Commit History
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Wave 21: adversarial-review fixes — all 9 verified findings closed
Baladithya Balamurugan +1: Claude Fable 53 reviewers (correctness/security/fidelity) + independent verifier over the Stage-0 pipeline commit; every P0/P1 empirically confirmed before fixing. P0: reverse_unified_diff silently corrupted file-add/delete patches (git apply rc 128: naive +/- swap inverts the ---/+++ order and leaves a stale `new file mode` header). Fix: route them to the UNREVERSED_MARKER fallback; regression test with a /dev/null patch. P1: DECONTAMINATION_LIST omitted SWE-Gym's 11 eval repos (the architecture named both families) — added; V3 now fully closed; regression test. P1: COMPOSER_RECIPE_MAPPING.md:20 still asserted KL(teacher||student) as blog-stated — corrected to direction-unverified per F-12. P1: build_corpus budget was a soft ceiling (check-then-spend overshot by one rollout) — now a pre-charge hard ceiling; test asserts cost <= budget. P2: dedup stats double-counted rows that were both within-run and cross-gen dups (disjoint partition now); run_id path-traversal guard o…3bbcf21 -
Wave 21: Stage-0 dataset pipeline — swesmith engine, rollout harness, gates, contract
Baladithya Balamurugan +1: Claude Fable 5Implements research/deepread/13-synthesis-architecture.md (ADR-016): the "point at a repo -> dataset" pipeline the critical review architected, closing every verified P0 from research/deepread/12-verified-findings.md. New modules (+96 tests, full suite 511 passed / 66 skipped): - datagen/repo_gate.py: SPDX-ish license detection -> 3 tiers (fail-closed) + benchmark DECONTAMINATION vs the SWE-bench eval-repo list (closes V3 — zero decontamination existed anywhere). - datagen/swesmith_adapter.py + [swesmith] extra: SWE-smith as the synthesis engine (closes V4 buy-vs-build). Handles the patch-semantics INVERSION (SWE-smith's patch INTRODUCES the bug; golden_diff = reverse_unified_diff) + strategy provenance sidecar + difficulty priors. - datagen/trajectory.py: canonical trajectory IR (closes D-11). ToolCall canonical_form = v1 divergence-gate action algebra (replaces the whitespace stub, D-3); to_policy_row = THE policy-visible serializer, sentinel-tested to never leak gol…9a2ce20
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Wave 20: Tier-0 fidelity fixes — k1-in-reward KL + Composer-2 behavior rewards
Baladithya Balamurugan +1: Claude Opus 4.8 (1M context)Closes the two cheapest "next-level" gaps from the F5 fidelity audit (Rubric A items c2, h, i). Both reproduce Composer-2 §4.1/§4.2 exactly, without the hint mystery. 33 new tests; full suite 415 passed / 66 skipped. (1) k1-in-reward KL (F5 #1, the highest-fidelity-leverage single change). Composer-2 §4.1 chooses the k1 estimator IN THE REWARD (-log r); TRL uses k3 IN THE LOSS. The 2025/26 evidence (arXiv:2512.21852, verl k1-only, TRL #4967) says k1-in-reward improves OOD generalization where k3-in-reward can collapse — exactly the "take any model to the next level" axis. - trainer/kl_in_reward.py: pure, tested math. k1/k3 per-sequence estimators + apply_kl_in_reward, which adjusts GRPO advantages by -coef·(KL - group_mean(KL)). test_kl_in_reward.py PROVES this exactly equals folding -coef·KL into the reward then re-running GRPO's group-mean baseline (9 group/gen combos) — the justification for not forking TRL's scoring code. Exact only without std-norm (Dr.GRPO …41289bf -
Wave 20: close F4 s3:// gap — live-S3 DiLoCo allreduce smoke (AWS_SMOKE-gated)
Baladithya Balamurugan +1: Claude Opus 4.8 (1M context)ObjectStoreAllReduce's S3 branches (_init_fsspec/_put/_exists/_get over s3fs) previously had only mock coverage; F4 flagged "s3:// never exercised against real S3" as the highest-value unproven gap. Adds test_s3_rendezvous_allreduce_across_replicas to test_serverless_local.py (torchft-free, so it runs on Apple Silicon CI too): 2 OS processes call ObjectStoreAllReduce.allreduce() over an s3:// rendezvous, every rank must end with the cross-rank mean. Reuses the existing spawn-importable _replica_compute_and_sync. Gated on AWS_SMOKE=1; skips cleanly otherwise. Verified live 2026-06-09 against s3://amazon-sagemaker-386931836011-us-west-2-7597bf4d9a3d/diloco-rdv/: both ranks converged to identical weights (max|diff|=0.00e+00), both round_000000/rank_000{0,1}.pt objects present in S3 — proving the PUT->poll->GET->mean path and S3 strong read-after-write consistency hold cross-process. Full file: 10 passed, 1 skipped. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>bd37412 -
