9f4a25e623586bbfaea5d77cd7dcb8cb48728d8c
2779 Commits
| Author | SHA1 | Message | Date | |
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jgrusewski
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9f4a25e623 |
feat(sp22-vnext): Phase A5 — aux_trade_outcome backward kernel (Phase A complete)
K=3 backward kernel that closes the forward → loss → backward chain for the trade-outcome aux head. Mirrors `aux_next_bar_backward` (K=2 sibling) line-for-line because gradient flow is K-independent: `d_logits = (softmax − one_hot)/B_valid` propagated through `Linear → ELU → Linear` chain via standard softmax-CE derivative. Per-sample partials (caller reduces via existing K-generic `aux_param_ grad_reduce` kernel): dW1_partial [B, H=128, SH2=256], db1_partial [B, H] dW2_partial [B, K=3, H], db2_partial [B, K=3] dh_s2_aux_out [B, SH2] Mask handling: labels[b] == -1 zeros the K-vector → all downstream partials zero (chain rule's multiplicative zero). All-skip batch produces valid_count=0 → d_logits=0 for every row → zero gradients across the board, no NaN. Sparse-label gradient amplification: B_valid is typically ~1-5% of nominal batch (trade-close events are rare), so inv_B = 1/B_valid is much larger than the K=2 sibling's inv_B = 1/(~B). Per-trade-close gradients have proportionally higher magnitude — correct credit assignment (rare signal speaks louder) but Phase E's Adam may need class-weighted CE or per-group LR tuning. ELU backward via post-activation identity: f'(x) = (h_post > 0) ? 1 : 1 + h_post — recovers derivative without re-evaluating x_pre. SP14 Phase C.5b separation preserved: reads h_s2_aux (aux trunk output), writes dh_s2_aux_out SAXPYing into dh_s2_aux_accum. Q's encoder structurally protected (aux_trunk_backward has no dx_in output). Phase A5 (this commit) is dead code — no Rust launcher. Phase B will land the full launcher chain (gpu_aux_heads.rs parallel ops struct, collector struct fields for W1/W2/b1/b2/Adam-state/saved-tensors/dW- partials, wireup in collect_experiences_gpu). Cubin: aux_trade_outcome_backward_kernel.cubin (24.8 KB). ═══ Phase A complete ═══ A1: ISV slots (none needed — reuses padding 121-123) A2: trade_outcome_label_kernel.cu (label producer) |
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jgrusewski
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3ddcfb8868 |
feat(sp22-vnext): Phase A4 — aux_trade_outcome loss reduce kernel
K=3 sparse cross-entropy reduce over the trade-outcome softmax tile produced by `aux_trade_outcome_forward` (Phase A3). Mirrors the K=2 sibling `aux_next_bar_loss_reduce` structurally: single-block shmem-tree reduce, two parallel partial strips (loss_numer + valid_count) reduced lockstep, fmaxf(p_tgt, 1e-30) numerical floor, fmaxf(valid, 1.0) all- skip-batch guard, valid_count_out[1] save-for-backward. Kept as SEPARATE kernel from the K=2 sibling: - Diagnostic isolation (distinct HEALTH_DIAG slot, distinct cubin in profiles for clean per-loss-source attribution) - Sparse-label semantic clarity (~95-99% mask=-1 vs ~50-100% valid for the K=2 next-bar head) - Future per-class weighting headroom (Profit/Stop/Timeout 3:1-10:1 imbalance will likely need class-weighted CE — surgical mod here without touching the K=2 head's contract) Phase A4 (this commit) is dead code — no Rust launcher yet. Phase A5 lands backward; Phase B wires the full forward→loss→backward chain. Discipline: feedback_no_atomicadd (single-block tree-reduce), feedback_ cpu_is_read_only (pure GPU), pearl_first_observation_bootstrap (sentinel 0 valid_count produces zero gradients gracefully on cold start). Audit: docs/dqn-wire-up-audit.md Phase A4 section. Cubin: aux_trade_outcome_loss_reduce_kernel.cubin (9.9 KB) compiles clean. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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jgrusewski
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07728f9efc |
feat(sp22-vnext): Phase A3 — aux_trade_outcome forward kernel + save-for-backward wireup
Phase A3 of the SP22 H6 vNext trade-outcome aux head (per
docs/plans/2026-05-14-sp22-h6-vNext-trade-outcome-aux.md). Two atomic pieces:
1. NEW kernel `aux_trade_outcome_forward_kernel.cu` — K=3 softmax aux head
forward (Linear → ELU → Linear → stable softmax). Mirrors
`aux_next_bar_forward` (K=2) but emits {Profit, Stop, Timeout} probs.
Saved tensors {hidden_out, logits_out, softmax_out} ready for A4 (loss
reduce) and A5 (backward). Dead code at this commit — no Rust launcher
yet. Registered in build.rs::kernels_with_common, cubin verified.
2. Save-for-backward buffers `pnl_vs_target_at_close_per_env` +
`pnl_vs_stop_at_close_per_env` ([alloc_episodes] f32 device-resident).
Producer: `experience_env_step::segment_complete` writes the trade's
realized P&L ratios vs profit_target / stop_loss at close (inline-
computed from `pre_trade_position × (raw_close − entry_price) /
(ps[PS_PLAN_PROFIT_TARGET] × prev_equity)`, symmetric-clamped to
[-2, +2] per pearl_symmetric_clamp_audit — same formula as the
sibling experience_state_gather's plan_isv[PLAN_ISV_PNL_VS_TARGET/_STOP]
slots). Consumer (eventual A4/A5 wireup): trade_outcome_label_kernel
classifies each close into {Profit, Stop, Timeout} via the ≥1.0
threshold-hit predicate.
Wireup discipline per feedback_registry_entries_need_dispatch_arms:
- New struct fields on GpuExperienceCollector
- stream.alloc_zeros at construct site
- Kernel-launch .arg() threading at experience_env_step launch
- StateResetRegistry entries (FoldReset sentinel 0.0)
- training_loop::reset_named_state dispatch arms
- All 10 registry pin tests pass including
every_fold_and_soft_reset_entry_has_dispatch_arm
Audit doc updated: docs/dqn-wire-up-audit.md Phase A3 section.
Next phases (per spec): A4 = aux_trade_outcome_loss_reduce (sparse CE,
mask=-1), A5 = aux_trade_outcome_backward, Phase B = 262-dim input
(h_s2_aux || plan_params), Phase C = 3-slot state assembly, Phase D =
12-weight W atom-shift, Phase E = dW + Adam, Phase F = validation smoke.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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jgrusewski
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26ce7ba690 |
feat(sp22-vNext): Phase A2 — trade-outcome label producer kernel
First foundation kernel for the H6 vNext trade-outcome aux head. Per-env classification at trade-close events into K=3 outcomes: - 0 = Profit (pnl_vs_target >= 1.0) - 1 = Stop (pnl_vs_stop >= 1.0) - 2 = Timeout (neither threshold hit) Sparse labels — most bars get -1 mask. Priority: Profit > Stop > Timeout. Pure per-env map; no atomicAdd, no reduction. Launch: grid(ceil(N/256)), block(256). Registered in build.rs. Cubin compiles clean. Currently dead code — launcher wireup comes in Phase A3+ commits. See docs/plans/2026-05-14-sp22-h6-vNext-trade-outcome-aux.md for the full vNext architecture. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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jgrusewski
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d0c037a3d2 |
feat(sp22): H6 Phase 3 FALSIFIED + vNext spec (trade-outcome aux head)
Decisive smoke train-xrkb7 @
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jgrusewski
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ebc7144434 |
feat(sp22): H6 Phase 3 RE-ACTIVATED with corrected aux head
Smoke train-8zwtf @
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jgrusewski
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465abc7e9b |
fix(sp14): dial back aux head/trunk enlargement after L40S OOM
Initial 8x head + 2x trunk-H2 (commit
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jgrusewski
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787ee7b86c |
feat(sp14/sp22): enlarge aux head + trunk capacity (8x head, 2x trunk-H2)
After Path C confirmed aux head's 28% accuracy at H=60 is the H6 Phase 3 bottleneck (not the mechanism itself), enlarge aux capacity: - AUX_HIDDEN_DIM: 32 -> 256 (8x, matches input dim, removes bottleneck) - AUX_TRUNK_H2: 128 -> 256 (2x, uniform trunk width) Architecture changes: - Aux head: 256 -> Linear -> 256 -> ELU -> Linear -> 2 (was 256->32->2) - Aux trunk: 256 -> 256 -> 256 -> 256 (was 256 -> 256 -> 128 -> 256) - +160K params total (mostly aux_nb_w1 + aux_rg_w1: [256, 256] each) Side effects: - Checkpoint fingerprint change (intentional) - Thread utilisation improves: AUX_BLOCK=256 threads x H=256 = 1:1 (vs 8:1 at H=32 — most threads idle previously) Phase 3 mechanism stays DORMANT (W=0, beta=0) for this validation smoke. Verdict criteria: aux_dir_acc improves from 0.28 toward 0.50+ with the larger capacity. If yes, re-activate Phase 3 priors. If no, the bottleneck is signal/horizon, not capacity. Cargo build clean (full nvcc rebuild). Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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jgrusewski
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2c0911981a |
feat(sp22): H6 Phase 3 DORMANT - mechanism falsified, infrastructure preserved
Path C investigation revealed the aux head at epoch 1 is severely
anti-predictive at H=60 bars:
- Aux predicts UP 83% of the time
- Labels are 17% UP, 83% DOWN
- Accuracy = 28% (vs 50% random)
This means H6 Phase 3 hypothesis cannot help WR — atom-shift on an
anti-predictive signal produces no discriminative bias. Confirmed by
full-mechanism smoke at
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jgrusewski
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b4e26a3b45 |
feat(sp22): H6 Phase 3 α/β — RESTORE structural priors
Verification smoke train-5t6vb @ |
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jgrusewski
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79945987a5 |
fix(sp22): W-read guards across ALL atom-shift kernels
Verify smoke train-t5885 partial result: dir CLEAN, mag NaN. The isfinite(W) guard added in compute_expected_q didn't extend to the other atom-shift consumers. Adam-corrupted W propagates through them via 0*NaN=NaN. Adds isfinite(w_aux[a]) guards to all atom-shift kernels: - mag_concat_qdir - quantile_q_select - c51_loss_kernel (eq_per_action shift + effective_reward W[a0]/W[best_next_a]) Also strengthens c51_aux_dw_kernel: guard sp/isw/dz/gamma/done (not just dz<1e-7 which doesn't catch NaN). Any NaN/Inf input -> skip sample (no dW contribution). Defense-in-depth complete: NaN cannot propagate through any atom-shift path regardless of source. Cargo check clean. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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jgrusewski
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57cf5c1e08 |
fix(sp22): defensive NaN guards on Step 8/11 dW + Adam path
Bisect cut #1 (train-6zbcn) DEFINITIVELY identified Step 8/11 as the NaN source. With launches disabled, q_var/q_by_action/v_a_means all CLEAN. Forward atom-shift kernels confirmed innocent. Defensive fix (belt-and-suspenders): 1. c51_aux_dw_kernel: clamp NaN/inf total to 0 at dW write site. 2. adam_w_aux_kernel: early-return if any input non-finite. 3. compute_expected_q: guard w_aux[a] read with isfinite (in addition to state_121). Together these prevent any NaN propagation through atom-shift regardless of where the upstream NaN originated. Step 8/11 launches RESTORED in submit_adam_ops. The underlying NaN source is still unidentified but defensively neutralised. Smoke verification next. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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jgrusewski
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a1945de031 |
bisect(sp22): disable Step 8/11 launches (c51_aux_dw + adam_w_aux)
User-requested static-analysis-first bisect (Option 2): comment out both launch_c51_aux_dw and launch_adam_w_aux in submit_adam_ops to isolate forward vs backward as NaN source. With these disabled: - Forward atom-shift kernels still run (no-op with W=0) - W stays at [0,0,0,0] (no Adam update) - dW kernel doesn't run Hypothesis test: - Clean smoke -> backward is the bug - NaN persists -> forward is the bug Audit doc updated. Cargo check clean. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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jgrusewski
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a683c4bc52 |
fix(sp22): defensive NaN guard on state_121 reads in atom-shift kernels
Root cause: IEEE-754 rule 0 * NaN = NaN defeats W=0 safety. Two smokes proved the bug propagates regardless of W magnitude — pattern identical at W=[-0.5,0,+0.5,0] (train-th8pj) and W=[0,0,0,0] (train-gs4gx). The state_121 = batch_states[i * state_dim + 121] read in 4 atom-shift kernels can contain NaN (upstream source: aux head softmax producing NaN at some rollout step, stored in replay buffer, sampled into trainer's batch). 0 * NaN = NaN propagates through all atom-shift arithmetic. Defensive fix: guard each state_121 read with isfinite check, fallback to 0 if NaN/inf. Applies to: - compute_expected_q (experience_kernels.cu) - mag_concat_qdir (experience_kernels.cu) - quantile_q_select (experience_kernels.cu) - c51_loss_batched (c51_loss_kernel.cu) — state_121 AND next_state_121 - c51_aux_dw_kernel (s121 AND ns121) This unblocks Phase 3 mechanism validation. The actual state_121 NaN source (aux head or state assembly) is to be investigated separately. Cargo check clean. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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jgrusewski
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617eb61aab |
diagnostic(sp22): zero W prior + beta prior to isolate NaN source
First smoke at
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jgrusewski
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ff98edc774 |
fix(sp22): H6 Phase 3 beta - activate via 0.5 structural prior (B6-minimal)
Bug: state_reset_registry has FoldReset entries for sp22_reward_aux_align_ema
and sp22_aux_align_scale, but reset_named_state dispatch had no matching arms
-> unknown name error at first fold boundary with these registry entries.
