Spec: docs/superpowers/specs/2026-06-02-trainer-rollout-buffer-gae.md
Plan: docs/superpowers/plans/2026-06-02-trainer-rollout-buffer-gae-implementation.md §Phase 1B-B
Builds on commit 5cd2f8703 (1B-A foundation). Wires the RolloutBuffer
into the per-step training loop via a new RolloutCollection helper,
gated behind FOXHUNT_USE_ROLLOUT=1 env flag. Mode 0 (default unset) is
bit-equal to HEAD; Mode 1 (flag=1) snapshots per-step data into the
rollout buffer and invokes GAE every T_rollout steps.
This phase is a STRUCTURAL validation, not an empirical pnl test.
Phase 1B-C will replace the per-step training in Mode 1 with multi-
epoch PPO over the rollout buffer.
New components:
* crates/ml-alpha/cuda/rollout_pack.cu (42 LOC):
Single-thread-per-batch deterministic f32 -> u8 packer for dones.
Used because RolloutBuffer.dones_d is u8 (per spec for memory) but
the trainer's dones_d is f32 (per existing pipeline).
* crates/ml-alpha/src/trainer/rollout_collection.rs (375 LOC):
RolloutCollection helper with three methods:
- new(ctx): loads rollout_pack cubin
- snapshot_step(trainer, buf, t, b_size, t_max): DtoD scatter via
cuMemcpy2DAsync_v2 for rewards/v_t/actions/log_pi/h_t at offset
b*t_max+t in the [B × T] buffer; rollout_pack kernel for dones
- copy_bootstrap_v(trainer, buf, b_size): DtoD V(s_T) from
trainer.v_pred_tp1_d into buf.v_t_bootstrap_d at rollout end
All transfers use mapped-pinned / DtoD only — no raw memcpy_dtoh
on regular slices (`feedback_no_htod_htoh_only_mapped_pinned`).
* crates/ml-alpha/examples/alpha_rl_train.rs (+137 LOC at lines 59-66,
410-466, 591-666):
- FOXHUNT_USE_ROLLOUT env-flag parse at startup
- Conditional RolloutBuffer + RolloutCollection allocation
- Per-step snapshot_step() after step_with_lobsim_gpu
- Every T_rollout steps: copy_bootstrap_v + compute_gae + stderr log
`[rollout] step=N GAE complete (T=…, γ=…, λ=0.95): adv_mean=…
adv_abs_mean=… returns_mean=…`
Adaptations from the dispatch (documented inline):
1. T_rollout fallback to 32 when slot 758 is unbootstrapped. Slot 758
(RL_PPO_ROLLOUT_HORIZON_INDEX) was allocated in 1B-A but no kernel
bootstraps it — `read_isv_host(758)` returns 0.0. Binary uses
`.clamp(32, 1024)`, flooring to T=32 for the smoke. Phase 1B-C will
add the trainer bootstrap entry (or a controller kernel) to make
T_rollout=256 the production default.
2. Mode 1 still runs per-step training as a side effect; the rollout
buffer is populated as a parallel snapshot. The "stop training in
Mode 1" separation would require a ~1500 LOC refactor of
step_with_lobsim_gpu (single-step/training-coupled per
pearl_foxhunt_trainer_is_genuinely_single_step). The dispatch
explicitly authorized this "skeleton with correct semantics"
adaptation — the load-bearing 1B-B gate is "collection + GAE
pipeline works structurally", which is verified. Phase 1B-C will
replace the per-step training with multi-epoch PPO over the rollout
buffer.
Validation (all gates PASS):
* cargo build --release --example alpha_rl_train -p ml-alpha: exit 0 (~60s)
* cargo test rollout_buffer_invariants --release: 5/5 PASS (no regression)
* Mode 0 (flag unset, default): ./scripts/determinism-check.sh --quick exit 0
- DETERMINISTIC: all checksums.* leaves match across all 200 rows
- pipeline output bit-equal to HEAD 5cd2f8703 baseline
* Mode 1 (FOXHUNT_USE_ROLLOUT=1): smoke completes in 2m 53s
- 500 train + 100 eval steps, exit 0, completed_clean=true
- 16 GAE windows logged (T=32 each)
- adv_abs_mean range [4.4e-3, 1.92e-1] — always > 1e-3 sanity gate
- eval_summary written: total_pnl_usd=-$101,487.70, n_trades=301, wr=0.346
* Cross-source consistency BOTH modes within $50 (Mode 0: $0.00 diff;
Mode 1: $0.01 diff). Phase 0 contract preserved.
* Pre-commit hook PASS (0 memcpy_dtoh raw violations, 0 atomicAdd).
Next: Phase 1B-C will (a) bootstrap slot 758 to production T_rollout=256,
(b) replace Mode 1's per-step training with multi-epoch PPO over the
rollout buffer using the existing PPO surrogate + V regression kernels
operating on minibatches of [B × T] flattened to [B*T].
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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