R14: harden live-Docker tests against transient daemon contention
Baladithya Balamurugan +1: Claude Opus 4.8 (1M context)The Phase-8 verifiers flagged 2 live-Docker DockerSandbox tests as flaky under concurrent container resource pressure (full suite + review agents spawning containers) — passing in isolation. Added _retry_docker(): bounded retry (3x, backoff) on transient daemon errors (timeout/resource/conflict/500/connection), re-raising genuine repeatable failures. Wired into the 4-gate inversion test and the network-disabled test. 27 passed / 1 skipped, lint-clean. Closes the last addressable Phase-8 verification finding; backlog now fully resolved on this host (remainder is user-gated GPU/token only). Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>c647fe9 -
Wave 3 cleanup: close deferred-LOW review items R5/R6/R11
Baladithya Balamurugan +1: Claude Opus 4.8 (1M context)- R5: EKSExecutor.cancel + SageMakerExecutor.cancel now re-raise genuinely unexpected errors instead of swallowing ALL exceptions; only already-terminated signals are idempotent no-ops (EKS: 404/409; SM: ResourceNotFound + already-terminal ValidationException via new _is_already_terminal). + a test that an AccessDenied-class error propagates. - R6: EKSExecutor.collect() result dicts include a 'result' key (the S3 rendezvous URI, or None) for cross-backend shape uniformity with Local/Modal/SageMaker. - R11: seed torch.manual_seed(0) in spike-006 test_alternating_batches_loss_ decreases so the loss-trend assertion is reproducible and no longer flaky under CPU contention (it failed only in the contended full suite, passed in isolation). Root cause was unseeded nondeterminism, not a real regression. All Wave-3 review findings (R1-R11) now closed. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>7d9dbbc -
Wave 3: close the HIGH review findings (kill-switch wiring, HeldoutSplit, EKS entrypoint bug)
Baladithya Balamurugan +1: Claude Opus 4.8 (1M context)Phase-7 reconciliation of the concurrent review team's findings (research/review-*.json). HIGH: - R1: wire HeldOutGuard into ComposerReplicationTrainer — OPTIONAL + OFF by default (no heldout_guard => byte-identical legacy behavior). When configured, _maybe_update_killswitch folds in-loop reward + injected heldout_eval_fn() + token-mean KL into the guard at the logging cadence; fires a hard (CollapseStopError) or soft (control.should_training_stop) halt. The #2 collapse safeguard now actually fires instead of being dead code. + test_killswitch_integration.py. - R2: build composer_replication/safety/holdout.py — HeldoutSplit disjointness enforcer (id-set + optional content-hash; .split()/.validate()/.assert_disjoint; raises HeldoutOverlapError listing the leak). The un-built second half of C1 that keeps the guard's proxy-real gap signal meaningful. +10 tests. Re-exported from safety/__init__ (resolves the dangling refs). - R3: EKS entrypoint contract bug — replica_e…bd0c358 -
Wave 2: 4 new modules (kill-switch, EKS/SageMaker executors, DockerSandbox) + B4/B7 completion
Baladithya Balamurugan +1: Claude Opus 4.8 (1M context)Built by the parallel execution team (worktree-isolated), integrated + tested here. New modules (all CPU-testable via mock/lazy-import; optional deps gated): - composer_replication/safety/ — HeldOutGuard run-level collapse kill-switch (held-out-declines-while-reward-rises streak + KL-to-init hard-stop 0.08 + proxy-real hacking-gap; EMA-denoised, latched-fire, CollapseStopError). The documented #2 safeguard for the self-evolving flywheel. 23 tests. - composer_replication/diloco/serverless/eks.py — EKSExecutor satisfying the ServerlessExecutor Protocol via a SINGLE Kubernetes Indexed Job → N rank-ordered ReplicaHandles, gang-cancel (Background propagation), REPLICA_RANK via the downward API, S3 rendezvous (IRSA). 28 tests (mock BatchV1/CoreV1). - composer_replication/diloco/serverless/sagemaker.py — SageMakerExecutor (boto3 create_training_job, same S3 rendezvous, status mapping). +13-test module written during integration (the build agent shipped it test-less). - compos…7a55e1e -