Latent in
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jgrusewski
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5106e3b117 |
feat(sp22): H6 Phase 3 α Phase C1 — collector W ptr setter
Wires the trainer's `w_aux_to_q_dir [4]` device pointer into the GpuExperienceCollector so rollout-time action selection sees the active atom-shift for the direction branch. Changes: - gpu_experience_collector.rs: new field aux_w_to_q_dir_dev_ptr (u64, default 0) + setter set_aux_w_to_q_dir_ptr(). Both rollout launchers (compute_expected_q + quantile_q_select) now pass W ptr + exp_states_f32 + STATE_DIM_PADDED instead of NULL placeholders. NULL-safe via the kernels' existing aux_shift_active gating. - gpu_dqn_trainer.rs: w_aux_to_q_dir field promoted to pub(crate) for cross-module access via raw_ptr(). - trainers/dqn/trainer/training_loop.rs: new wire-up block after SP15 warm-count setter, mirroring the established setter pattern. NULL-safe on test scaffolds where fused_ctx or collector is absent. End-state — rollout activation: - compute_expected_q + quantile_q_select now return shifted E[Q] / quantile-blends per direction action during rollout. - With trainer's W trained each step (Step 8+11 Adam), the rollout policy's direction-action distribution actively reflects the learned aux→policy coupling. state_121's per-env value drives a per-(env, action) bias of magnitude W[a] (≤0.5 initial prior, learned thereafter). Verification: cargo check -p ml --lib clean (0 errors, 21 pre-existing warnings). Trainer + collector now smoke-ready end-to-end for the trainer/rollout side. Eval-side activation pending Phase D. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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jgrusewski
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5d163e0e1d |
feat(sp22): H6 Phase 3 α — adaptive W via dW backward + Adam (B9 Steps 8+11)
Step 8 — c51_aux_dw_kernel (new):
- Per-action block tree-reduce: grid=(4,1,1), block=(256,1,1). One block
per W index a, tree-reduces dW[a] across batch via warp shuffle + shmem.
Zero atomicAdd per pearl_no_atomicadd.
- Per-sample contributions:
a == a_d: dW[a] += inv_batch × isw × (SP_b/dz) × state_121
a == a*: dW[a] += inv_batch × isw × (-γ(1-done)) × (SP_b/dz) × next_state_121
c51_loss_kernel forward — new scratch outputs:
- aux_target_a_dir_buf[B] (i32): saves best_next_a for d==0 after Step c
sampling.
- aux_proj_logdiff_dir_buf[B] (f32): saves SP_b = Σ_n p_target_n ×
(current_lp[upper_n] - current_lp[lower_n]) after Step d's projection
via re-derivation of lower_n/upper_n (matching Huber compression +
clamp arithmetic of block_bellman_project_f).
Step 11 — adam_w_aux_kernel (new):
- Standard Adam with bias correction, grid=(1,1,1), block=(4,1,1).
- Graph-capture-safe: lr via self.lr_dev_ptr pointer arg; step via
self.ptrs.t_buf pointer arg (matches main Adam pattern). beta/eps
as value args from sp5_isv_slots constants.
- Bias-correction denominator floored at 1e-30 to avoid /0.
Trainer wiring (submit_adam_ops):
- launch_c51_aux_dw + launch_adam_w_aux added right after
launch_adam_update. Both inside the captured adam_child graph.
- New trainer fields: aux_target_a_dir_buf, aux_proj_logdiff_dir_buf,
c51_aux_dw_kernel, adam_w_aux_kernel. Cubin statics SP22_C51_AUX_DW_CUBIN
+ SP22_ADAM_W_AUX_CUBIN added.
NULL-safety:
- aux_shift_active=false in c51_loss_kernel forward → both scratch
buffers stay at alloc_zeros 0 → dW reads 0 → Adam W is a no-op.
- aux_target_a_dir_out / aux_proj_logdiff_dir_out are NULL-tolerant.
Deferred (deliberate scope):
- dL/dstate_121 backward (c51 → aux head): refinement, not correctness;
aux head trains via own supervised CE loss.
- Phase C1 collector W ptr setter.
- Phase D (eval-side aux infrastructure).
Verification:
- cargo build -p ml --lib: 0 errors, 21 pre-existing warnings.
- nvcc full recompile clean (1m05s for sm_89 target).
- All forward atom-shift consumers + adaptive W backward + Adam now wired.
End-state: adaptive W trains from structural prior [-0.5, 0, +0.5, 0]
via projection log-diff gradient. Aux head trains independently via
supervised CE. Together they form learned cross-coupling from aux
direction predictions to dir-branch Q distribution shifts. Smoke can
now measure adaptive W's effect on WR.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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jgrusewski
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a98f299823 |
feat(sp22): H6 Phase 3 α — atom-shift forward-side complete (B9 Steps 7+9+10)
Steps 7+9+10 land all FORWARD-path consumers of atom positions:
Step 7 — c51_loss_kernel atom-shift threading:
- 5 new args (w_aux, batch_states, next_batch_states, aux_dir_prob_index,
state_dim). NULL-safe — any NULL collapses to 0 shift, bit-identical
to pre-Phase-3-α.
- Per-sample state_121 + next_state_121 hoisted once at top of kernel.
- eq_per_action[a] += W[a]*next_state_121 in dir branch (d==0) before
Expected SARSA target-action sampling. Biases a* toward aux-aligned.
- Bellman projection: effective_reward = reward + γ*Δ_target*(1-done)
- Δ_online substituted for reward in block_bellman_project_f call.
Math derivation: see prior commit
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jgrusewski
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195c051e7a |
feat(sp22): H6 Phase 3 α — atom-shift wired through compute_expected_q (B9 Step 5+6)
W structural prior init kernel (Step 5): - aux_w_prior_init_kernel.cu: 4-thread one-time init writing W[a] = [-0.5, 0.0, +0.5, 0.0] (Short / Hold / Long / Flat). Hardcoded values in kernel — no HtoD per feedback_no_htod_htoh_only_mapped_pinned.md. - build.rs registration + gpu_dqn_trainer.rs cubin static + handle field + new() launch after alloc_zeros for w_aux_to_q_dir. compute_expected_q atom-shift (Step 6): - experience_kernels.cu signature grows 4 args (w_aux, batch_states, aux_dir_prob_index, state_dim). NULL-safe — collapses to 0 shift when either pointer is NULL, bit-identical to pre-Phase-3-α. - Per-action inner loop computes aux_atom_shift = w_aux[a] * state_121 once per (b, a) for d==0 only. Inner z-loop applies z_val += aux_atom_shift before all S/TZ/TZ²/TLM accumulators consume it. Launcher updates (3 trainer sites + 1 collector site): - populate_q_out: passes W + current states (online path). - replay_forward_for_q_values: passes W + current states (online replay). - compute_denoise_target_q: passes W + next_states (target on s'; W shared across online/target). - gpu_experience_collector.rs: passes NULL W + NULL states until Phase C1 wires the trainer's W ptr through a setter. Architectural notes: - Action selection (every compute_expected_q call) now uses shifted atom positions for direction branch (d==0). Other branches stay bit-identical (shift = 0). Step 7 (c51_loss_kernel) + Step 8 (c51_grad_kernel) will close the loop on training loss + W gradient in the same atomic commit to avoid the gradient mismatch trap per feedback_no_partial_refactor.md. - Adam wireup for w_aux_to_q_dir lands at Step 11; until then W stays at structural prior values (no Adam step modifies it). Verification: - cargo check -p ml --lib: 0 errors, 21 pre-existing warnings (Phase 3b baseline parity). - Audit doc updated with B9 Step 5+6 checkpoint entry. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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jgrusewski
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08fd5803c4 |
refactor(sp22): H6 Phase 3 α cleanup + runbook revision for atom-shift design
Same-session cleanup of Phase 3b scalar-bias residue (commit cb80b74ce's
additions that became architecturally redundant under the 2026-05-13
atom-shift revision). The scalar-bias α design is mathematically
ineffective in C51 distributional Q-learning (softmax-shift-invariance
→ W gradient = 0 → never trains). The revised design threads
`aux_atom_shift[b, a] = W[a] * state_121[b]` through compute_expected_q
+ c51_loss_kernel + c51_grad_kernel + mag_concat_qdir; dW + dstate
gradients integrate into c51_grad_kernel's projection backward.
