation of ambiguous atoms by @luwei0917 in #314
• Fix Colab again after ModelCIF merge and python version change in Colab by @vaclavhanzl in #308
• Fix Colab: Install all conda packages together by @vaclavhanzl in #320
• Multimer by @dingquanyu in #331
• Added multi-chain permutation steps, multimer datamodule, and training code for multimer by @dingquanyu in #336
• Fix multimer boolean tensor error by @dingquanyu in #337
• Update multi-chain permutation by @dingquanyu in #343
• Update validation by @dingquanyu in #346
• Fixes cuda/float wrapper error in unit tests by @jnwei in #350
• Fixed inference script in multimer mode by @dingquanyu in #348
• Update multi-chain permutation and training codes by @dingquanyu in #353
• fixed the creation of best_align when permutation is turned off by @dingquanyu in #355
• Single-sequence model by @sachinkadyan7 in #354
• move the kabsch rotation step to gpu by @dingquanyu in #359
• Installation updates by @jnwei in #360
• [DNM] Update Docker config by @mattwthompson in #361
• Bump actions/checkout from 2 to 4 by @dependabot in #366
• Bump actions/setup-python from 2 to 4 by @dependabot in #365
• Fixes imports to colab notebook. by @jnwei in #372
• Adds Soloseq parameter download script. by @jnwei in #373
• Fix for MSA block deletion by @christinaflo in #374
• Adds query_multiple to jackhammer.py by @jnwei in #375
• Deepspeed evoformer attention by @christinaflo in #378
• Speed up data loading process by @dingquanyu in #376
• Update data pipeline by @dingquanyu in #385
• Bump actions/setup-python from 4 to 5 by @dependabot in #380
• Readme changes by @jnwei in #389
• suporting newer numpy by @YoelShoshan in #307
• Change test_compare_model in deepspeed test to use mean instead of max by @jnwei in #396
• Fix Miniforge3 download link in Dockerfile by @controny in #402
• Adding multimer support to OpenFold notebook by @jnwei in #401
• Type fixes and README changes for multimer branch by @jnwei in #404
• Full multimer merge by @christinaflo in #405

New Contributors

• @p-durandin made their first contribution in #252
• @l-bick made their first contribution in #264
• @awaelchli made their first contribution in #278
• @vaclavhanzl made their first contribution in #285
• @zrqiao made their first contribution in #275
• @luwei0917 made their first contribution in #314
• @dingquanyu made their first contribution in #331
• @jnwei made their first contribution in #350
• @mattwthompson made their first contribution in #361
• @dependabot made their first contribution in #366
• @christinaflo made their first contribution in #374
• @YoelShoshan made their first contribution in #307
• @controny made their first contribution in #402

Full Changelog: v1.0.1...v2.0.0

OpenFold v1.0.1

OpenFold as of the release of our manuscript. Many new features, including FP16 training + more stable training.

What's Changed

• use multiple models for inference by @decarboxy in #117
• Update input processing by @brianloyal in #116
• adding a caption to the image in the readme by @decarboxy in #133
• Properly handling file outputs when multiple models are evaluated by @decarboxy in #142
• Fix for issue in download_mgnify.sh by @josemduarte in #166
• Fix tag-sequence mismatch when predicting for multiple fastas by @sdvillal in #164
• Support openmm >= 7.6 by @sdvillal in #163
• Fixing issue in download_uniref90.sh by @josemduarte in #171
• Fix propagation of use_flash for offloaded inference by @epenning in #178
• Update deepspeed version to 0.5.10 by @NZ99 in #185
• Fixes errors when processing .pdb files by @NZ99 in #188
• fix incorrect learning rate warm-up after restarting from ckpt by @Zhang690683220 in #182
• Add opencontainers image-spec to Dockerfile by @SauravMaheshkar in #128
• Write inference and relaxation timings to a file by @brianloyal in #201
• Minor fixes in setup scripts by @timodonnell in #202
• Minor optimizations & fixes to support ESMFold by @nikitos9000 in #199
• Drop chains that are missing (structure) data in training by @timodonnell in #210
• adding a script for threading a sequence onto a structure by @decarboxy in #206
• Set pin_memory to True in default dataloader config. by @NZ99 in #212
• Fix missing subtract_plddt argument in prep_output call by @mhrmsn in #217
• fp16 fixes by @beiwang2003 in #222
• Set clamped vs unclamped FAPE for each sample in batch independently by @ar-nowaczynski in #223
• Fix probabilities type (int -> float) by @atgctg in #225
• Small fix for prep_mmseqs_dbs. by @jonathanking in #232

New Contributors

• @brianloyal made their first contribution in #116
• @josemduarte made their first contribution in #166
• @sdvillal made their first contribution in #164
• @epenning made their first contribution in #178
• @NZ99 made their first contribution in #185
• @Zhang690683220 made their first contribution in #182
• @SauravMaheshkar made their first contribution in #128
• @timodonnell made their first contribution in #202
• @nikitos9000 made their first contribution in #199
• @mhrmsn made their first contribution in #217
• @beiwang2003 made their first contribution in #222
• @ar-nowaczynski made their first contribution in #223
• @atgctg made their first contribution in #225
• @jonathanking made their first contribution in #232

Full Changelog: v1.0.0...v1.0.1

OpenFold v1.0.0

OpenFold at the time of the release of our original model parameters and training database. Adds countless improvements over the previous beta release, including, but not limited to:

• Many bugfixes contribute to stabler, more correct, and more versatile training
• Options to run OpenFold using our original weights
• Custom attention kernels and alternative attention implementations that greatly reduce peak memory usage
• A vastly superior Colab notebook that runs inference many times faster than the original
• Efficient scripts for computation of alignments, including the option to run MMSeqs2's alignment pipeline
• Vastly improved logging during training & inference
• Careful optimizations for significantly improved speeds & memory usage during both inference and training
• Opportunistic optimizations that dynamically speed up inference on short (< ~1500 residues) chains
• Certain changes borrowed from updates made to the AlphaFold repo, including bugfixes, GPU relaxation, etc.
• "AlphaFold-Gap" support allows inference on complexes using OpenFold and AlphaFold weights
• WIP OpenFold-Multimer implementation on the multimer branch
• Improved testing for the data pipeline
• Partial CPU offloading extends the upper limit on inference sequence lengths
• Docker support
• Missing features from the original release, including learning rate schedulers, distillation set support, etc.

Full Changelog: v0.1.0...v1.0.0

OpenFold v0.1.0

The initial release of OpenFold.

Full Changelog: https://github.com/aqlaboratory/openfold/commits/v0.1.0