Wave 1: fix 8 failing tests + unblock Docker E2E + dep/doc debt
Baladithya Balamurugan +1: Claude Opus 4.8 (1M context)Backlog-resolution Wave 1 (branch backlog/goal-resolution-2026-06). Bugs fixed: - B1 (P0): generate spikes/007 synthetic_session_with_error.jsonl fixture (never committed — .gitignore *.jsonl whitelisted the sibling but not this one) → the 8 failing test_trace_examples_adapter tests now pass. Added the missing .gitignore whitelist line. - B2 (P2): [dev] extra was un-installable on Apple Silicon (pulled Linux-only torchft-nightly). Dropped diloco from base [dev]; added [dev-full] for Linux. - B3 (P2): [serverless] extra now includes s3fs/boto3/kubernetes (needed for real S3 rendezvous + the EKSExecutor/SageMakerExecutor adapters). Newly unblocked: - D1 (…-245d): Docker substrate E2E — Docker now available on host; both gates (4-gate substrate inversion + cache-scrub-in-container) PASS. Long-standing "hardware-blocked" item closed. Doc/API debt: - B4: reconciled divergent test counts (115/176/210/232) to one canonical figure measured this session: 266 passed / 62 skipp…c11cf49
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feat(trainer): policy-optimization objective MENU (ADR-014)
Adds make_po_config(objective=..., **overrides) — RL's base objective is no longer hardcoded to Dr.GRPO. Six selectable named presets over trl 1.5.0's verified GRPOConfig knob-space (introspected the installed package, not a GitHub snapshot): grpo | vanilla GRPO (std-norm advantage) dr_grpo | DEFAULT; no length-std bias (Composer 2.5's base objective) bnpo | batch-normalized dapo | decoupled clip-higher (epsilon_high=0.28) + overlong mask + KL off gspo | sequence-level importance ratio (Qwen3; long-CoT / MoE stable) cispo | detached-IS REINFORCE (every token keeps a gradient; MiniMax-M1) Every preset is PURE CONFIG (trl already implements each loss_type branch + importance_sampling_level/epsilon_high) — no custom _compute_loss. Drift guards assert loss_type / IS-level / epsilon_high actually applied so a preset can't silently degrade (e.g. GSPO with IS overridden back to token raises). 10 unit tests green against real trl 1.5.0. Research-grounded: Composer …aae66fa
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fix(phase-8): close all 5 cross-family final-verify findings + regression tests
The deep-work-loop exit gate (2 independent confirmations). A final 3-family scatter of the session diff found and we fixed: - [P0 latent] SDPO sentinel-mask used only student_response_valid; now requires BOTH valid masks AND non-sentinel indices (a future divergent teacher tail could have distilled against clamped position 0). - [P1 convergent, GPT-5.5+Gemini] curriculum shared one n_effort denominator for turns+think_tokens; split into independent n_turns/n_think counters. - [P1] docker E2E test ran pip-install under --network none (would fail when the gate activates); replaced with stdlib python -c expression runner, no network. - [P1] MMLU reward: Answer: A or B hedge scored full credit; _HEDGE_RE now penalizes it as multiple-answers. - [P1] HackMonitor read-markers matched import in important / cat in concatenate and scanned the agent patch as read-evidence; whole-word regex + exclude patch/diff payloads from BOTH layers (a legit patch can no longer self-incriminate…678d10b -
feat(b4-gpu+b6): GPU train-proof on A10G + docker-gated substrate E2E test
B4-GPU: modal_b4_gpu_smoke.py ran real Qwen2.5-0.5B-Instruct on a Modal A10G in bf16, 30 steps of the real 3-channel composition. PASS: all-finite, SDPO channel fired nonzero (max JSD 0.1855), loss converged 4.7262 -> 0.0050 monotone. This is the genuine "it trains on GPU" proof the CPU smoke could not give. Result + curve in gpu_smoke_result.json; README documents both CPU and GPU proofs. B6: test_docker_substrate_e2e.py — the docker-gated 4-gate substrate-inversion E2E now EXISTS (was only referenced). Runs the gates against a real python:3.11-slim container + real subprocess pytest on a minimal synthetic feature-deletion task, plus a cache-scrub-in-container test. Skips cleanly with no Docker (2 skipped here), runs the moment a Docker host executes the suite. ADR-010 [~] gate updated: mechanics gate is now ready-to-close, not just wired. Cost: ~1-3 USD A10G. No LMA budget touched.c009712 -
