diff --git a/README.md b/README.md new file mode 100644 index 0000000000000000000000000000000000000000..372b1485e3a75502947d886c66462acb08d5e022 --- /dev/null +++ b/README.md @@ -0,0 +1,23 @@ +--- +pretty_name: FastPLMs research and validation artifacts +license: other +license_name: source-specific-terms +license_link: https://github.com/Synthyra/FastPLMs/blob/main/docs/licensing.md +--- +# FastPLMs artifacts + +This dataset holds the measured reports and golden regression tensors maintained by [FastPLMs](https://github.com/Synthyra/FastPLMs). It is not a training dataset or a set of model checkpoints. + +The source repository keeps `evidence.toml`, which pins an immutable dataset revision and each payload's SHA-256 digest and size. Fetch explicitly with `python -m tools.artifacts.evidence_store fetch` before offline documentation, release, or parity checks. + +Paths preserve the source workspace layout: `docs/evidence`, `docs/validation`, and `tests/goldens`. Runtime configuration, model manifests, dependency locks, and small synthetic fixtures remain in Git. + +## Evidence status + +The v2 confidence reports preserve historical numeric results. Their `metrics_review` fields mark correlations, bootstrap intervals, and acceptance gates as requiring recomputation after the tied-rank correction. Raw per-target predictions were not recovered from the closed training workstation or W&B. These archived values must not be presented as corrected evaluation results. No v2 confidence weights are included. + +Other artifacts retain their recorded source revisions, environments, and evidence boundaries. Presence in this dataset is not an assertion that all release gates pass. + +## Terms and provenance + +Payloads originated in the public FastPLMs repository at PR #49 (`1ae17f2b3955db28fe9c076b5c7e2394c6fc83ac`), with review-status annotations added to the v2 confidence reports. Golden metadata identifies originating checkpoints and source revisions. Applicable model and source terms remain in effect; migration does not relicense them. Consult the source repository's `LICENSES`, model manifest, and licensing documentation. No blanket permissive license is asserted for the combined collection. diff --git a/docs/evidence/attention/backend_latency.json b/docs/evidence/attention/backend_latency.json new file mode 100644 index 0000000000000000000000000000000000000000..34267fe987e493719e9f020bec6782ad3fe82642 --- /dev/null +++ b/docs/evidence/attention/backend_latency.json @@ -0,0 +1,203 @@ +{ + "schema_version": 1, + "method": "Randomly initialized models at published dimensions, FP32 parameters under CUDA BF16 autocast, inference mode. Each backend runs in its own process, three interleaved rounds per case; a round reports the median forward latency after warm-up. One batch is 8 rows of 512 positions.", + "residues_per_batch": { + "padded": 2336, + "full": 4096 + }, + "limitations": "Descriptive latency of an uncommitted working tree on cloud workers. It orders backends for automatic selection and is not a release benchmark or a parity claim.", + "runs": [ + { + "run": "20260921T131922-backend-bench-b42b0fec", + "source": { + "revision": "d9a23718713905dd907add3d7b7a85d6e8e49f23", + "dirty": true, + "changed_paths": 104 + }, + "environment": { + "python": "3.12.10", + "platform": "Linux-4.19.0-gvisor-x86_64-with-glibc2.36", + "torch": "2.13.0+cu130", + "transformers": "5.13.0", + "cuda": "13.0", + "gpu": "NVIDIA L4", + "compute_capability": [ + 8, + 9 + ] + }, + "cases": { + "dplm-full": { + "median_ms": { + "sdpa": 79.51769256591797, + "flash_attention_3": 79.99282836914062 + }, + "speedup_over_sdpa": { + "sdpa": 1.0, + "flash_attention_3": 0.9940602699903289 + }, + "failures": {} + }, + "dplm-padded": { + "median_ms": { + "sdpa": 79.93548583984375, + "flash_attention_3": 74.23538970947266 + }, + "speedup_over_sdpa": { + "sdpa": 1.0, + "flash_attention_3": 1.0767840803783608 + }, + "failures": {} + }, + "esm2-full": { + 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Correlations, bootstrap intervals, and acceptance gates must be recomputed with average tied ranks.", + "historical_values_preserved": true, + "raw_prediction_recovery": { + "status": "unavailable", + "details": "The GH200 workstation is closed. W&B contains no logged artifacts or raw per-target prediction records for either v2 run; aggregate history cannot reconstruct corrected metrics.", + "required_files": [ + "~/data/confidence-v2/evaluation/esmfold2_300/records.json", + "~/data/confidence-v2/evaluation/esmfold2/records.json" + ] + }, + "training_history_audit": { + "wandb_url": "https://wandb.ai/lhallee/fastplms-confidence/runs/d5587e06871a", + "history_rows": 780, + "metric": "train/skipped_targets", + "maximum": 0, + "scope": "All 780 update rows were inspected.", + "conclusion": "The skipped-target gradient bug did not affect this recorded training run because no training target was skipped." + } + }, + "model_id": "esmfold2_300", + "data": { + "dataset": "Synthyra/AtlasFold-Data", + "configurations": [ + "rcsb", + "rcsb_multimer" + ], + "maximum_resolution_angstrom": 4.0 + }, + "training": { + "donor_repo": "biohub/ESMFold2-Experimental-Fast-Cutoff2025", + "donor_revision": "74b88548bf19688b8727432db0d698cb2e1d8783", 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