f68e0a1d0d
The Phase 1 multi-resolution layout (10 raw + 10 agg@30 + 12 agg@100) regressed ALL horizons in alpha-perception-htpp6 (2026-05-22): - auc_h100: 0.681 -> 0.512 (-0.169) - auc_h300: 0.617 -> 0.506 (-0.111) - auc_h1000: 0.576 -> 0.526 (-0.050) Hypothesis falsified. Root cause: Mamba2+CfC SSM encoder already used all 32 raw ticks effectively via state-recurrence; replacing 22 raw ticks with arithmetic-mean aggregates destroyed within-window microstructure variance (the actual h100 signal) AND broke temporal continuity that the recurrence relies on. Δt Fourier encoder couldn't compensate. Architectural pearl: SSM/RNN/CfC + multi-resolution input is incompatible without separate-encoder-per-scale or explicit scale tokens. Transformer-style positional encoding tolerates scale-mixing; recurrent state updates assume consecutive positions. Reverts default to '1:32'. Adds explicit single_scale_32() constructor for callers (harness, tests). Keeps default_three_scale() in code with deprecation note for future sub-variant experiments. Production defaults across alpha_train CLI, Argo template, dispatcher script, ml-backtesting harness now match the proven baseline.
159 lines
5.6 KiB
Bash
Executable File
159 lines
5.6 KiB
Bash
Executable File
#!/usr/bin/env bash
|
|
# Submit the alpha-perception workflow.
|
|
#
|
|
# Trains the stacked Mamba2 -> CfC -> heads perception model on MBP-10
|
|
# from the training-data PVC. Emits alpha_train_summary.json with
|
|
# per-horizon validation AUC to the feature-cache PVC.
|
|
#
|
|
# Defaults match the validated synthetic-overfit smoke config; cluster
|
|
# runs can override for sweep work.
|
|
#
|
|
# Usage:
|
|
# ./scripts/argo-alpha-perception.sh # current HEAD on ml-alpha-phase-a
|
|
# ./scripts/argo-alpha-perception.sh --branch main
|
|
# ./scripts/argo-alpha-perception.sh --epochs 1 --n-train-seqs 1000 # quick smoke
|
|
# ./scripts/argo-alpha-perception.sh --watch
|
|
|
|
set -euo pipefail
|
|
|
|
SHA=HEAD
|
|
BRANCH=$(git symbolic-ref --short HEAD 2>/dev/null || echo "ml-alpha-phase-a")
|
|
GPU_POOL=ci-training-l40s
|
|
EPOCHS=5
|
|
MULTI_RESOLUTION="1:32"
|
|
MAMBA2_STATE_DIM=16
|
|
LR_CFC=3e-3
|
|
LR_MAMBA2=1e-3
|
|
N_TRAIN_SEQS=8000
|
|
N_VAL_SEQS=1000
|
|
SEED=16962
|
|
BATCH_SIZE=1
|
|
AUTO_HORIZON_WEIGHTS=false
|
|
EARLY_STOP_METRIC=mean_auc
|
|
EARLY_STOP_PATIENCE=5
|
|
CV_FOLD=0
|
|
CV_N_FOLDS=1
|
|
CV_TRAIN_WINDOW=0
|
|
DECISION_STRIDE=1
|
|
INSTRUMENT_MODE="all"
|
|
WATCH=false
|
|
|
|
usage() {
|
|
cat <<EOF
|
|
Usage: $0 [OPTIONS]
|
|
--sha <commit> Git SHA (default: HEAD on the current branch)
|
|
--branch <branch> Git branch (default: $BRANCH)
|
|
--gpu-pool <pool> GPU pool (default: $GPU_POOL)
|
|
--epochs <n> Training epochs (default: $EPOCHS)
|
|
--multi-resolution <S> Multi-scale input: scale:count[,...] (default: $MULTI_RESOLUTION)
|
|
--mamba2-state-dim <n> Mamba2 SSM state dim (default: $MAMBA2_STATE_DIM)
|
|
--lr-cfc <f> CfC learning rate (default: $LR_CFC)
|
|
--lr-mamba2 <f> Mamba2 learning rate (default: $LR_MAMBA2)
|
|
--n-train-seqs <n> Train sequences per epoch (default: $N_TRAIN_SEQS)
|
|
--n-val-seqs <n> Val sequences per epoch (default: $N_VAL_SEQS)
|
|
--seed <n> Random seed (default: $SEED)
|
|
--cv-fold <k> CV fold index (default: $CV_FOLD)
|
|
--cv-n-folds <N> Total CV folds (default: $CV_N_FOLDS)
|
|
--cv-train-window <W> Files per train window (default: $CV_TRAIN_WINDOW = auto)
|
|
--decision-stride <S> Snapshot stride for sequence sampling (default: $DECISION_STRIDE)