feat(wave-b): ADR-013 LMA integration + B4 end-to-end SDPO-fires proof + doc refresh
ADR-013: composer_replication/integrations/altered_minds/ (generic, framework-side) - MMLUFormatReward: structured-answer reward, scores only the final letter (not rationale style), unparseable/multiple-answer penalties, option-order randomization, always-C exploit detectable via logged option distribution. - dual_kl_logger: KL(policy||altered-init) AND KL(policy||unaltered-base) as the washout-vs-amplification instrument (neither optimized). - channel_ladder_configs: A0-A4 isolated-channel ladder (alpha=0.02/beta=0.05), replacing the uninterpretable combined alpha=0.2/beta=0.4 recipe per the cross-family research critique (SDPO can AMPLIFY an altered model). B4: examples/altered_minds_channel_ladder/run.py PROVES the SDPO channel FIRES nonzero (JSD=0.0565, grad flows) through the REAL shipped collator alignment indices — the thing the old smoke could not show (it only proved init). Honest stub-with-differing-tokens proof; real-model path gated behind ALTERED_MINDS_REAL_MODE…21647a4 -
feat(wave-a): close ADR-011 (SDPO alignment indices) + ADR-012 (review findings)
B1/ADR-011: collator emits student/teacher_response_idx + valid masks via _mask_to_padded_indices; loss sentinel-masks padding. Strict SDPO no longer raises against the real collator (the regression my review-fix introduced). B2/ADR-012: - k1-KL: found TRL 1.5.0 uses k3 not k1; corrected docstring honestly + documenting test. - hint routing: style/communication/effort sites now reach the judge (error-kind aware). - HackMonitor: added patch-provenance layer defeating string-concat obfuscation; ADR-010 language corrected AST->signature+patch-provenance. - curriculum: optional turns/think_tokens effort signals, backward-compatible. 210 passed / 16 skipped (was 192). Two Opus-4.8 workers in parallel.d02d724 -
review+fix: cross-family adversarial ADR review (owed item) + remediation
Ran the owed 5-family adversarial review of ADR-008/009/010 (unblocked once OpenRouter credits were restored). 4/5 clean reviews (GPT-5.5, Gemini 3.1 Pro, DeepSeek V4 Pro, Grok 4.3; Kimi starved its token budget). Verdicts: ADR-008 3-REJECT/1-fix, ADR-009 unanimous-fix, ADR-010 3-REJECT/1-fix — all REJECTs were "accepted-status outran the evidence," not "design wrong." The review caught a real policy-corrupting P0 the solo pre-mortem missed: the SDPO alignment guard was a shape-check, so hint-shifted teacher tokens could silently misalign and distill garbage into the policy. Verified every convergent finding against code, then fixed (192 pass/16 skip, was 187): - SDPO alignment (composer_trainer.py): require collator-emitted student_response_idx/teacher_response_idx; gather aligned post-hint logits before JSD; strict-mode raises on missing/mismatched indices. Tests rewritten to the corrected contract (different-length sequences now exercised). - Sandbox scrub (sandbox.py): boo…185cce2 -
feat(datagen): ADR-010 FeatureDeletionEnv synthetic-data subsystem; accepted
Track A of the deep-work-loop — Composer 2.5's named synthetic-data generator (Feature Deletion) as a reusable subsystem. New composer_replication.datagen: - schema.py: FeatureDeletionTask (broken_repo + FAIL_TO_PASS reward target + PASS_TO_PASS functional guard; golden_diff HELD OUT of repr/observation). - sandbox.py: Sandbox Protocol + FakeSandbox (unit tests) + LocalSubprocessSandbox (real); SANDBOX_DENYLIST blocks find/strings/unzip/decompilers/git (the tools Composer's reported reward-hacks used to recover deleted signatures). - monitor.py: HackMonitor — flags cache/bytecode-provenance hacks so the grader masks reward (defense-in-depth behind the sandbox lockdown). - curriculum.py: DifficultyCurriculum — online pass-rate gate; up-weights the ~0.5 frontier (w ∝ p(1-p)), retires aced tasks, quarantines all-fail tasks (raw rate, not smoothed). Implements the blog's "select for harder tasks dynamically". - validator.py: 4-gate solvability validator (baseline-green / del…9336af3 -
feat(hints): ADR-009 layered HintGenerator; accepted
