fix(init): make seeded parallel weight initialization machine-independent - #2038
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…dent Parallel fills partitioned >=2^18-element tensors by Environment.ProcessorCount with per-chunk RNG seeds, so the same seed produced different weights on machines with different core counts. Use fixed 262,144-element chunks instead. Fixes 10 of the 84 training-invariant CI failures (run 32182588897); zero regressions at the CI configuration; full attestation in the PR body. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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No actionable comments were generated in the recent review. 🎉 ℹ️ Recent review info⚙️ Run configurationConfiguration used: Path: .coderabbit.yaml Review profile: ASSERTIVE Plan: Pro Plus Run ID: 📒 Files selected for processing (2)
Included review availability: Your plan provides up to 1 included review per hour; 0 remain after this review. WalkthroughGaussian and uniform initialization now use fixed 256K-element chunks for large tensors. Chunk calculations avoid integer overflow near ChangesInitialization chunking
Estimated code review effort: 3 (Moderate) | ~20 minutes Merge Risk: 🟡 Moderate · up to The change makes seeded initialization machine-independent, but the new chunk-count calculation can overflow for valid near-limit tensors and cause initialization to fail. This bounded correctness risk should be fixed or explicitly accepted before merging. Suggested reviewers: Poem
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Inline comments:
In `@src/Initialization/InitializationStrategyBase.cs`:
- Around line 352-354: Update all four fill methods in
InitializationStrategyBase to compute chunkCount with overflow-safe division,
using 1 + ((length - 1) / ParallelThreshold), and calculate each chunkEnd with a
long-based addition capped by length before passing the range to AsSpan. Add
boundary tests covering lengths near int.MaxValue and the final chunk.
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src/Initialization/InitializationStrategyBase.cs
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fix(init): make seeded parallel weight initialization machine-independent
What this fixes
Seeded weight initialization produced different weights on machines with different CPU core counts. This PR makes initialization machine-independent, fixes 10 of the 84 training-invariant CI failures (run 32182588897), introduces zero new failures at the CI configuration, and makes the remaining failures reproducible on any machine.
Mechanism
The four parallel fill routines in
src/Initialization/InitializationStrategyBase.cspartition tensors ≥ 2¹⁸ elements into one chunk per core, drawing one seed per chunk from the master RNG stream:Same seed, different core count → different network.
ResidualNeuralNetwork's 512×512 matrices are exactly 2¹⁸ elements, so 4-vCPU CI runners and dev machines built different models from identical seeds.The decisive experiment
ResidualNeuralNetworkTests.Training_ShouldReduceLoss(seed 1234, 10 Adam steps, 871,553 params):DOTNET_PROCESSOR_COUNT=4Faking only the reported core count reproduces CI exactly. One variable, full-precision match.
Impact across the 84-test training-failure class
7 tests proven core-count-dependent (stable within each core count across repeated runs, outcome differing between counts; one — SegNeXt — flips in the opposite direction: the bug was a lottery, not a 4-core penalty). 2 more probable (UNITER, Wav2Small: fail at both counts pre-fix, pass post-fix under the corrected seed layout). 10 net CI fixes, 0 regressions at the CI configuration.
Caveats — read these
Training_ShouldReduceLoss(already failing in CI) sometimes passed on 16-core machines pre-fix; it now fails consistently at 4 cores. Existing failure made consistent, not new breakage.stable_16core=noin the registry data below and are excluded from core-count attribution. This is a separate bug worth its own issue.Agent validation registry
How to use: pick claims by budget — C3 is the smoke check, C2 the decisive causation check, C4 the exhaustive tier. Execute
commandverbatim from the repo root, compare againstexpected. Verdicts per claim:confirmed(expected matched),confirmed-outcome-level(pass/fail outcomes matched but float fingerprints differed — expected off x64/deterministic-BLAS),refuted,inconclusive(run aborted/crashed: rerun without concurrent load before concluding anything — an aborted run attests nothing).TESTS.tsv — 84 tests: expected outcome per configuration + 16-core stability flag
check_c4.py — TRX-vs-expected checker (exit 0 = leg confirmed)
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