Argo WorkflowTemplate at infra/k8s/argo/alpha-perception-template.yaml
runs the stacked Mamba2 -> CfC -> heads PerceptionTrainer on a single
L40S in fr-par-2. Two-stage DAG:
ensure-binary (ci-compile-cpu pool, sccache-backed cargo build of
alpha_train example, SHA-keyed binary cache under
/data/bin/$SHORT_SHA/)
train (ci-training-l40s pool, runs the cached binary against
/data/futures-baseline/mbp10 with predecoded sidecar
cache at /feature-cache/predecoded, writes
alpha_train_summary.json to
/feature-cache/alpha-perception-runs/$SHA/)
Defaults mirror the validated synthetic-overfit smoke config:
epochs=5, seq_len=32, mamba2_state_dim=16, lr_cfc=3e-3,
lr_mamba2=1e-3, n_train_seqs=8000, n_val_seqs=1000, seed=0x4242
Submission script scripts/argo-alpha-perception.sh wraps argo submit
with the standard L40S/H100 cuda-compute-cap mapping. --watch
follows logs.
Workflow nodeSelector pinned to fr-par-2 (consistent with the cluster
topology constraint). ttlStrategy 1h after completion;
activeDeadlineSeconds 4h cap (well above expected ~30-90 min wall).
This is the cluster entrypoint for the stacked perception design.
Once it lands a summary on MinIO, the gate runner (alpha_gate, Task
17) can consume it.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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