Track B of the deep-work-loop. Extends hint_generator.py from a flat dispatch registry into a layered, cost-ordered HintGenerator behind a typed Protocol — the SDPO textual-feedback hint source (Composer 2.5's hint mechanism is unstated in every Cursor artifact; this is our reconstruction). Layers (tried cheapest-first, first non-None wins): 1. TemplateHintGenerator — the existing 5 templates (free, deterministic; byte-identical to dispatch(), preserved). 2. RawErrorHintGenerator — raw env/tool error text as the hint (free; covers any message-bearing site templates miss). SDPO "environment feedback as conditioning signal". 3. LLMJudgeHintGenerator — <=2-sentence corrective hint via an injected complete() callable (optional, OFF unless provided; in-memory + disk cache keyed on error-context hash; covers style/communication/effort). CompositeHintGenerator.as_collator_hook() returns a callable matching the existing CollatorConfig.hint_generator signature (…84740d4 -
feat(trainer): ADR-008 Dr.GRPO config + SDPO strict-alignment guard
Phase-6 execution of ADR-008 (gates 1, 2, 5 green; gate 3 = the live GRPOTrainer smoke runs detached separately). - make_dr_grpo_config(): builds trl.GRPOConfig to the Dr. GRPO recipe (loss_type=dr_grpo => no length-standardization bias; scale_rewards=none => no std-dev advantage normalization; num_iterations=1 => single-epoch), with a drift-guard assertion. TRL 1.5.0 natively supports these knobs and its own help text cites the Dr. GRPO paper for both. - ComposerReplicationTrainer.strict_sdpo_alignment (default True): the student/teacher logit shape-mismatch path now RAISES instead of silently zeroing the SDPO channel (closes the ADR-008 trust-gap, composer_trainer.py lines 158-160). Opt-out to warn-and-skip for production resilience. - prime_rl/composer_loss.py: NotImplementedError(alpha_sdpo>0) message now points at the TRL host as the SDPO home (documents the ADR-006 amendment). - Tests: 7 new (config knobs asserted; strict raises / non-strict skips / aligned fir…bde5c5e
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Wave 21c: verify PRIME-RL adapter parity against upstream source (byte-for-byte)
The recipe's only automated parity check (test_parity_with_prime_rl_default_loss_fn) is skip-marked whenever prime-rl isn't importable in the framework venv — i.e. essentially always, since we deliberately keep prime-rl's heavy deps (vLLM, pydantic config trees, flash-attn) out of our test env. The fallback was an in-file reimplementation (_reference_default_loss), so a shared bug could pass silently. This closes that gap against the ACTUAL upstream source. ## What was done Built an out-of-band parity harness that: - clones PrimeIntellect-ai/prime-rl (shallow) - builds an isolated venv with ONLY torch+beartype+jaxtyping+numpy - loads upstream src/prime_rl/trainer/rl/loss.py directly by path, stubbing the two modules it imports (prime_rl.configs.trainer, prime_rl.utils.utils) so we skip the vLLM/pydantic dependency tree entirely - runs identical inputs through our loss_fn and upstream default_loss_fn ## Result 24/24 cases match (12 seeds × 2 regimes: tiny-perturbation + wide-diver…c98928e -
Wave 21b: skip zero-signal SDPO on empty-recovery error turns + real-trace validation
Found by validating the Wave 21 pipeline against REAL Claude Code session logs (738 local sessions, 66 with is_error:true) rather than only the synthetic fixture. Two outcomes: a collator fix and a permanent validation example. ## Collator fix: empty-recovery error turns On real traces, ~67% of error sites have EMPTY recovery content when strip_thinking=True — because the error-RECOVERY turn is frequently pure [THINKING] (the model reasons about the failure, then silently retries a tool), and stripping thinking empties it. The old code set any_errors=True and injected a hint the moment hint_text existed, BEFORE checking recovery content, so an empty-recovery turn produced an all-ignore_index sdpo_loss_mask: a zero-signal SDPO row that wastes a forward pass and dilutes the channel. Fix: only treat a turn as an SDPO error site when BOTH a hint was produced AND the recovery turn has content (`hint_text and turn.get("content")`). Applied symmetrically to `_build_hint_injected_trace` (te…d61036a -
Wave 21: close both Wave 20 debt items — chat-template alignment + structural is_error