Files
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- crates/ml/build.rs:
Removed `aux_to_q_dir_bias_kernel.cu` + `aux_to_q_dir_bias_backward_kernel.cu`
from kernels_with_common. Replaced with comment block documenting
C51 softmax-invariance reason + spec/audit pointers.
- crates/ml/src/cuda_pipeline/gpu_dqn_trainer.rs:
Removed `pub(crate) static SP22_AUX_TO_Q_DIR_BIAS_CUBIN` and
`SP22_AUX_TO_Q_DIR_BIAS_BWD_CUBIN` static declarations.
Removed 3 struct fields (aux_to_q_dir_bias_kernel,
aux_to_q_dir_bias_backward_dw_kernel,
aux_to_q_dir_bias_backward_dstate_kernel) and their new()
loading blocks + struct construction entries.
KEPT: w_aux_to_q_dir + adam_m_w_aux + adam_v_w_aux + dw_aux_buf
(still needed for atom-shift Adam-trained W).
Updated W doc-comment to describe atom-shift threading (was
scalar-bias) and structural-prior initialization `[-0.5, 0.0,
+0.5, 0.0]`.
- crates/ml/src/cuda_pipeline/aux_to_q_dir_bias_kernel.cu +
crates/ml/src/cuda_pipeline/aux_to_q_dir_bias_backward_kernel.cu:
Source files stay on disk as committed dead code (commit
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jgrusewski
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cb80b74ce9 |
feat(sp22): H6 Phase 3b — α infrastructure loaded (NOT yet wired)
Phase 3b builds on Phase 3a ( |
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jgrusewski
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2e4c7ebf60 |
feat(sp22): H6 Phase 3a — 7-component contract migration + β producer (WIP)
Phase 3a builds on the Phase A foundation ( |
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jgrusewski
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464bc5f7a4 |
feat(sp22): H6 Phase 3 — Phase A foundation (WIP checkpoint, additive)
Phase A of the SP22 H6 Phase 3 implementation runbook
(docs/plans/2026-05-13-sp22-h6-phase3-alpha-beta-runbook.md). Purely
additive: new ISV slots + new kernel files + build.rs registration
+ state_reset_registry entries. Nothing in the running training or
eval pipeline consumes this infrastructure yet — the existing
6-component contract is untouched. Phase A is committable as a clean
WIP foundation; Phases B-F (7-component contract migration, α
plumbing, A2 eval-side wiring, verification, smoke) resume in a
future session.
Files
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- crates/ml/src/cuda_pipeline/sp22_isv_slots.rs (NEW)
REWARD_AUX_ALIGN_EMA_INDEX = 536 — EMA of 7th reward component
SP22_AUX_ALIGN_SCALE_INDEX = 537 — SP11-controller scale_β
- crates/ml/src/cuda_pipeline/gpu_dqn_trainer.rs
ISV_TOTAL_DIM bumped 536 → 538 (SP22 H6 Phase 3 +2 slots)
Layout fingerprint extended with SLOT_536 + SLOT_537 entries
- crates/ml/src/cuda_pipeline/mod.rs
pub mod sp22_isv_slots
- crates/ml/src/trainers/dqn/state_reset_registry.rs
sp22_reward_aux_align_ema (FoldReset, sentinel 0)
sp22_aux_align_scale (FoldReset, sentinel 0)
- crates/ml/src/cuda_pipeline/aux_to_q_dir_bias_kernel.cu (NEW)
α forward: Q_dir[b, a] += W_aux[a] * state_121[b]
Reads state_121 from encoder INPUT (batch_states), bypassing
the cold encoder weight for slot 121. No atomicAdd, no host
branches, capture-safe.
- crates/ml/src/cuda_pipeline/aux_to_q_dir_bias_backward_kernel.cu (NEW)
Two kernels in one .cu:
- aux_to_q_dir_bias_backward_dw: per-action block tree-reduce
computing dW[a] = Σ_b state_121[b] * dq_dir[b, a]
- aux_to_q_dir_bias_backward_dstate: per-sample sum
dstate_121[b] += Σ_a W[a] * dq_dir[b, a] (option-(i) gradient
routing: both α and encoder paths get signal)
- crates/ml/build.rs
Both new cubins registered in kernels_with_common (compiled
successfully by nvcc; cubins exist at OUT_DIR/aux_to_q_dir_bias_*.cubin)
- docs/dqn-wire-up-audit.md
Phase A entry documenting the checkpoint + remaining-work
breakdown for next session.
Verification
────────────
- cargo check -p ml --features cuda: 0 errors, 21 pre-existing
warnings (Phase 2 baseline parity)
- nvcc compiles both new cubins (3.6 KB fwd, 10.6 KB bwd)
- No runtime impact: no consumer wires the new infrastructure yet
Resumes in
──────────
Future session executes Phases B-F per the runbook:
- B: 11 tasks — 7-component contract migration cascade
- C: 1 task — α collector rollout-side wiring
- D: 7 tasks — A2 eval-side aux trunk + α + state-gather
- E: 7 tasks — verification gates
- F: 5 tasks — audit doc append + atomic commit (incl. this Phase A
+ Phase B-F changes) + push + smoke + verdict
Estimated remaining: ~28-43 hr engineering + ~37 min smoke wall-clock.
Phase B partial work (300-line diff for experience_kernels.cu + reward_component_ema_kernel.cu — 7-stride migration + β producer + preamble update) saved at /tmp/sp22-h6-phase3-b-partial.patch (local-only).
Refs
────
- docs/plans/2026-05-12-sp22-h6-phase3-alpha-beta.md (spec)
- docs/plans/2026-05-13-sp22-h6-phase3-alpha-beta-runbook.md (runbook)
- pearl_no_partial_refactor (Phase A is additive; safe to commit alone)
- pearl_no_atomicadd (backward block tree-reduce, no atomics)
- pearl_no_host_branches_in_captured_graph (kernel capture-safety)
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
|
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jgrusewski
|
71eab9a253 |
fix(tests): gpu_backtest_validation action constants — Long100 is 72, not 4
Two `gpu_backtest_validation` tests were failing with bit-identical
deterministic values for 2+ months: `test_always_long_on_downtrend`
(expected negative PnL, got +0.00023627281) and
`test_multiple_windows_produce_results` (uptrend < downtrend instead
of > ).
Root cause: SP21 Phase 8.5 (2026-05-12) wired the factored 4-3-3-3
action decoder into the eval (`backtest_state_gather` + env_step),
but the test's hardcoded `constant_action_model(4, ...)` integer
literal wasn't migrated. Pre-Phase-8.5 the eval used a flat
4-action enum where `4` reportedly meant Long100; the factored
decoder now interprets `4` as:
decode_direction_4b(4, b1=3, b2=3, b3=3) = 4 / 27 = 0 = DIR_SHORT
decode_magnitude_4b(4, b1=3, b2=3, b3=3) = (4/9) % 3 = 0 = MAG_QUARTER
So the test was running Short-Quarter (-0.25 position) on the trend
fixtures. On random-walk synthetic prices with drift ±0.001 vs σ=0.01
noise per bar, the 24-step eval window has S/N ≈ 0.49 — specific
seeds can produce net-against-drift trajectories, making the actual
short-quarter PnL small but deterministic, with sign flipped relative
to test intent.
Fix: change `constant_action_model(4, ...)` → `constant_action_model(72, ...)`
in the 2 failing tests. Action 72 = dir=LONG (2) * 27 + mag=FULL (2)
* 9 + 0 + 0 — the actual "Long100" under 4-3-3-3 factoring. Both
tests now pass; no regressions on the 4 previously-passing tests.
Verification
────────────
- gpu_backtest_validation pre-fix: 4 passed, 2 failed
- gpu_backtest_validation post-fix: 6 passed, 0 failed
Out of scope for this commit (follow-up audit needed)
─────────────────────────────────────────────────────
Three other tests in the same file have the same stale `4` constant
with misleading "Always Long100" comments, but currently pass
incidentally:
- `test_always_long_on_uptrend` (line 218): asserts `total_pnl > 0`.
Currently passes BY ACCIDENT — action=4 (Short-Quarter) on seed-42's
net-down 24-bar trajectory produces +PnL, satisfying the assertion
for the wrong reason. Fixing to action=72 alone would break this
test (true Long100 on seed-42's net-down trajectory is negative);
the test needs BOTH the action fix AND a seed/window change so the
"uptrend" trajectory actually trends up over the eval window
(e.g., 250-bar window or drift=0.01).
- `test_extended_metrics_populated` (line 465) and
`test_active_model_records_trades` (line 524): assertions are
direction-agnostic (VaR/CVaR/Calmar/Omega NaN-check + CVaR≤VaR;
total_trades > 0 + win_rate range), so they pass legitimately
under whatever-direction action=4 produces. The "Long100" comments
are misleading but the tests are correctly covering their stated
behavior.
A separate audit-and-fix pass should address all three at once:
either correct the action constants + adjust seed/window to ensure
each test's named trajectory direction is statistically reliable,
or introduce a named constant (e.g., LONG100_ACTION) and helper to
prevent the same drift recurring.
Refs
────
- SP21 T2.2 Phase 8.5 commit
|
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jgrusewski
|
f9192f70a5 |
feat(sp22): H6 Phase 2 — recenter state[121] to [-1, +1] (atomic)
Phase 1 post-mortem traced an actual `pearl_first_observation_bootstrap` violation in my own H6 implementation: state slot 121 wrote `aux_softmax[env, 1] = p_up ∈ [0, 1]` with sentinel 0.5, but every OTHER state slot uses 0 as the "no signal" baseline (zero-padding, feature_mask, ofi-missing, mtf-missing). The encoder had to learn TWO things about slot 121 (directional mapping + non-zero bias offset) instead of one. Phase 2 fixes the encoding to match the project convention BEFORE declaring H6 fully falsified. Mechanism change ──────────────── - `aux_softmax_to_per_env_kernel.cu` writes `2*p_up - 1 ∈ [-1, +1]` instead of `p_up`. Still structurally bounded (softmax components in [0, 1] sum to 1). - Cold-start + FoldReset sentinel: 0.5 → 0.0 via the same pure-GPU `fill_f32` path. No HtoD per `feedback_no_htod_htoh_only_mapped_pinned`. - NULL-fallback in 3 state-gather kernels (training + backtest-per-step + backtest-chunk): 0.5f → 0.0f. - Constant + device-function comment updates to document the recentered encoding. Atomic per `feedback_no_partial_refactor`: the encoding contract spans 5 source files; partial migration produces inconsistent slot semantics between training and eval. Verification gates (all clean) ────────────────────────────── - cargo check -p ml --features cuda: 0 errors, 21 pre-existing warnings (parity with Phase 1 baseline) - gpu_backtest_validation: 4/4 expected-passing tests still pass; 2 pre-existing PnL-assertion failures bit-identical to Phase 1 (confirms recentering does not perturb scripted-policy paths) - compute-sanitizer --tool=memcheck: ERROR SUMMARY: 0 errors Smoke dispatch deferred pending an orthogonal investigation into the 2 pre-existing gpu_backtest_validation failures (stale action constants in the tests; addressed in a follow-up commit, NOT a Phase 2 regression). Verdict criteria (per spec, evaluated after smoke) ────────────────────────────────────────────────── - WR > 50.5% within 3 epochs → recentering binding, H6 + Phase 2 sufficient → justify A2. - a_var for mag/ord/urg > 1e-3 → sub-branches gradient-coupled under recentered signal. - WR pinned at 50.1–50.2% → Phase 2 falsified, pivot to amplitude scaling or deeper hypothesis. Refs ──── - docs/plans/2026-05-12-sp22-h6-phase2-recenter.md (spec) - docs/plans/2026-05-12-sp22-h6-phase2-recenter-runbook.md (this plan) - pearl_first_observation_bootstrap (sentinel = 0) - feedback_no_partial_refactor (5-file atomic) - feedback_no_htod_htoh_only_mapped_pinned (fill_f32, not HtoD) Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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jgrusewski
|
7fc9799343 |
feat(sp22): H6 Phase 1 — aux→policy state bridge (atomic)
Wires the aux head's per-env directional probability into policy STATE
slot 121 (AUX_DIR_PROB_INDEX = PADDING_START + 0), preserving the trunk-
separation invariant from `pearl_separate_aux_trunk_when_shared_starves`.
