Rebuild OpenBoost as a programmable v1 boosting foundation - #23

Merged

jxucoder merged 122 commits into

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codex/gpu-python-foundation-design

Sep 6, 2026

Commits on Aug 16, 2026

bench: add ScoringBench integration
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docs: add agent guide and learning log
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fix: preserve categorical tree state on save
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docs: record categorical persistence fix
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fix: reject unrepresentable categorical tree splits
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docs: record categorical cardinality limit
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fix: fail fast for unsupported model batching
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docs: mark experimental scaling boundaries
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docs: record scaling capability boundaries
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ci: compare performance across pushed revisions
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docs: record performance gate design
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Commits on Sep 5, 2026

docs: research OpenBoost impact and adoption strategy
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82cf1e2
docs: design GPU Python boosting foundation and execution plan
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merge: integrate unified trainer and local correctness fixes
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test: add isolated Modal foundation smoke and evidence gate
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test: record passing T4 foundation smoke evidence
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test: add wheel-installed weighted CUDA correctness regressions
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fix: make unified trainer execution and sampling explicit
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test: record T4 weighted Hessian regression and passing fix
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test: add real CUDA trainer boundary suite
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test: freeze real-data P2 baseline protocol and harness
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test: freeze passing T4 P2 execution and housing baseline
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feat: add validated experimental CPU objective facade
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feat: dispatch experimental builders and per-tree schedules
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feat: persist experimental inference state and restore coefficients
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docs: record P3 CPU contract and isolated wheel validation
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feat: add fixed-slot CPU and CUDA histogram primitive
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docs: freeze real T4 histogram parity evidence for P4.1
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feat: add numeric batch split and routed partition primitives
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docs: freeze P4.2 T4 evidence and prioritize extension usability
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feat: add device leaf reduction and explicit Newton leaf rules
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docs: freeze P4.3 T4 leaf rule evidence
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feat: assemble opt-in level-wise CPU and CUDA tree builder
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docs: freeze P4.4 T4 builder parity evidence
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feat: add independently installable CPU extension examples
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docs: freeze independent CPU wheel conformance evidence
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feat: integrate strict CUDA extensions in unified trainer
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test: extend strict GPU adapter and external builder coverage
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docs: freeze strict GPU trainer verification and remaining gates
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feat: add independent CUDA extension wheel conformance
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fix: guard GPU extension demo against spawned worker reentry
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docs: freeze independent GPU wheel conformance evidence
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bench: preregister resident foundation value matrix
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docs: add extension author guide and independent trial task
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bench: retain P7 quality pass and 13.9x GPU regression
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bench: isolate host profiling from GPU memory sampling
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docs: freeze P7 profiling and negative value conclusion
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perf: keep level-wise split updates in fixed slots
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test: freeze fixed-slot CUDA trainer conformance
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bench: verify fixed-slot wheels and clarify profile metadata
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bench: record fixed-slot improvement and remaining GPU gap
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fix: align ScoringBench model seeds and depth with declared runs
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docs: redesign the agent boosting foundation plan
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docs: define OpenBoost v1 scope and evaluation gates
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docs: require every v1 use case individually
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docs: specify all v1 foundation tasks and baselines
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docs: specify how to construct the v1 foundation
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Commits on Sep 6, 2026

docs: start v1 sprint execution and reflection log
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test: add independent scalar and tree references for v1
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refactor: retire legacy production code for the v1 rebuild
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test: add independent data and classification references for v1
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test: add ranking quantile and vector leaf references for v1
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test: add positive target and AFT references for v1
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test: add Normal and Formula directional update references for v1
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test: add identity and isolated run references for v1
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test: add exact author mutation references for v1
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test: add mixed feature and full vector growth references for v1
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test: integrate reference models and close v1 F0.2
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test: add v1 artifact integrity judge
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data: freeze A5 bike sharing inputs and rolling splits
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data: freeze A1 A11 housing with five splits
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data: freeze Adult official test and stratified splits
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docs: use English throughout repository prose
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data: freeze remaining grouped and stratified evaluation inputs
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eval: add independent scoring preprocessing and bounded workers
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eval: verify isolated CPU and CUDA comparator capabilities
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eval: add validation-only baseline workers with offset replay
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eval: seal independent validation selection before test release
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eval: support native baseline early stopping and replay
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eval: add query-aware ranking comparator workers
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eval: add parametric and paid-loss comparison workers
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eval: report auxiliary quality and supported survival scores
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eval: preserve train-only multi-output target scaling
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docs: record matching Housing host license evidence
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eval: seal independently authored held-out package metadata
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eval: bind frozen real folds to comparator worker packets
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eval: bind classification and rolling quantile datasets
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eval: bind counts paid amounts and survival worker inputs
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docs: audit F0 prerequisites and proposed foundation sequencing
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feat: add initial public CPU problem state and artifacts
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feat: add composable CPU numeric split operations
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feat: assemble composable depthwise numeric trees
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feat: compose squared boosting with mapped tree transactions
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feat: add Normal boosting with independent raw parameter width
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feat: add Formula geometry and sequential heterogeneous runs
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feat: add best-first and symmetric numeric growth policies
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feat: add categorical equality splits and mixed-feature artifacts
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feat: add class schemas and binary logistic boosting
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Add joint multiclass boosting and composable vector leaves
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Add query-local pairwise and lambda ranking recipes
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Add routed quantile and anchored penalized leaf solvers
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Add Poisson count boosting with explicit exposure
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Add weighted Gamma positive-target mean boosting
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Add fixed-power Tweedie nonnegative mean boosting
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Add persisted paid-frequency and severity composition
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Add censored log-normal AFT and scale-aware inference
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Audit CPU v1 coverage and order remaining foundation work
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Add multi-output squared recipes and persisted target scaling
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Reuse explicit prepared training data across independent runs
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654a3f2
Clean preparation test trailing whitespace
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Review foundation goals and plan remaining v1 acceptance work
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Add independent validation stopping across CPU recipes
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Verify installed public cohort and penalized-leaf extensions
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Verify public ordered Normal and Formula updates
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Accept external recipe results through a shared structural contract
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Verify an installed external expectile objective
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Connect current regression and Normal evaluation workers
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Bind multi-output evaluation to frozen training scales
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Bind A6 selection to verified training scales
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Report A6 standardized quality with verified training scales
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Connect classification workers and preserve external row identities
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Record full Covertype timeouts and prioritize CPU profiling
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