Two architectural-debt items flagged "Wave 20 candidate" in the framework doc, both CPU-only, both now fixed and regression-guarded. ## 1. SDPO mask chat-template drift (was ~67% aligned, now ~100%) `ComposerDataCollator._build_segment_mask` built the sdpo_loss_mask (and the aligned-student response_mask) by tokenizing each content segment in isolation and concatenating. That ignored the scaffolding tokens apply_chat_template inserts around every message (<|im_start|>{role}\n ... <|im_end|>\n, BOS), so mask bits drifted left of the real content tokens — the residual ~33% contamination documented in the Wave 19 production audit. Fix: new `_build_chat_aligned_mask` derives the mask from per-message apply_chat_template prefix deltas. For message k it computes the token span len(template(msgs[:k+1])) - len(template(msgs[:k])), then locates the content run inside that span by subsequence match and marks ONLY those positions as loss. Falls back to whole-span marking if the content run can…6806cf7 -
Wave 20: ModalSpawnExecutor — finish the Modal-backed serverless executor
Wave 17 shipped a NotImplementedError skeleton for ModalExecutor pinned by test_skeleton_executors.py. Wave 18 hardened the skeleton contract to be strict per-code-path. This wave adds the real Modal-backed executor as ModalSpawnExecutor (sibling class), preserving the skeleton contract for backward compat while making DiLoCo across Modal containers actually runnable. Design choices vs the v0 skeleton's docstring: 1. **User-provided modal.Function instead of internal app construction.** The skeleton showed a pattern where the executor builds its own modal.App and registers run_replica internally. That couples the executor to image/GPU/Volume choices the user actually wants to own. ModalSpawnExecutor takes a *pre-decorated* modal.Function from the caller. The user defines: @app.function(gpu="H100:4", image=img, volumes={"/vol": vol}, secrets=[...], timeout=4*3600) def diloco_replica(rank: int, rendezvous_uri: str, world_size: int, **k…a384097
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Wave 19: production-grade SDPO via ComposerDataCollator + adapter + collator fixes
Adds the full production data path Wave 18 deferred: ClaudeCodeIngester → adapter → ComposerDataCollator → compose_loss with proper hint injection at detected error sites. Two rounds of 3-reviewer cross-family review caught a critical SDPO mask alignment bug in round 1; round 2 verified the fix. NEW infrastructure: - composer_replication/ingestion/trace_examples.py: claude_states_to_trace_examples() adapter walks ClaudeCodeIngester output, detects [TOOL_RESULT (ERROR)] tagged user turns, marks the recovery assistant turn with tool_error="<kind>" so ComposerDataCollator._is_error_turn picks it up. Default classifier handles file_not_found, permission_denied, command_not_found, syntax_error, connection_error; users can pass custom error_kind_fn. Backward-scan finds errors even when intervening user turns separate the error from recovery. - composer_replication/ingestion/tests/test_trace_examples_adapter.py: 14 tests pinning the adapter contract (error detection, classifica…03bf323
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Wave 18: 14 backlog items closed + 3-reviewer cross-family review
Polish wave grinding down 14 P0/P1/P2 items from Wave 7 audit + Wave 11/12 self-critique + Wave 16/17 deferrals. Two passes of 3-reviewer cross-family review (Gemini 3.1 Pro / Grok 4.3 / Sonnet 4.6) caught 6 real issues in round 1; round 2 verified all fixed plus 2 new flagged items addressed. Doc honesty (P0): - README.md scoping change at line 29: dropped "any HuggingFace base model" for the more honest "any HF causal LM with a chat template (Qwen, Llama, Mistral, DeepSeek, Phi, Gemma families)". Added qualifier that Spike 006 zeroed the SDPO channel due to shape misalignment, so SDPO is verified via the integration test suite + end-to-end examples, not Spike 006. - spikes/005-integrated-trainer-skeleton/verl_path/README.md NEW — explicit STATUS: design-only marker per Wave 7 audit Objection 3. Documents what to do before relying on the VeRL path (install Ray, run parity test against trl_path). Test honesty (P1): - spikes/006-real-hf-model-smoke/verdict.md numerical c…54efac8 -
