#!/bin/bash
#SBATCH --time=02:00:00
#SBATCH --nodes=1
#SBATCH --ntasks-per-node=4
#SBATCH --mem=64G
#SBATCH --gres=gpu:a100:1
#SBATCH --job-name="probe15_seal_milk"
#SBATCH --output="logs/probe15_seal_milk_%j.out"

export PYTHONUNBUFFERED=1

echo "============================================"
echo "Probe 15: Seal Milk OOD Topology Benchmark"
echo "============================================"
echo "Started: $(date)"
echo "Node: $(hostname)"
echo "GPU: $(nvidia-smi --query-gpu=name --format=csv,noheader 2>/dev/null || echo 'N/A')"

# ─── Environment ──────────────────────────────────────────────────────────
source /work/ratul1/supantha/miniconda3/etc/profile.d/conda.sh
conda activate glycanml
pip install umap-learn --quiet 2>/dev/null

cd /work/ratul1/supantha/glycan-SD-VS/bert_training_v3/v3.1_cluster_training

# ─── Run Probe 15 ────────────────────────────────────────────────────────
python3 -u bert_v6_contrastive/scripts/probe_15_seal_milk_ood.py \
    --model v6 \
    --task all

echo ""
echo "============================================"
echo "Completed: $(date)"
echo "============================================"