File size: 3,407 Bytes
cfc7a54 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 | #!/usr/bin/env bash
# v32 training — T42 concept map: dry_skin [4,2,0] → [4,0] (remove continuity)
#
# Goal: Fix spurious noise_level crosstalk in dry_skin degradation (v31: Spearman -0.758).
# noise_level [3] is NOT in the dry_skin target but drops strongly in v31.
# Hypothesis: continuity [2] shares backbone features with noise texture → when
# concept[2] is pulled down by dry_skin, concept[3] follows via shared feature paths.
# Removing continuity forces disambiguation via contrast[4] + orientation[0] only.
#
# Key changes vs v31 (T42 concept map):
# 1. dry_skin: [4, 2, 0] → [4, 0] (remove continuity)
# Continuity [2] shares patch-scale features with noise texture → causes
# spurious noise_level[3] activation (v31: Spearman -0.758 on non-target).
# Fix: use contrast[4] + orientation[0] only (regional features, not shared).
# 2. noise: [3] → [1, 3] (add clarity as co-target)
# TinyViT patch embed (16×16) averages out pixel Gaussian noise → concept[3]
# gets almost no gradient (v31: noise→noise_level Spearman only -0.081).
# Adding clarity[1] anchors noise degradation to ridge-valley blur at patch
# scale → strong ViT signal → reinforces concept[3] training direction.
# Note: T41 proposed both changes but v29 failed due to --concept-spread-weight,
# NOT the concept map. v32 uses T42 map with no --concept-spread-weight.
#
# Inherited from v31 (unchanged):
# --teacher dinov2_raw, --no-mat-stats, --spread-weight 4.0
# --concept-deg-gamma 2.0, --k-cross 0, --deg-every-n-steps 2
#
# Expected:
# Track 2: KS ≤ 0.15, Pearson ≥ 0.80 (concept map change should not affect)
# Track 4: dry_skin → noise_level crosstalk ↓ from -0.758
# noise → noise_level Spearman ↓ from -0.081 (stronger signal)
# dry_skin → contrast_uni, orient_coh remain strong
set -euo pipefail
REPO_ROOT="$(cd "$(dirname "$0")/../.." && pwd)"
export PATH="/home/aiserver/miniconda3/bin:$PATH"
VERSION="v32"
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 "${REPO_ROOT}/dataset/nist302a/images/challengers" \
# --root-302b "${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" \
# --teacher dinov2_raw \
# --dinov2-model dinov2_vits14 \
# --no-mat-stats \
# --proto-max-batches 0 \
# --epochs 60 \
# --batch-size 96 \
# --image-size 224 \
# --lr 1e-4 \
# --spread-mode uniform \
# --spread-weight 4.0 \
# --concept-deg-gamma 2.0 \
# --sd302-concept-weight 0.0 \
# --deg-every-n-steps 2 \
# --k-cross 0 \
# --max-train-samples -1 \
# --num-workers 8 \
# --gpus 0 \
# --save-dir "${SAVE_DIR}" \
# --wandb \
# --wandb-offline \
# --wandb-project "sifq" \
# --wandb-run-name "${VERSION}" \
# 2>&1 | tee "${LOG_FILE}"
echo "[auto-eval] Training done. Starting eval ${VERSION}..."
bash "${EVAL_SCRIPT}" >> "${LOG_FILE}" 2>&1
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