Wave 17: close all 5 audit FLAGs + SDPO context alignment + serverless re-exports
Three-track follow-up to Wave 16, with cross-model review (gemini-3.1-pro APPROVED, grok-4.3 surfaced one BLOCKER that verified false-positive empirically, deepseek-v4-pro burned all max_tokens on hidden reasoning producing no visible output): Wave 17a — serverless package re-exports (real code bug) composer_replication/diloco/serverless/__init__.py now re-exports ModalExecutor and HFJobsExecutor alongside LocalProcessExecutor. The package docstring already documented `from composer_replication.diloco.serverless import ModalExecutor` as the public API but the import would have failed because the names weren't in __init__.py's import list or __all__. Both modal.py and hf_jobs.py import-safely (they don't import the optional `modal` / `huggingface_hub` packages at module level — those are deferred to class method calls), so adding the re-exports doesn't introduce a new dependency. Pinned by a regression test (test_public_reexports_include_all_executors in test_s…a84c060 -
Wave 16: install ergonomics + gradient evidence + SDPO end-to-end example
Five-track polish wave with mandatory cross-model adversarial review (deepseek-v4-pro + gemini-3.1-pro-preview, route-fidelity-verified via direct-urllib scatter; reviewers caught 2 real bugs that BOTH made it into the staged diff and would have shipped without the review): Wave 16a — Install ergonomics (extras pinning) pyproject.toml dropped three extras whose lower bounds were unsatisfiable on public PyPI and would have blocked any fresh user: - monarch>=0.4.1: PyPI 'monarch' tops out at 0.1.11 and is unrelated to Meta's actor framework; the real Monarch ships as torchmonarch-nightly with platform constraints. - prime-rl>=0.5: 'prime-rl' is not registered on PyPI at all; Prime Intellect publishes from source only. - data-juicer>=1.0: 'data-juicer' is not registered on PyPI; the closest match (py-data-juicer) has broken transitive deps. All three integrations import lazily, so the framework still loads cleanly without them. docs/TROUBLESHOO…c0a5ab7 -
Wave 15: 4-angle multi-model self-critique caught 2 math BLOCKERs in primary loss kernels; fixed against upstream byte-for-byte + GSM8K example + ergonomics
PHASE 15a: 4 parallel adversarial reviewers, each with different framing to maximize independent-angle coverage: - MATH (Opus 4.7): cloned upstream OPSD/TAID/PRIME-RL/SimPO, did line-by-line diff. Found 2 BLOCKERs all 8+ prior reviewers missed. - TESTS (Opus 4.7): scrutinized 3 high-stakes test files for weak assertions. Found PRIME-RL parity test silently never runs; bit-exact test uses allclose; entropy-OPD test is pure smoke. - DOCS (Opus 4.7): audited 6 major docs + ADRs. Found test-count drift (77/107/124 vs 145), compose_loss kwarg drift, stale "Deferred to Wave 14" claim, PRIME-RL test count 10 vs 16. - USER-JOURNEY (Opus 4.7): walked "RL-finetune Qwen-7B on GSM8K" end-to-end. Scored framework 2.4/5 with Real-Task-Path = 1/5. #1 friction: NO GSM8K example anywhere. All 4 reports saved to /tmp/wave15_*.md. Headline: math reviewer's upstream-clone-and-diff approach caught what paper-level review missed. PHASE 15b: synthesized findings into 5-task fix scatter. PHA…e5add15 -
Wave 14: close every Wave 13 review finding + 4 documentation files; Wave 14b: real PRIME-RL parity + multi-process DiLoCo convergence
PHASE A: 4 parallel impl subagents closed every Wave 13 cross-model review item. T1 \u2014 compose_loss integration (closes W13 BLOCKER 2): - Added `dpo_variant: 'dpo'|'simpo'`, `sdpo_wrapper: 'none'|'taid'|'entropy_opd'`, `taid_schedule_step`, `taid_total_steps` plus 5 tuning kwargs - 11 new integration tests in composer_replication/tests/test_compose_loss_integration.py - Bit-exact reproduction of legacy compose_loss output when defaults preserved - All 38 spike-005 tests still pass T2 \u2014 replaysim DJ adapter reshape (closes W13 Suggestion 3): - _dpo_pair_to_dj_record now emits BOTH flat strings AND chat-messages for dual-shape compatibility with data-juicer's text ops - _dj_record_to_normalized round-trips both shapes - default.yaml fixed: text_keys plural \u2192 text_key singular (caught a related bug in the same op set) - Real data-juicer e2e test runs DefaultExecutor on a 3-record fixture - 15 tests (was 9) T3 \u2014 MockManager DiLoCo integration (closes W13 Suggest…d9dd3a5 -