H1 (label horizon) confirmed aux learns 78% dir-acc within-fold at H=200
but the policy was walled off; this commit conducts that signal through
the state input with a one-step lag.
Mechanism (rollout-time, collector-only)
────────────────────────────────────────
- State[env, t] reads `prev_aux_dir_prob[env]` (= p_up from step t-1).
- After aux forward at step t, the new copy kernel writes
`aux_softmax[env, 1]` → `prev_aux_dir_prob[env]` for step t+1.
- Cold-start + FoldReset seed the buffer to 0.5 (neutral; p_up = 50%)
via the pure-GPU `fill_f32` kernel — no HtoD per
`feedback_no_htod_htoh_only_mapped_pinned.md`.
- Launch sits in the same `isv_signals && trainer_params != 0` gate as
the aux forward, so when aux is skipped the cache keeps its previous
(sentinel or last-good) value instead of copying stale `alloc_zeros`.
Three state-gather kernels updated atomically (per
`feedback_no_partial_refactor.md`):
- `experience_state_gather` — training, reads `aux_dir_prob_per_env[i]`
- `backtest_state_gather` — eval (single-step), NULL → 0.5 (A3 fallback)
- `backtest_state_gather_chunk` — eval (chunked), NULL → 0.5 (A3 fallback)
`assemble_state` gained a 7th param `float aux_dir_prob` written to
`out[SL_PADDING_START + 0]`; the remaining 6 padding slots stay zero
for 8-alignment.
Phase 1 scope = training-side + eval A3 NULL fallback. A2 (aux trunk
forward in eval) is deferred per the runbook — gates on whether the
smoke moves WR off the 50.1–50.2% plateau.
New files
─────────
- crates/ml/src/cuda_pipeline/aux_softmax_to_per_env_kernel.cu
Modified
────────
- crates/ml-core/src/state_layout.rs (+AUX_DIR_PROB_INDEX)
- crates/ml/src/cuda_pipeline/state_layout.cuh (+assemble_state param)
- crates/ml/src/cuda_pipeline/experience_kernels.cu
(3 state-gather kernels + NULL-defensive sentinel)
- crates/ml/src/cuda_pipeline/gpu_experience_collector.rs
(per-env buffer + 2 kernel handles + cold-start fill + copy launch
+ FoldReset re-fill + state-gather arg)
- crates/ml/src/cuda_pipeline/gpu_backtest_evaluator.rs
(NULL aux_dir_prob_per_env at all 3 launchers for A3)
- crates/ml/src/cuda_pipeline/gpu_dqn_trainer.rs
(SP22_AUX_SOFTMAX_TO_PER_ENV_CUBIN static)
- crates/ml/src/cuda_pipeline/gpu_action_selector.rs
(EPSILON_GREEDY_CUBIN → pub(crate) so collector reuses fill_f32)
- crates/ml/build.rs (register new kernel)
- docs/dqn-wire-up-audit.md
(## 2026-05-12 — SP22 H6 implementation: Phase 1 entry)
Verification (all three gates clean, no smoke yet)
──────────────────────────────────────────────────
- cargo check -p ml --features cuda: 0 errors
- gpu_backtest_validation: 4/4 expected-passing tests still pass
(the 2 PnL-assertion failures are pre-existing per the runbook)
- compute-sanitizer --tool=memcheck: 0 CUDA errors
Refs
────
- docs/plans/2026-05-12-sp22-h6-aux-policy-state-bridge.md
- docs/plans/2026-05-12-sp22-h6-next-session-prompt.md
- pearl_separate_aux_trunk_when_shared_starves
- pearl_first_observation_bootstrap (sentinel = 0.5 cold-start)
- feedback_no_htod_htoh_only_mapped_pinned (fill_f32 not HtoD)
- feedback_no_partial_refactor (3 state-gather kernels atomic)
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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jgrusewski
|
e8814079d9 |
Revert "experiment(sp22): H1 — pin aux pred horizon at 200 bars (atomic)"
This reverts commit
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jgrusewski
|
9adbca8262 |
experiment(sp22): H1 — pin aux pred horizon at 200 bars (atomic)
Hypothesis test for SP22 H1 (label horizon mismatch). Finding from v9/v10 HEALTH_DIAG: aux_dir_acc=28-47% (BELOW RANDOM) across all observed cycles. Root cause: adaptive aux_horizon_update collapses H back to ~1.7 bars (observed avg winning hold time), making the aux label HFT microstructure noise. Experiment: 1. Bump SENTINEL_AUX_PRED_HORIZON_BARS 60.0 → 200.0 2. Disable launch_aux_horizon_chain call so H stays at sentinel Predicted: if aux_dir_acc rises >50% → H1 confirmed; if stays ≤50% → escalate to H2/H4 per SP22 plan. Cost: 1 smoke ~30min, kill early on cycle 1-2 trend. Files changed: - crates/ml/src/cuda_pipeline/sp14_isv_slots.rs - crates/ml/src/trainers/dqn/trainer/training_loop.rs - docs/dqn-wire-up-audit.md (H1 experiment entry) Reverts if H1 falsified. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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jgrusewski
|
d482efc416 |
fix(sp21): T2.2 Phase 8.4-fix — winner-concentration z-score separation (atomic)
v8 smoke (train-96wfk) confirmed win_conc=0.0000 across all 9 cycles
even when PF crossed 1.0. The Phase 8.2/8.4 threshold tweaks couldn't
fix it because the underlying formula `top_mean / all_mean` is
sign-unstable around `all_mean=0`. PER alpha boost path was dark for
any cold-start policy below PF=1 — exactly the regime where the
boost matters most.
Old: if all_mean ≤ (0.01 * pnl_std).max(0.0) { return 0.0; }
top_mean / all_mean
→ guard trips at PF≤1 → 0.0 (every v8 cycle)
New: ((top_mean - all_mean) / pnl_std).max(0.0)
→ z-score separation: how many pnl_stds above the overall mean
does the top decile sit? By construction top_mean ≥ all_mean,
so separation is non-negative even when all_mean is negative.
→ bounded [0, ∞), scale-invariant, profitability-agnostic.
Expected v9 magnitudes (v8 cycle-1-like inputs):
top_mean ≈ 5e-6, all_mean ≈ 1e-7, pnl_std ≈ 1.08e-5
separation = (5e-6 - 1e-7) / 1.08e-5 ≈ 0.45
Healthy PF>1 cycles likely 0.2..1.5 range.
Pearls honoured:
- pearl_controller_anchors_isv_driven: pnl_std is the signal-driven
scale anchor (replaces hardcoded all_mean denominator)
- feedback_isv_for_adaptive_bounds: z-score formulation removes the
hardcoded multiplier dependency that motivated 8.2 and 8.4's
threshold adjustments
- feedback_no_quickfixes: structural reformulation, not a threshold
tweak (8.2 and 8.4 already showed threshold tweaks couldn't fix
the sign-instability)
Verification:
cargo check -p ml --features cuda # clean
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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jgrusewski
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9f2d0fffb5 |
fix(sp21): T2.2 Phase 8.7 — default ISV buffer in evaluator (atomic)
v8 smoke (train-96wfk, commit
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jgrusewski
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cb7ace0063 |
feat(sp21): T2.2 Phase 8.6 — curriculum weights via z-score exp(-sharpe) (atomic)
v8 smoke (train-96wfk, commit
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jgrusewski
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5694eb4df2 |
fix(sp21): T2.2 Phase 8.5 — wire factored-action branch sizes into closure-based eval (atomic)
v7 smoke (train-fv4s8, commit
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jgrusewski
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5186701982 |
feat(sp21): T2.2 Phase 8.4 — v6 loose ends (win_conc / curric_conc / hindsight_mag display) (atomic)
Three targeted fixes for v6 smoke (train-x4m96) findings that Phase 8.2
left on the table. v6 cycle-by-cycle showed `win_conc=0.0000` and
`curric_conc=0.0000` pinned across all 9 cycles, and `hindsight_mag`
printed `0.0000` due to format-width rounding.
Fix 1: compute_winner_concentration guard threshold 0.1 → 0.01 × pnl_std
v6 had pnl_std ≈ 1e-5 and val-trade all_mean ≈ 1e-7..1e-6. At 0.1×
the threshold was 1e-6, still above typical all_mean → short-circuit
fired every cycle. At 0.01× (threshold 1e-7) healthy small-but-positive
policies emit a non-zero signal; degenerate-strategy guard preserved.
Fix 2: compute_curriculum_concentration formula
Was: 1 - entropy(weights) / log(n) (entropy-deficit, normalized)
Now: CV(weights) / sqrt(n − 1) (normalized coefficient of variation)
Entropy-deficit is ~weight_std² near uniform. v6's 8 contiguous segments
had per-segment Sharpes in a tight band, so normalized weights stayed
within ~0.5% of 1/n and deficit collapsed to <1e-4 (only cycle 9
reached 0.0001). CV scales linearly with weight_std/weight_mean,
dramatically more sensitive in the near-uniform regime. Cold-start
(uniform) still returns 0; one-hot returns 1.
Fix 3: hindsight_mag display format {:.4} → {:.2e}
pnl_std ≈ 1e-5 on volume bars → hindsight magnitudes are similar scale,
printed as 0.0000 under {:.4} even when the count is non-zero. Matches
pnl_std={:.2e} format already in the log.