|
|
--instrument-mode <S> MBP-10 filter: all | front-month | id=<N> (default: $INSTRUMENT_MODE)
|
|
--watch Follow logs via argo watch
|
|
EOF
|
|
}
|
|
|
|
while [[ $# -gt 0 ]]; do
|
|
case "$1" in
|
|
--sha) SHA="$2"; shift 2 ;;
|
|
--branch) BRANCH="$2"; shift 2 ;;
|
|
--gpu-pool) GPU_POOL="$2"; shift 2 ;;
|
|
--epochs) EPOCHS="$2"; shift 2 ;;
|
|
--multi-resolution) MULTI_RESOLUTION="$2"; shift 2 ;;
|
|
--mamba2-state-dim) MAMBA2_STATE_DIM="$2"; shift 2 ;;
|
|
--lr-cfc) LR_CFC="$2"; shift 2 ;;
|
|
--lr-mamba2) LR_MAMBA2="$2"; shift 2 ;;
|
|
--n-train-seqs) N_TRAIN_SEQS="$2"; shift 2 ;;
|
|
--n-val-seqs) N_VAL_SEQS="$2"; shift 2 ;;
|
|
--seed) SEED="$2"; shift 2 ;;
|
|
--batch-size) BATCH_SIZE="$2"; shift 2 ;;
|
|
--auto-horizon-weights) AUTO_HORIZON_WEIGHTS=true; shift ;;
|
|
--early-stop-metric) EARLY_STOP_METRIC="$2"; shift 2 ;;
|
|
--early-stop-patience) EARLY_STOP_PATIENCE="$2"; shift 2 ;;
|
|
--cv-fold) CV_FOLD="$2"; shift 2 ;;
|
|
--cv-n-folds) CV_N_FOLDS="$2"; shift 2 ;;
|
|
--cv-train-window) CV_TRAIN_WINDOW="$2"; shift 2 ;;
|
|
--decision-stride) DECISION_STRIDE="$2"; shift 2 ;;
|
|
--instrument-mode) INSTRUMENT_MODE="$2"; shift 2 ;;
|
|
--watch) WATCH=true; shift ;;
|
|
-h|--help) usage; exit 0 ;;
|
|
*) echo "Unknown option: $1"; usage; exit 1 ;;
|
|
esac
|
|
done
|
|
|
|
case "$GPU_POOL" in
|
|
ci-training-l40s)
|
|
SM=89 ;;
|
|
ci-training-h100)
|
|
SM=90 ;;
|
|
*)
|
|
echo "Unknown gpu-pool: $GPU_POOL"
|
|
exit 1 ;;
|
|
esac
|
|
|
|
# Resolve commit-sha=HEAD to an actual SHA locally before submission.
|
|
# The in-cluster check-cache pod uses this SHA to look up the binary
|
|
# cache without needing git inside the alpine pod.
|
|
if [ "$SHA" = "HEAD" ]; then
|
|
echo "Resolving HEAD for branch $BRANCH..."
|
|
if ! git rev-parse --git-dir >/dev/null 2>&1; then
|
|
echo "ERROR: not in a git repo; cannot resolve HEAD"
|
|
exit 1
|
|
fi
|
|
git fetch --quiet origin "$BRANCH" 2>/dev/null || true
|
|
SHA=$(git rev-parse "origin/$BRANCH" 2>/dev/null \
|
|
|| git rev-parse "$BRANCH" 2>/dev/null \
|
|
|| git rev-parse HEAD)
|
|
echo " resolved: $SHA"
|
|
fi
|
|
|
|
echo "Submitting alpha-perception workflow..."
|
|
echo " branch: $BRANCH"
|
|
echo " sha: $SHA"
|
|
echo " gpu-pool: $GPU_POOL (sm_$SM)"
|
|
echo " epochs: $EPOCHS"
|
|
echo " multi-resolution: $MULTI_RESOLUTION"
|
|
echo " mamba2-state-dim: $MAMBA2_STATE_DIM"
|
|
echo " lr-cfc: $LR_CFC"
|
|
echo " lr-mamba2: $LR_MAMBA2"
|
|
echo " n-train-seqs: $N_TRAIN_SEQS"
|
|
echo " n-val-seqs: $N_VAL_SEQS"
|
|
echo " seed: $SEED"
|
|
|
|
WATCH_FLAG=""
|
|
if [[ "$WATCH" == "true" ]]; then
|
|
WATCH_FLAG="--watch"
|
|
fi
|
|
|
|
argo submit -n foxhunt --from=wftmpl/alpha-perception \
|
|
-p commit-sha="$SHA" \
|
|
-p git-branch="$BRANCH" \
|
|
-p cuda-compute-cap="$SM" \
|
|
-p gpu-pool="$GPU_POOL" \
|
|
-p epochs="$EPOCHS" \
|
|
-p multi-resolution="$MULTI_RESOLUTION" \
|
|
-p mamba2-state-dim="$MAMBA2_STATE_DIM" \
|
|
-p lr-cfc="$LR_CFC" \
|
|
-p lr-mamba2="$LR_MAMBA2" \
|
|
-p n-train-seqs="$N_TRAIN_SEQS" \
|
|
-p n-val-seqs="$N_VAL_SEQS" \
|
|
-p seed="$SEED" \
|
|
-p batch-size="$BATCH_SIZE" \
|
|
-p auto-horizon-weights="$AUTO_HORIZON_WEIGHTS" \
|
|
-p early-stop-metric="$EARLY_STOP_METRIC" \
|
|
-p early-stop-patience="$EARLY_STOP_PATIENCE" \
|
|
-p cv-fold="$CV_FOLD" \
|
|
-p cv-n-folds="$CV_N_FOLDS" \
|
|
-p cv-train-window="$CV_TRAIN_WINDOW" \
|
|
-p decision-stride="$DECISION_STRIDE" \
|
|
-p instrument-mode="$INSTRUMENT_MODE" \
|
|
$WATCH_FLAG
|