Wave 13: serverless DiLoCo + replaysim normalization + 3 distillation losses + PRIME-RL + Monarch
Expanded the brief mid-deep-work-loop to address the user's request for serverless training-system support, replaysim dataset normalization, deeper self-distillation paper coverage, and Meta's PyTorch agentic stack tie-ins. NEW MODULES (35 tests passing): - composer_replication.distillation: SimPO (arXiv:2405.14734), TAID (arXiv:2501.16937), Entropy-Aware OPD (ICLR 2026 spotlight). 17 unit tests covering scalar/differentiable/scheduler-monotonicity and boundary-condition correctness against paper formulas. - composer_replication.diloco.serverless: ServerlessExecutor Protocol + ObjectStoreAllReduce (fsspec-backed; works with file:// + s3:// + hf:// + gs:// + az://) + LocalProcessExecutor (working) + ModalExecutor / HFJobsExecutor (skeletons, raise NotImplementedError). 9 tests including 3 multi-process tests pinning the allreduce barrier with mean-of-{0,1,2}=1 + mean-of-{0,100,200}=100 across two consecutive rounds. - composer_replication.replaysim: data-juicer adapte…b266c31 -
Wave 12: close V1-V8 brief — GPU smoke, SDPO firing, real-trace e2e
Addresses cross-model review priority items 3, 4, 5, 9 — the ones that materially close the original V1-V8 brief. Wave 12 deliverables: 1. **Spike 002a-mini-gpu-smoke** (NEW directory) — closes "zero GPU evidence": - 50-step Qwen2.5-0.5B-Instruct training run on local RTX 5090 (sm_120, Blackwell), bf16, in 35 s wall-clock total - Loss 0.7354 → 0.00034 (99.95% reduction), all grads finite, peak VRAM 5.31 GB (well under ADR-001's 8 GB target), median 480 ms/step - Captures per-step memory + step-time + finite-grads in results/gpu_loss_curve.csv + results/gpu_verdict.json - ADR-001's local-5090 choice now empirically verified (vs ~3-5 min cold-start cycle estimated for Modal L4) - Resolves cross-model review item #4 2. **Spike 006-strict** (`tests/test_strict.py`) — closes the tautology critique: - test_alternating_batches_loss_decreases: 10 steps alternating between factorial + binary_search variants. Late-avg-loss < 50% × early-avg-loss. …d88715c -
Wave 11: cross-model adversarial review + honest down-revision
Phase 11 of the deep work loop ran a cross-model adversarial review on the Wave 7-10 work. The review (anthropic/claude-opus-4.7, separate session) found 10 substantive flaws including 2 BLOCKERs: 1. **Scorecard inflation** — initial self-claim was 5/10 → 9/10, honest re-scoring is 5/10 → 7/10 ✅ + 1/10 ⚠️ + 2/10 ❌-spirit. 2. **Spike 008 acceptance criterion silently redefined** — BACKLOG required "2 replicas converge"; what shipped is "1 replica + passthrough no-op allreduce." The recon doc's "ready-to-paste 2-replica pattern" hits a single-process post-hook sequencing bug. Both BLOCKERs addressed in this commit: - docs/research/WAVE_7_10_FINAL_REVIEW.md — full 423-line review committed. - docs/VISION_VALIDATION.md — replace 9/10 self-claim with honest 7/10 re-scoring + per-test caveats acknowledging the spirit-failures of tests 6/8/10. Explicitly notes "the framework as of this commit has zero GPU evidence of any kind." - spikes/008-streaming-diloco/verdict.md — s…f16fa23 -
Wave 10 — packaging: composer_replication is now pip-installable
Promotes the framework from "skeleton scattered across spike directories" to a proper installable Python package (closes vision-validation gap V4). What's new: pyproject.toml at repo root - Hatchling build backend - Python ≥3.10 - Core deps: torch≥2.0, transformers≥4.46 - Optional extras: replay (httpx), diloco (torchft-nightly), train (trl, peft, accelerate, datasets), dev (everything + pytest, ruff) - Project URLs point to the HF repo + Discussions composer_replication/ package (8 modules) - __init__.py re-exports the framework's public API: compose_loss, LossComponents, build_batch (Spike 006) generalized_jsd_loss (verified port of OPSD) ClaudeCodeIngester, IngestionStats, SYSTEM_PROMPT (Spike 007) TraceState, DPOPair, TeacherSpec, replay_trace, extract_dpo_pairs, DEFAULT_TEACHERS (Spike 001/005) ComposerReplicationTrainer (Spike 005, TRL subclass) make_diloco_outer_loop …ac05fbf