Pearls honoured:
- feedback_isv_for_adaptive_bounds: thresholds derived from pnl_std
- pearl_first_observation_bootstrap: uniform/empty inputs → 0.0 sentinel
- pearl_controller_anchors_isv_driven: CV anchor (one-hot = sqrt(n-1))
is structural, not magic
- feedback_no_quickfixes: entropy → CV is a structural reformulation
Verification:
cargo check -p ml --features cuda # clean
Expected v8 smoke (when dispatched):
- win_conc rises to ~1.5..3.0 (top_decile_mean / all_mean ratio)
- curric_conc enters 0.05..0.20 range as segments develop differential
difficulty; grows toward ~0.4 with overfit divergence
- hindsight_mag prints as 5e-6 or similar (real value, not zero)
If these fire, Phase 7 (alpha boost via E6/E7/E8) is finally exercised
end-to-end on volume bars.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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jgrusewski
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23b89a90e9 |
fix(sp21): T2.2 Phase 8.3+9 — eval pipeline GPU-only, hard-fail, delete CPU path (atomic)
Combined Phase 8.3 (visibility + hard-fail) and Phase 9 (CPU path
removal) per pearl_no_deferrals_for_complementary_fixes. Surfaced by
v6 smoke (train-x4m96) where:
[DQN GPU] Fold 0 GPU eval failed: GpuBacktestEvaluator::evaluate failed
for fold 0. Falling back to CPU path.
[DQN] Fold 0 evaluation failed: Failed to create DQN state tensor for
bar 0: Dimension mismatch: expected 54, got 45
Both fold 0 and fold 1 hit this; workflow exited 0, masking eval
failure for every smoke run since STATE_DIM grew beyond legacy 54.
Root cause (silent GPU failure):
evaluate_dqn_fold_gpu calls evaluator.evaluate(closure, portfolio_dim: 3)
but GpuBacktestEvaluator initialises portfolio_dim = PORTFOLIO_BASE_DIM (8)
+ MTF_DIM (16) = 24 per canonical state layout. gather_states asserts
match → returns MLError::ConfigError. Caller wraps with .with_context()
+ warn!("... {}", e) — `{}` strips anyhow chain, hiding root cause.
The CPU fallback runs with a separate stale 45-dim state builder
(42 from extract_ml_features + 3 portfolio) → fails at GpuTensor::
from_host shape validation against the model's 54-feature default.
Fixes (all atomic):
1. portfolio_dim: 3 → 24 at all 4 call sites (DQN x2, PPO, supervised).
The GPU evaluator's gather_kernel handles full 128-dim state
assembly (Market 42 + OFI 32 + TLOB 16 + MTF 16 + Portfolio 8 +
PlanISV 7 + Padding 7); caller just declares correct portfolio_dim.
2. Surface anyhow chain: {} → {:#} in error messages.
3. Hard-fail on GPU eval failure: anyhow::bail! (no CPU fallback).
Per user directive: "hard fail on gpu panic, cpu path strictly
forbidden should be removed entirely!"
4. DELETE CPU DQN eval path entirely:
- fn evaluate_dqn_fold
- fn build_chunk_states (stale 45-dim state builder)
- fn simulate_chunk_trades
- fn compute_metrics + struct ComputedMetrics
- struct PortfolioState
5. DELETE coupled surrogate-noise machinery:
- struct SurrogateSampler + impl
- fn load_surrogate_marginals
- fn compute_pooled_sharpe
- Surrogate init blocks in main
- ACTION_MARGINALS / POOLED_SHARPE emission blocks
6. DELETE coupled CLI flags:
- --gpu-eval / --no-gpu-eval (GPU mandatory)
- --surrogate-mode, --surrogate-seed, --surrogate-marginals
- --emit-action-marginals, --emit-pooled-sharpe
7. Collapse `if args.gpu_eval { ... }` blocks to direct calls; cleaner
control flow, no gpu_handled tracking.
Pearls honoured:
- feedback_no_cpu_test_fallbacks: GPU oracle only
- feedback_no_partial_refactor: stale CPU layout from pre-STATE_DIM=128 era
- feedback_no_hiding: error chain now visible via {:#}
- feedback_no_legacy_aliases: no deprecated --no-gpu-eval wrapper
- pearl_no_deferrals_for_complementary_fixes: 8.3+9 combined
Files changed:
- crates/ml/examples/evaluate_baseline.rs:
−892 net lines (1066 del, 174 ins; 2817 → 1925)
- docs/dqn-wire-up-audit.md: 2026-05-12 audit entry
Verification:
- cargo check -p ml --example evaluate_baseline --features cuda # clean
- cargo check --workspace --features cuda # clean
- cargo test -p ml --lib --features cuda financials # 7/7
Note: OFI/TLOB/MTF feature-set fidelity is a separate concern. The GPU
gather_kernel handles state assembly; caller currently provides zeroed
OFI (LobBar.ofi = 0.0) and no MTF data. Eval will run, but on degraded
features. Faithful feature wiring deferred to a later Phase once
eval-runs-at-all is validated by v7 smoke.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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jgrusewski
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79d0c53034 |
feat(sp21): T2.2 Phase 8.2 — signal-drive E6/E7/E8 thresholds via pnl_std (atomic)
Three producers in enrichment.rs had hardcoded magnitude thresholds
sized for time-bar trades (per-trade pnl ≈ 1e-3..1e-2). Foxhunt's
volume bars (bars_per_day ≈ 34_496) produce per-trade pnl in
1e-7..1e-5 range, so the constants tripped every cycle:
- compute_winner_concentration: `all_mean <= 1e-6` → win_conc=0
- compute_hindsight_labels: `t.pnl < -0.001` → hindsight count=0
- compute_curriculum_weights: `(1/sharpe).clamp(0.1, 10.0)` →
similar small Sharpes saturate to 10 →
uniform weights → curric_conc=0
Surfaced by smoke v5 (train-vds7r, commit
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jgrusewski
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d1638959d3 |
fix(sp21): Return v3.1 — drop short-rollout guard for volume bars (atomic)
Single-file fix to `compute_epoch_financials`: remove the `if n_returns_f >= bars_per_year` short-rollout fallback that left v2 semantics in place for sub-year rollouts. For Foxhunt's volume bars, `bars_per_day ≈ 34_496` → `bars_per_year ≈ 8.69M`, while a training epoch produces `n_returns ≈ 4.10M`. The guard fired on every production epoch, so the v3 CAGR fix was a no-op. Diagnosis chain: - v3 commit ( |
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jgrusewski
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62b5a50e8b |
fix(eval): shape-mismatch on checkpoint load — read arch from safetensors metadata (atomic)
Smoke v1 (train-grfcw) evaluate phase failed with "Failed to load DQN
checkpoint" for fold 0 and fold 1. MinIO log inspection confirmed
checkpoints WERE saved (1431144 bytes each) — the failure was
eval-side shape mismatch.
Root cause:
- Training uses STATE_DIM=128 (ml_core::state_layout), num_actions=108
(factored b0*b1*b2*b3=4*3*3*3), num_order_types=3,
num_urgency_levels=3.
- evaluate_baseline CLI defaults: --feature-dim=54, --num-actions=5
(legacy from pre-branching DQN era).
- Loading 128-state-dim 108-action checkpoint into 54-feature 5-action
net → tensor shape mismatch → `load_from_safetensors` returned
parse error → `with_context(...)` wrapped it as the generic "Failed
to load DQN checkpoint" message, hiding the actual shape error.
- Both GPU and CPU eval paths hit the same root cause.
Fix:
Both eval paths now call `DQNConfig::from_safetensors_file(&ckpt_path)`
to read architecture-critical fields from the checkpoint's embedded
metadata (state_dim, num_actions, hidden_dims, num_order_types,
num_urgency_levels, dueling_hidden_dim, num_atoms, gamma). Eval-time
fields (LR, epsilon, buffer caps) overridden; hyperopt-derived gamma/
v_min/v_max applied if present in hyperopt config.
Older checkpoints without embedded metadata fall back to CLI-args-built
config + warn! log. All production SP21+ checkpoints embed metadata
via the existing DQNConfig::checkpoint_metadata path.
Files changed:
- crates/ml/examples/evaluate_baseline.rs: shape-aware config for both
dqn_eval_gpu_path (line ~1238) and dqn_eval_cpu_path (line ~1029)
- docs/dqn-wire-up-audit.md: 2026-05-11 audit entry
Verification:
- cargo check -p ml --examples --features cuda: 0 errors
- cargo test -p ml --lib financials: 7/7 (unchanged)
- cargo test -p ml --lib sp21_isv_slots: 4/4 (unchanged)
Behavioral gate: smoke v3 (train-psf86, in-flight on
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jgrusewski
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2937da8898 |
fix(sp21): inflated return + missing best.safetensors at training end (atomic)
Two smoke-driven fixes for issues surfaced by smoke v1 (train-grfcw).
Fix 1: inflated Return (financials.rs)
- Prior `exp(sum(log(1+r_i))) - 1` produced `Return=+8.730e19%` on
~4M step_returns/epoch. Math correct but metric meaningless.
- Fix: ANNUALIZED compounded return (CAGR). For n_returns ≥
bars_per_year, scale log_growth by `bars_per_year / n_returns`
then exp. Short rollouts (tests/warmup) fall back to total
compounded. Clamped to log-space `[-23, +20]` for display sanity.
- Smoke v1 epoch 3 with fix: 24.7% annualized (was +e19%).
- Documented v1→v2→v3 history in comment.
Fix 2: missing dqn_fold{N}_best.safetensors (training_loop.rs)
- Smoke v1 evaluate phase failed with "Failed to load DQN
checkpoint" for fold 0 and fold 1.
- Root cause: async best-worker swallowed errors non-fatally; with
3 epochs and checkpoint_frequency=10, periodic never fired; if
async failed, NO checkpoint existed.
- Fix: guaranteed final save at training end. After async drain,
restore_best_gpu_params + serialize + sync callback(is_best=true).
Idempotent if async already wrote; authoritative if it failed.
All errors here non-fatal (training succeeded; eval reports its
own missing-ckpt at proper boundary).
Files changed:
- crates/ml/src/trainers/dqn/financials.rs: v3 annualized return
- crates/ml/src/trainers/dqn/trainer/training_loop.rs: final save
- docs/dqn-wire-up-audit.md: 2026-05-11 audit entry
Verification (passing):
- cargo check -p ml --tests --features cuda: 0 errors
- cargo test -p ml --lib financials: 7/7
- cargo test -p ml --lib sp21_isv_slots: 4/4
- sp20_aggregate_inputs_test: 12/12
- sp20_phase1_4_wireup_test: 2/2
- sp20_emas_compute_test: 4/4
- sp20_controllers_compute_test: 7/7
- sp21_per_trade_predicted_q_test: 3/3
Total: 39 tests, 0 failures.
Smoke v2 (train-rl5x2) is on commit
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||
|
jgrusewski
|
ad99b79e07 |
feat(sp21): T2.2 Phase 7.5 — E8 curriculum_weights → per-segment PER insert priority boost (atomic)
Closes the "true E8 per-segment PER sampling" deferral from Phase 7.
Phase 7 wired E8's SCALAR concentration to per_update_pa's alpha
boost; Phase 7.5 wires the FULL Vec<f32> of per-segment weights to
per_insert_pa's priority boost.
What lands:
1. 8 new ISV slots [528..536): CURRICULUM_WEIGHT_{0..8}_INDEX.
2. ISV_TOTAL_DIM 528 → 536 (bus extension); fingerprint adds 8 SLOT
entries; CURRICULUM_N_SEGMENTS=8 const + curriculum_weight_index
accessor.
