0d9fbc16b0
5 sweep YAMLs updated to reference the new checkpoint filename:
- config/ml/sweep_smoke.yaml: trunk_best_h6000.bin → trunk_best_h1000.bin
- config/ml/sweep_perhoriz_diag.yaml: same
- config/ml/sweep_threshold_tuning.yaml: same
- config/ml/sweep_deployability.yaml: same
- config/ml/sweep_smoke_perhoriz_cfc.yaml: same + 3 comment updates
(WIN-gate criteria, header doc, best-checkpoint annotation)
scripts/generate_sweep_variants.py:61 updated atomically — without this
the next regeneration of sweep_deployability.yaml would silently
re-introduce trunk_best_h6000.bin.
Argo workflow templates (alpha-perception, alpha-cv, lob-backtest-sweep)
did NOT need text changes — they're already horizon-agnostic:
- They forward CLI flags via {{workflow.parameters.*}} to binaries
- Don't grep alpha_train_summary.json inline
- Don't reference per-horizon field names
- early-stop-metric default is "mean_auc" (horizon-agnostic)
Intentionally left:
- alpha-cv-template.yaml stacker-horizon: "6000" (unrelated TFT lookback)
- alpha-cv-template.yaml horizon: "1200" (DQN execution horizon in bars)
- lob-backtest-sweep-template.yaml ci-training-h100 (GPU pool name)
NOTE: kubectl apply of workflow templates is deferred to Task 10 (push
+ dispatch). Verified all 5 sweep YAMLs parse with python3 yaml.safe_load.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
21 lines
655 B
YAML
21 lines
655 B
YAML
base:
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data: /mnt/training-data/futures-baseline-mbp10/ES.FUT
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predecoded_dir: /feature-cache/predecoded
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n_parallel: 1
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latency_ns: 200000000
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target_annual_vol_units: 50.0
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annualisation_factor: 825.0
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max_lots: 5
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max_events: 2000000
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seed: 12648430
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checkpoint: /feature-cache/alpha-perception-runs/8b2ac1e57/trunk_best_h1000.bin
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min_reasonable_px: 1000.0
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max_reasonable_px: 20000.0
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delta_floor: 1.0
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per_horizon_logit_sampling_stride: 1000
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sim_variants:
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- { name: t0c1l200_perhoriz_diag, threshold: 0.0, cost_per_lot_per_side: 0.125,
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latency_ns: 200000000, max_hold_ns: 60000000000 }
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cells:
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- { name: perhoriz_diag }
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