scripts/run_train_v27.sh

#!/usr/bin/env bash
# v27 training — SpatialConceptHead: ConceptHead now operates on 14×14 spatial
# token map [B, 196, 320] instead of globally-pooled vector [B, 320].
#
# Architecture change (relative to v26):
#   ConceptHead (legacy): Linear(320→256)→LN→GELU→Linear(256→6)→Sigmoid
#     - input: [B, 320] globally-pooled backbone output
#     - loses spatial information entirely
#   SpatialConceptHead (v27+):
#     Shared trunk : Linear(320→128)→LN→GELU              → [B, 196, 128]
#     Per-concept  : 6 × Linear(128→1) → mean over 196   → [B, 6]
#     Activation   : Sigmoid                               → (0, 1)
#     - input: [B, 196, 320] backbone.forward_spatial() output
#     - each concept attends to different spatial regions
#     - separate proj weights per concept → reduced entanglement
#
# Why this matters:
#   orientation_coherence: needs local ridge flow consistency across patches
#   continuity:            needs to detect ridge break locations spatially
#   minutiae_reliability:  needs to localise bifurcation / ending regions
#
# BREAKING CHANGE: incompatible with v16–v26 checkpoints.
#
# All other hyperparameters identical to v26 (gamma=2.0, spread-weight=3.0).
# After confirming spatial head matches or exceeds v26 on KS/Pearson, the
# noise→noise_lv supervision mismatch (+0.365 in v24/v26) can be addressed.

set -euo pipefail

REPO_ROOT="$(cd "$(dirname "$0")/../.." && pwd)"
export PATH="/home/aiserver/miniconda3/bin:$PATH"

VERSION="v27"
SAVE_DIR="${REPO_ROOT}/sifq/checkpoints/${VERSION}"
LOG_FILE="${REPO_ROOT}/sifq/logs/train_${VERSION}.log"
EVAL_SCRIPT="${REPO_ROOT}/sifq/scripts/run_eval_${VERSION}.sh"

mkdir -p "${REPO_ROOT}/sifq/logs"

python "${REPO_ROOT}/sifq/scripts/train_sifq.py" \
  --root-302a  "${REPO_ROOT}/dataset/302a/images/challengers" \
  --root-302b  "${REPO_ROOT}/dataset/302b/images/baseline" \
  --root-302d  "${REPO_ROOT}/dataset/nist_302d/images/auxiliary" \
  --root-fvc2002 "${REPO_ROOT}/dataset/FVC_Dataset/FVC2002" \
  --root-fvc2004 "${REPO_ROOT}/dataset/FVC_Dataset/FVC2004" \
  --root-polyu "${REPO_ROOT}/dataset/PolyU" \
  --exclude-sensor "R_1000_slap,R_500_slap,S_500_slap" \
  --mdgt-checkpoint "${REPO_ROOT}/pad/TRAM-downstream/checkpoint/checkpoints_dinov2_tram/best_eer.pt" \
  --epochs 60 \
  --batch-size 96 \
  --image-size 224 \
  --lr 1e-4 \
  --spread-mode uniform \
  --spread-weight 3.0 \
  --concept-deg-gamma 2.0 \
  --sd302-concept-weight 0.0 \
  --deg-every-n-steps 2 \
  --no-mat-stats \
  --proto-max-batches 0 \
  --k-cross 0 \
  --max-train-samples -1 \
  --num-workers 8 \
  --gpus 0 \
  --save-dir "${SAVE_DIR}"

echo "[auto-eval] Training done. Starting eval ${VERSION}..."
bash "${EVAL_SCRIPT}" >> "${LOG_FILE}" 2>&1