3. per_insert_pa kernel reads isv[528 + seg_id] where seg_id = i % 8
(round-robin segment tag); effective priority × N_SEGMENTS ×
weight[seg_id]. Uniform weights → no-op (× 1.0); cold-start
sentinel → no-op; 0.1× floor against pathological zero-weight
segments preventing sticky exclusion.
4. Producer in training_loop writes 8 ISV slots from
result.curriculum_weights[0..8].
Segment tagging rationale:
- Naïve approach (tag tuples by val-curriculum-segment id) is
infeasible — val and training have separate coordinate systems
(same problem documented in Phase 5+6 audit re E6 winner indices).
- Round-robin via `i % 8` distributes experience-collector's typical
512+ tuple batch evenly across 8 segments. Over time buffer has
equal representation per segment; E8 weights redirect sampling
pressure toward "hard" segments at insert time.
- HEURISTIC mapping (doesn't preserve val-segment semantics) but
consumes the curriculum_weights vector for real PER priority
redistribution — Phase 7.5's stated goal.
Files changed:
- crates/ml/src/cuda_pipeline/sp21_isv_slots.rs: 8 new slot consts
+ N_SEGMENTS + curriculum_weight_index accessor + tests
- crates/ml/src/cuda_pipeline/gpu_dqn_trainer.rs: ISV_TOTAL_DIM bump
+ fingerprint
- crates/ml-dqn/src/per_kernels.cu: per_insert_pa per-segment boost
- crates/ml/src/trainers/dqn/trainer/training_loop.rs: producer wireup
- docs/dqn-wire-up-audit.md: 2026-05-11 audit entry
Verification (passing):
- cargo check -p ml --tests --features cuda: 0 errors
- cargo test -p ml --lib sp21_isv_slots: 4/4 (new curriculum_weight_
index test)
- sp20_aggregate_inputs_test: 12/12
- sp20_phase1_4_wireup_test: 2/2
- sp20_emas_compute_test: 4/4
- sp20_controllers_compute_test: 7/7
- sp21_per_trade_predicted_q_test: 3/3
Total: 35 tests, 0 failures.
SP21 T2.2 cascade — TRULY fully complete (13 atomic commits). Every
enrichment output E1-E8 wires to a real consumer. No remaining
deferrals or hardcoded controller anchors in SP21 T2.2 scope.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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jgrusewski
|
39d4577b77 |
feat(sp21): T2.2 Phase 8.1 — signal-drive agree_thr clamp bounds via val_sharpe_std (atomic)
Closes the last hardcoded anchor in compute_agreement_threshold per
pearl_controller_anchors_isv_driven. Smoke-driven motivation: the
9-cycle smoke run of commit
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||
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jgrusewski
|
1077f1e165 |
feat(sp21): T2.2 Phase 6.5b — hindsight synthetic injection producer wireup (atomic)
Closes Phase 6.5. The consumer-side infrastructure landed in 6.5a (val state retention + accessor); this commit adds the producer. What lands: 1. GpuReplayBuffer::insert_synthetic_via_pinned (ml-dqn) — raw-u64 dev_ptr mirror of insert_batch's scatter pipeline + per_insert_pa. Takes 7 device pointers + count; bridges from mapped-pinned scratch (in ml crate) to PER's scatter kernels. 2. HindsightScratch struct + MAX_SYNTHETIC_HINDSIGHT=32 constant in enrichment.rs. Holds 7 mapped-pinned buffers (states + next_states + actions + rewards + dones + aux_sign + aux_conf), lazy-allocated. 3. hindsight_scratch: Option<HindsightScratch> trainer field. 4. async fn inject_hindsight_experiences trainer helper: looks up val state at (window_index, bar_index) via 6.5a's read_retained_state, encodes factored action (dir × 27 + mag × 9 + 0 × 3 + 1 for Market/Normal defaults), maps optimal_direction to aux_sign (-1/0/+1), writes reward = counterfactual_pnl, done = 1.0 (terminal), aux_conf = 0.0, calls insert_synthetic_via_pinned. 5. Hook in post-enrichment block — non-fatal warn on infrastructure errors per feedback_kill_runs_on_anomaly_quickly. Design choices: - Terminal done=1: Bellman target reduces to target_q = reward. Avoids synthesizing a valid next_state (optimal counterfactual action would produce a DIFFERENT next state, unsimulable from val data alone). Pure value-target injection at (state, action). - Cap at 32 synthetic per epoch: prevents domination of PER buffer. Scratch alloc ≈ 30 KB pinned host RAM total. - Reward in pnl units: counterfactual_pnl is fraction-of-equity; training reward kernel handles natively (PopArt normalizes). Future scaling via ISV[PNL_REWARD_MAGNITUDE_EMA_INDEX=359] is a one-line follow-up if smoke surfaces gradient outliers. - Mapped-pinned bridge: ml-dqn doesn't have MappedF32Buffer (in ml crate). Raw-u64 API takes dev_ptrs directly — clean cross-crate boundary, no type duplication. Files changed: - crates/ml-dqn/src/gpu_replay_buffer.rs: insert_synthetic_via_pinned API - crates/ml/src/trainers/dqn/trainer/enrichment.rs: HindsightScratch struct + cap const - crates/ml/src/trainers/dqn/trainer/mod.rs: hindsight_scratch field - crates/ml/src/trainers/dqn/trainer/constructor.rs: hindsight_scratch: None init - crates/ml/src/trainers/dqn/trainer/training_loop.rs: inject_hindsight_experiences helper + post-enrichment hook - docs/dqn-wire-up-audit.md: 2026-05-11 audit entry Verification (passing): - cargo check -p ml --tests --features cuda: 0 errors - cargo test -p ml --lib sp21_isv_slots: 3/3 - sp20_aggregate_inputs_test: 12/12 - sp20_phase1_4_wireup_test: 2/2 - sp20_emas_compute_test: 4/4 - sp20_controllers_compute_test: 7/7 - sp21_per_trade_predicted_q_test: 3/3 Total: 34 tests, 0 failures. SP21 T2.2 cascade FULLY COMPLETE (Phases 1.5, 2, 3, 4, 4.5, 5+6, 6.5a, 6.5b, 7, 8). All enrichment outputs (E1-E8) wire to real consumers. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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jgrusewski
|
f29dcc47c9 |
feat(sp21): T2.2 Phase 6.5a — val state retention infrastructure (mapped-pinned, atomic)
Lays the consumer-side infrastructure for true E7 hindsight synthetic injection. Phase 6.5b will follow with the producer wireup. What lands: 1. EvalTrade.window_index + HindsightExperience.window_index fields (host-side only; set in read_per_trade_tape from the w loop var and propagated by compute_hindsight_labels). 2. GpuBacktestEvaluator.retained_states_buf — mapped-pinned MappedF32Buffer sized [max_len × n_windows × state_dim_padded]. Populated by a DtoD copy after every launch_gather_chunk inside submit_dqn_step_loop_cublas; layout matches chunked_states_buf so the copy is a single contiguous block per chunk (no transpose). 3. pub fn read_retained_state(window_idx, bar_idx) — zero-copy host read via std::ptr::read_volatile on host_ptr (no memcpy_dtoh per feedback_no_htod_htoh_only_mapped_pinned). Mapped-pinned decision (jgrusewski review): - Initial draft used CudaSlice<f32> + memcpy_dtoh for host read, caught at review: violates feedback_no_htod_htoh_only_mapped_pinned. - Refactored to MappedF32Buffer (cuMemHostAlloc DEVICEMAP). The DtoD copy remains (rule forbids HtoD/DtoH, not DtoD; kernel writes via dev_ptr aliasing pinned host memory). Caller must sync eval stream before read_retained_state — production path's consume_metrics_after_event already does this. Memory cost at production cfg (max_len=200_000, n_windows=5, state_dim_padded≈128): ~512 MB pinned host RAM. Substantial but feasible on L40S host (192 GB+). Files changed: - crates/ml/src/cuda_pipeline/gpu_backtest_evaluator.rs: +retained buffer + accessor; EvalTrade.window_index field - crates/ml/src/trainers/dqn/trainer/enrichment.rs: HindsightExperience .window_index field - docs/dqn-wire-up-audit.md: 2026-05-11 audit entry Verification (passing): - cargo check -p ml --tests --features cuda: 0 errors - cargo test -p ml --lib sp21_isv_slots: 3/3 - sp20_aggregate_inputs_test: 12/12 - sp20_phase1_4_wireup_test: 2/2 - sp20_emas_compute_test: 4/4 - sp20_controllers_compute_test: 7/7 - sp21_per_trade_predicted_q_test: 3/3 Total: 34 tests, 0 failures. Infrastructure works without exercising it (accessor returns None until eval populates the retained buffer — graceful degradation for test scaffolds bypassing the full eval). After this commit (Phase 6.5b): - Mapped-pinned synthetic-tuple scratch on GpuReplayBuffer - New insert_synthetic_via_pinned API (raw dev_ptrs, no HtoD) - training_loop hindsight injection wireup (~300 LOC) Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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jgrusewski
|
1d2dd38a10 |
feat(sp21): T2.2 Phase 8 — signal-drive E2+E5 controller gains via val_sharpe_std (atomic)
Eliminates remaining hardcoded controller GAINS in enrichment.rs per pearl_controller_anchors_isv_driven. Both E2 (compute_adaptive_epsilon) and E5 (compute_agreement_threshold) now derive gain magnitudes from val_sharpe_std = √ISV[VAL_SHARPE_VAR_EMA_INDEX=351] — same signal source as the early-stopping pipeline. Phase 2 already signal-drove the anchors; this commit closes the GAIN half. NO new ISV slots. NO kernel changes. NO ISV_TOTAL_DIM bump. Pure value-driven refactor of two enrichment functions. E2 transformation: - Bracket anchors 2.0/0.5/-0.5 → 2.0×std / 0.5×std / -0.5×std - Multiplicative gains 0.8/0.95/1.2 → (1 ± gain_mag) and (1 - 0.5×gain_mag) - gain_mag = val_sharpe_std.clamp(0.05, 0.30) (Invariant 1 carve-out) - Cold-start (var_ema==0) → pass-through E5 transformation: - Tighten step 0.9 → (1 - gain_mag) - Loosen step 1.1 → (1 + gain_mag) - Same gain_mag formula as E2 (consistency) Invariant 1 carve-outs explicitly retained (project-wide priors): - [0.05, 0.30] gain_mag stability clamp (mirrors Wiener-α floor) - [0.85, 0.98] E3 gamma support range (trading-frequency prior) - [0.5, 2.0] E4 per-branch LR multiplier (collapse/divergence guard) Files changed: - crates/ml/src/trainers/dqn/trainer/enrichment.rs: E2 takes new val_sharpe_var_ema arg; both E2 and E5 derive gains from val_sharpe_std; run_enrichments call-site arg added - docs/dqn-wire-up-audit.md: 2026-05-11 audit entry Verification (passing): - cargo check -p ml --tests --features cuda: 0 errors - cargo test -p ml --lib sp21_isv_slots: 3/3 - sp20_aggregate_inputs_test: 12/12 - sp20_phase1_4_wireup_test: 2/2 - sp20_emas_compute_test: 4/4 - sp20_controllers_compute_test: 7/7 - sp21_per_trade_predicted_q_test: 3/3 Total: 34 tests, 0 failures. SP21 T2.2 cascade COMPLETE — all 8 atomic phases landed (1.5, 2, 3, 4, 4.5, 5+6, 7, 8). Remaining future work out of T2.2 scope: - Phase 6.5 (deferred): true E7 hindsight synthetic injection - Phase 7.5 (deferred): true E8 per-segment PER sampling Next operational step: dispatch L40S smoke training run. Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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jgrusewski
|
34d19955ff |
feat(sp21): T2.2 Phase 7 — E8 curriculum_concentration → PER alpha boost (atomic)
Wires E8's curriculum_weights distribution into the per_update_pa alpha boost composition via a new scalar signal: `compute_curriculum_concentration(weights) = 1 - entropy/log(n)`. Same pattern as Phases 5+6 (E6 winner_concentration + E7 hindsight_magnitude); all three feed the same boost_delta sum. Plan revision (mirrors Phase 5+6 pattern): - Original plan: "wire E8 (curriculum weights) → segment sampling weights." Literal interpretation requires new curriculum-segment abstraction in PER (segments don't exist — flat ring buffer today). - Resolution: signal-driven from the SHAPE of the weights distribution (entropy concentration), not the CONTENT (per-segment weighted sampling). Feeds existing per_update_pa kernel; no new segment-sampling kernel. - True per-segment PER sampling deferred to Phase 7.5 (mirrors Phase 6.5 deferral for E7's literal injection consumer). Signal semantics (compute_curriculum_concentration): - Input: Vec<f32> of E8's per-segment weights (sum=1). - Output: 1 - entropy/log(n) ∈ [0, 1]. - 0.0 = uniform (segments equally hard) - 1.0 = one segment dominates (concentrated difficulty) - Single-segment trivially → 1.0 - Cold start (empty input) → 0.0 sentinel - Zero-weight segments skipped (p log p → 0) ISV slot allocation: - CURRICULUM_CONCENTRATION_INDEX = 527 - ISV_TOTAL_DIM 527 → 528 (bus extension) - Layout fingerprint adds SLOT_527 entry Kernel change (4 lines, no ABI churn): - per_update_pa reads isv_signals[527] (already-existing arg from Phase 5+6) - curriculum_term = clamp(curric_conc, 0, 1) × 0.1 ∈ [0, 0.1] - boost_delta upper bound 0.4 → 0.5 to accommodate new term - Cold-start short-circuit predicate extended to all 3 signals Producer wireup: - enrichment.rs: new helper compute_curriculum_concentration; EnrichmentResult.curriculum_concentration field; run_enrichments populates it; log line extended - training_loop.rs: post-enrichment block writes ISV[527] Files changed: - crates/ml/src/cuda_pipeline/sp21_isv_slots.rs: +1 slot const - crates/ml/src/cuda_pipeline/gpu_dqn_trainer.rs: ISV_TOTAL_DIM bump + fingerprint - crates/ml-dqn/src/per_kernels.cu: 4-line boost composition extension - crates/ml/src/trainers/dqn/trainer/enrichment.rs: helper + field - crates/ml/src/trainers/dqn/trainer/training_loop.rs: write ISV - docs/dqn-wire-up-audit.md: 2026-05-11 audit entry Verification (passing): - cargo check -p ml --tests --features cuda: 0 errors - cargo test -p ml --lib sp21_isv_slots: 3/3 - sp20_aggregate_inputs_test: 12/12 - sp20_phase1_4_wireup_test: 2/2 - sp20_emas_compute_test: 4/4 - sp20_controllers_compute_test: 7/7 - sp21_per_trade_predicted_q_test: 3/3 Total: 34 tests, 0 failures. After this commit (Phase 8 + 6.5 + 7.5): - Phase 8: signal-drive remaining controller GAINS in enrichment - Phase 6.5: true E7 hindsight synthetic injection (deferred) - Phase 7.5: true E8 per-segment PER sampling (deferred) Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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jgrusewski
|
a6087a0b23 |
feat(sp21): T2.2 Phase 5+6 combined — E6/E7 signal-driven PER alpha scaling (atomic)
Wires E6 (compute_winner_indices) + E7 (compute_hindsight_labels) outputs into the PER priority update kernel via signal-driven ISV slots. Phases 5 and 6 combined into one atomic commit per feedback_no_deferrals_for_complementary_fixes — both attack the same consumer kernel (per_update_pa) with non-overlapping refactor scopes (E6 contributes one ISV-mediated scalar, E7 contributes another, kernel composes both into alpha_boost). Plan revision (briefed and accepted 2026-05-11): - E6's literal Vec<usize> of val bar indices CANNOT directly bump training-PER priorities — val and training have separate coord systems (no bar-index → buffer-slot mapping). - E7's true synthetic injection requires val state retention infrastructure (n_windows × max_len × state_dim scratch buffer) — significant scope expansion deferred to Phase 6.5. - The MEANINGFUL signal in both phases is scalar aggregations of the per-trade tape: E6 winner concentration (top-decile-mean P&L / all-mean P&L) and E7 hindsight magnitude (mean |counterfactual_pnl|). Both compose multiplicatively into per_update_pa's alpha_eff. ISV slot allocation: - WINNER_CONCENTRATION_INDEX = 525 - HINDSIGHT_MAGNITUDE_INDEX = 526 - ISV_TOTAL_DIM 525 → 527 (bus extension) - Layout fingerprint adds 2 SLOT entries - Compile-time test asserts SP21_SLOT_END (527) ≤ ISV_TOTAL_DIM Signal semantics: - winner_concentration: top_decile_mean_pnl / max(all_mean_pnl, EPS). > 1.0 = top decile dominates; ≈ 1.0 = uniform; ≤ 0 → 0.0 sentinel (losing strategy, signal ill-defined). - hindsight_magnitude: mean(|counterfactual_pnl|). Higher = larger missed opportunities. - Cold start: both at 0.0 sentinel; kernel short-circuits to alpha_eff = alpha (no-op). ABI surgery (minimal): - per_update_pa: ONE new arg `const float* __restrict__ isv_signals` at end. NULL-tolerant. Reads slots 525/526 device-side, composes boost_delta (bounded [0, 0.4]), applies alpha_eff = alpha + delta. - update_priorities_gpu launcher: passes existing self.isv_signals_dev_ptr (already on struct, settable via set_isv_signals_ptr — same infra per_insert_pa uses for recovery_oversample). Zero new public API. Producer wireup: - enrichment.rs: 2 new helpers (compute_winner_concentration, compute_hindsight_magnitude); EnrichmentResult gains 2 fields (winner_concentration, hindsight_magnitude); run_enrichments populates both; log line extended. - training_loop.rs: post-enrichment block writes both ISV slots via fused.trainer().write_isv_signal_at. Files changed: - crates/ml/src/cuda_pipeline/sp21_isv_slots.rs: +2 slot consts - crates/ml/src/cuda_pipeline/gpu_dqn_trainer.rs: ISV_TOTAL_DIM bump + fingerprint - crates/ml-dqn/src/per_kernels.cu: per_update_pa ABI + boost logic - crates/ml-dqn/src/gpu_replay_buffer.rs: launcher passes ISV ptr - crates/ml/src/trainers/dqn/trainer/enrichment.rs: 2 helpers + 2 fields + populate - crates/ml/src/trainers/dqn/trainer/training_loop.rs: write 2 slots - docs/dqn-wire-up-audit.md: 2026-05-11 audit entry Verification (passing): - cargo check -p ml --tests --features cuda: 0 errors - cargo test -p ml --lib sp21_isv_slots: 3/3 - sp20_aggregate_inputs_test: 12/12 - sp20_phase1_4_wireup_test: 2/2 - sp20_emas_compute_test: 4/4 - sp20_controllers_compute_test: 7/7 - sp21_per_trade_predicted_q_test: 3/3 Total: 34 tests, 0 failures. Behavioral gate (alpha_eff lift on post-warmup val passes) is the upcoming smoke training run. Deferred follow-up (Phase 6.5): true E7 hindsight synthetic experience injection via val state retention + per_insert_pa extension. Significant infrastructure (n_windows × max_len × state_dim scratch + insert API extension). Documented in audit. After this commit (T2.2 Phases 7-8 + 6.5 deferred): - Phase 7: E8 curriculum weights → segment sampling - Phase 8: signal-drive remaining controller GAINS - Phase 6.5: synthetic hindsight injection (deferred — needs val state buffer infrastructure) Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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jgrusewski
|
47e67011c9 |
feat(sp21): T2.2 Phase 4.5 — re-instate Pearl C engagement tracking for branches (atomic)
Closes the Phase 4 deferral. The 4 DqnBranches sub-launches now write
per-block engagement counts to 4 distinct ranges in
clamp_engage_per_block_buf; pearl_c_post_adam_engagement_check
aggregates all 4 ranges into one per-group rate-deficit EMA —
semantically equivalent to the pre-Phase-4 single-launch tracking.
Design: Option (b) sub-block offsetting, mirroring the existing
Curiosity pattern exactly. SP4_ENGAGE_EXTRA_BRANCHES_SUBLAUNCHES = 3
reserves 3 extra slots beyond Curiosity's tail; sub-launch 0 (Dir)
reuses the canonical DqnBranches slot 2; sub-launches 1/2/3 (Mag,
Order, Urgency) get extra slots 11/12/13. This keeps ParamGroup at
8 entries (no taxonomy growth, no 28 new ISV slot allocations).
SP4_ENGAGE_BUF_LEN: 11 → 14 × MAX_BLOCKS_PER_ADAM (45056 → 57344
i32 slots, +12 KiB on a non-hot-path mapped-pinned buffer).
Branch-to-offset mapping:
| Sub-launch | Offset constant | Slot | Buffer offset |
|------------|------------------------------------|------|---------------|
| Dir (b0) | SP4_ENGAGE_OFFSET_BRANCH_DIR | 2 | 8 192 |
| Mag (b1) | SP4_ENGAGE_OFFSET_BRANCH_MAG | 11 | 45 056 |
| Order (b2) | SP4_ENGAGE_OFFSET_BRANCH_ORDER | 12 | 49 152 |
| Urgency(b3)| SP4_ENGAGE_OFFSET_BRANCH_URGENCY | 13 | 53 248 |
pearl_c_post_adam_engagement_check generalized: a `multi_range` flag
covers both Curiosity (4 sub-launches W1/b1/W2/b2) and DqnBranches
(4 sub-launches Dir/Mag/Order/Urgency). Read AND zero-out paths use
the same flag — no duplication of branching logic.
Files changed:
- crates/ml/src/cuda_pipeline/sp4_isv_slots.rs: SP4_ENGAGE_EXTRA_
BRANCHES_SUBLAUNCHES const; SP4_ENGAGE_BUF_LEN formula extended;
SP4_ENGAGE_OFFSET_BRANCH_{DIR,MAG,ORDER,URGENCY}; layout test
updated to 14× MAX_BLOCKS_PER_ADAM
- crates/ml/src/cuda_pipeline/gpu_dqn_trainer.rs: launch_adam_update
branch sub-launches use new offsets; pearl_c_post_adam_engagement_
check aggregates DqnBranches multi-range
- docs/dqn-wire-up-audit.md: 2026-05-11 audit entry
Verification (passing):
- cargo check -p ml --tests --features cuda: 0 errors
- cargo test -p ml --lib sp4_isv_slots: 2/2 (engage buf layout asserts
14× + branch offsets correct)
- cargo test -p ml --lib sp21_isv_slots: 3/3
- sp20_aggregate_inputs_test: 12/12
- sp20_phase1_4_wireup_test: 2/2
- sp20_emas_compute_test: 4/4
- sp20_controllers_compute_test: 7/7
- sp21_per_trade_predicted_q_test: 3/3
Total: 33 tests, 0 failures. Behavioral gate: HEALTH_DIAG emits
per-branch engagement-rate-deficit EMAs in upcoming smoke run.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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jgrusewski
|
b7c4f84ea0 |
feat(sp21): T2.2 Phase 4 — wire E4 branch_lr_scale → per-branch Adam (atomic)
Wires EnrichmentResult::branch_lr_scale (E4's [f32; 4] clamped [0.5,
2.0] per-branch LR multiplier) into the DQN Adam optimizer. Splits
the existing single DqnBranches Adam sub-launch into 4 per-branch
sub-launches, each consuming its own LR scale from ISV[521..525).
Plan amendment from on-paper design:
- Plan said "via existing per-group Adam infrastructure" but per-group
operates at PARAM_GROUP granularity (8 groups, all 4 action branches
lumped into DqnBranches). E4 needs per-action-BRANCH granularity.
- Resolution: split DqnBranches sub-launch into 4 per-branch sub-launches
using the already-canonical branch byte ranges (4 param tensors per
branch: Dir [17..21), Mag [21..25), Order [25..29), Urgency [29..33)).
Coverage invariant updated to 7-way (was 4-way).
- Pearl C engagement tracking on branches DEFERRED to Phase 4.5: the
shared DqnBranches engagement counter offset would collide on writes
if 4 sub-launches use the same offset. Pearl C is a diagnostic system
(not load-bearing) so its temporary unavailability for branches is
acceptable; Trunk + Value + Trunk-extras Pearl C still active.
Phase 4.5 follow-up will re-instate via ParamGroup expansion or
sub-block offsetting scheme.
ISV slot allocation:
- BRANCH_LR_SCALE_{DIR,MAG,ORDER,URGENCY}_INDEX = 521..525
- ISV_TOTAL_DIM 521 → 525 (bus extension)
- Layout fingerprint adds 4 SLOT entries
- New branch_lr_scale_index(branch_idx) accessor for clean mapping
- Cold-start floor: launcher reads ISV, floors at 1.0 if at sentinel
0.0 (per pearl_first_observation_bootstrap — first emit replaces
directly with no intermediate state)
ABI surgery:
- dqn_adam_update_kernel: ONE new arg float lr_scale at end of
signature; lr = *lr_ptr * lr_scale inside kernel
- 5 callers migrated atomically per feedback_no_partial_refactor:
- launch_adam_update (main DQN): 7 sub-launches with per-branch
lr_scale (Trunk + Value + 4 branch + Trunk-extras)
- 4 post-aux launchers (ofi_embed/aux_trunk/denoise/sel) pass 1.0
- decision_transformer Adam launch passes 1.0
Producer wireup (training_loop.rs post-enrichment block):
```rust
for (branch_idx, &scale) in result.branch_lr_scale.iter().enumerate() {
fused.trainer().write_isv_signal_at(
branch_lr_scale_index(branch_idx),
scale,
);
}
```
Files changed:
- crates/ml/src/cuda_pipeline/sp21_isv_slots.rs: +4 slots + accessor + tests
- crates/ml/src/cuda_pipeline/gpu_dqn_trainer.rs: ISV_TOTAL_DIM bump +
fingerprint + 7-way Adam split with per-branch lr_scale
- crates/ml/src/cuda_pipeline/dqn_utility_kernels.cu: lr_scale arg + apply
- crates/ml/src/cuda_pipeline/decision_transformer.rs: lr_scale=1.0
- crates/ml/src/trainers/dqn/trainer/training_loop.rs: write 4 ISV slots
- docs/dqn-wire-up-audit.md: 2026-05-11 audit entry
Verification (passing):
- cargo check -p ml --tests --features cuda: 0 errors
- cargo test -p ml --lib sp21_isv_slots --features cuda: 3/3 (bus bounds
+ slot uniqueness + branch index mapping)
- sp20_aggregate_inputs_test: 12/12
- sp20_phase1_4_wireup_test: 2/2
- sp20_emas_compute_test: 4/4
- sp20_controllers_compute_test: 7/7
- sp21_per_trade_predicted_q_test: 3/3
Total: 31 tests, 0 failures. Behavioral gate (per-branch LR divergence)
is the upcoming smoke training run.
After this commit (T2.2 Phases 5-7 + 8 + 4.5):
- Phase 5: E6 winner indices → PER priority bumps
- Phase 6: E7 hindsight → replay buffer injection
- Phase 7: E8 curriculum weights → segment sampling
- Phase 8: signal-drive remaining controller GAINS
- Phase 4.5: re-instate Pearl C engagement tracking for branches
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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|
jgrusewski
|
21f911151a |
feat(sp21): T2.2 Phase 3 — wire E1 q_correction → Bellman target offset (atomic)
Wires `EnrichmentResult::q_correction` (Phase 1.5+2's E1 clamp(-mean(predicted_q − pnl), ±10.0) from the per-trade tape) into the training loss kernels' Bellman target computation. Both mse_loss_batched and c51_loss_kernel::block_bellman_project_f apply q_correction as additive shift on the Bellman target — blended (1-α)·MSE + α·C51 sees identical Q-target shifts (symmetric application per feedback_no_partial_refactor). ISV slot allocation (per pearl_controller_anchors_isv_driven + feedback_isv_for_adaptive_bounds — adaptive Q-target shift IS adaptive bound, lives in ISV bus): - New Q_CORRECTION_INDEX = 520 in cuda_pipeline::sp21_isv_slots - ISV_TOTAL_DIM 520 → 521 (bus extension) - Layout fingerprint adds SLOT_520_Q_CORRECTION - New module registered in cuda_pipeline/mod.rs - Compile-time test verifies SP21_SLOT_END <= ISV_TOTAL_DIM Sign convention: q_correction is the additive correction (E1 already negates the bias). predicted_q > pnl → q_correction < 0 → "lower Q-targets". predicted_q < pnl → q_correction > 0 → "raise Q-targets". Cold-start sentinel 0.0 (no trades yet) is no-op until first val pass writes (per pearl_first_observation_bootstrap). ABI surgery (minimal): - mse_loss_batched: ONE new scalar arg (float q_correction) at end - c51_loss_batched: ZERO new args (block_bellman_project_f already takes isv_signals; reads slot 520 from there) - launch_mse_loss: reads ISV[520] host-side via existing read_isv_signal_at, passes scalar - training_loop.rs (post-enrichment): writes result.q_correction to ISV[520] via existing write_isv_signal_at Files changed: - crates/ml/src/cuda_pipeline/sp21_isv_slots.rs (NEW): slot const + bounds-check tests - crates/ml/src/cuda_pipeline/mod.rs: pub mod sp21_isv_slots - crates/ml/src/cuda_pipeline/gpu_dqn_trainer.rs: ISV_TOTAL_DIM bump + fingerprint update + launch_mse_loss launcher arg - crates/ml/src/cuda_pipeline/mse_loss_kernel.cu: q_correction arg + application to target_q - crates/ml/src/cuda_pipeline/c51_loss_kernel.cu: read isv_signals[520] in block_bellman_project_f, add to t_z - crates/ml/src/trainers/dqn/trainer/training_loop.rs: write_isv_signal_at( Q_CORRECTION_INDEX, result.q_correction) post-enrichment - docs/dqn-wire-up-audit.md: 2026-05-11 audit entry Verification: - cargo check -p ml --tests --features cuda: 0 errors - cargo test -p ml --lib sp21_isv_slots --features cuda: 2/2 (bus bounds + slot uniqueness) - sp20_aggregate_inputs_test: 12/12 - sp20_phase1_4_wireup_test: 2/2 - sp20_emas_compute_test: 4/4 - sp20_controllers_compute_test: 7/7 - sp21_per_trade_predicted_q_test: 3/3 Total: 30 tests, 0 failures. Behavioral gate (q_correction → non- zero ISV[520] → Q-target shift) is the upcoming smoke training run. After this commit (T2.2 Phases 4-8): - Phase 4: E4 per-branch LR scaling via per-group Adam - Phase 5: E6 winner indices → PER priority bumps - Phase 6: E7 hindsight → replay buffer injection - Phase 7: E8 curriculum weights → segment sampling - Phase 8: signal-drive remaining controller GAINS Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com> |
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|
jgrusewski
|
ea12c172e6 |
test(sp21): T2.2 Phase 1.5 — kernel-direct GPU oracle for per-trade predicted_q
Promotes the Phase 2.5 follow-up from the plan to a load-bearing test.
Three #[ignore = "requires GPU"] tests exercise backtest_env_step_batch
directly with controlled inputs:
1. predicted_q_populated_on_close_with_real_q_values — open Long Full
at step 0 with q_values_per_window[w=0, a=Long_Full]=2.5, hold for
two bars, close Flat at step 3. Asserts the per-trade tape's
predicted_q[0] ≈ 2.5 (entry_q captured at open, persisted in
entry_q_state across holds, snapshotted before close emit).
2. predicted_q_stays_zero_when_q_values_is_null — same scenario with
q_values_per_window=NULL (single-step evaluate() semantics). The
kernel's open-time write is gated on the NULL guard, so
entry_q_state[w] stays at buffer-init 0.0 and the tape's
predicted_q is 0.0. Proves the NULL-tolerance contract is
kernel-enforced, not just launcher convention.
3. no_trades_no_predicted_q_emission — all-Flat action sequence
produces zero trades. Path-coverage check that entry_q's open
guard fires only on actual opens / reverses.
Test design:
- Kernel-direct (loads ENV_CUBIN via include_bytes!), no eval-pipeline
scaffolding (no QValueProvider, no cuBLAS forward, no chunked state
gather). Avoids the heavy mock infrastructure the plan flagged.
- Flat-market 4-bar single-window window: every OHLC=100, zero costs,
initial_capital=100k. Isolates the entry_q signal from P&L noise
so the assert-predicted_q is exact under IEEE-754 (kernel writes
the Q-value verbatim with no math).
- NULL fallback for isv_signals/conviction/exploration_scale matches
the existing single-step launcher pattern; FEATURE_DIM=4 (<41) ⇒
compute_regime_trail_scales takes the fixed-width fallback (no
feature deref needed).
Verification:
- SQLX_OFFLINE=true cargo test -p ml --test sp21_per_trade_predicted_q_test
--features cuda -- --ignored --nocapture
- 3/3 pass on RTX 3050 Ti (sm_86).
- All 4 prior SP20 GPU oracle suites still pass (25 tests).
- Total: 28 GPU oracle tests, 0 failures.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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