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eb725f8 1f3e7a2 eb725f8 1f3e7a2 eb725f8 1f3e7a2 eb725f8 1f3e7a2 eb725f8 1f3e7a2 eb725f8 1f3e7a2 eb725f8 | 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 | #!/bin/bash
#SBATCH --account=<your-slurm-account>
#SBATCH --partition=l40s
#SBATCH --nodes=1
#SBATCH --ntasks=8
#SBATCH --gres=gpu:l40s:1
#SBATCH --time=04:00:00
#SBATCH --job-name=ddpm_hi_lh6_eval
#SBATCH --mail-user=<your-email> # replace before submitting
#SBATCH --output=slurm-eval-%j.out
#SBATCH --error=slurm-eval-%j.err
# Evaluate conditional DDPM (6 CAMELS LH parameters).
# Submit:
# sbatch <DDPM_ROOT>/Models/6param_ddpm_hi_lh6/scripts/shell/evaluate_conditional_lh6.sh
#
# Optional overrides (example):
# sbatch --export=CHECKPOINT=/path/to/best_model.pt,OUTPUT_DIR=/path/to/eval_out evaluate_conditional_lh6.sh
REPO="<DDPM_ROOT>/Models/6param_ddpm_hi_lh6"
cd "${REPO}" || exit 1
module load python/miniconda3-py3.12-usr
DATA_DIR="${DATA_DIR:-<DDPM_ROOT>/data/LH_data/params_6}"
# Default: trained run kept under april_26 (large artifacts not duplicated here).
CHECKPOINT="${CHECKPOINT:-<DDPM_ROOT>/april_26/ddpm_hi_lh6/outputs_conditional_6param_20260413_132226/checkpoints/best_model.pt}"
OUTPUT_DIR="${OUTPUT_DIR:-${REPO}/evaluation_outputs_6param}"
TRAINING_ARGS="${TRAINING_ARGS:-}"
echo "==============================================="
echo "Job ID: ${SLURM_JOB_ID:-local}"
echo "Job Name: ${SLURM_JOB_NAME:-evaluate_conditional_lh6}"
echo "Node: ${SLURM_NODELIST:-$(hostname)}"
echo "GPU: ${CUDA_VISIBLE_DEVICES:-n/a}"
echo "Starting Time: $(date)"
echo "CHECKPOINT: ${CHECKPOINT}"
echo "DATA_DIR: ${DATA_DIR}"
echo "OUTPUT_DIR: ${OUTPUT_DIR}"
echo "==============================================="
EVAL_ARGS=(
python evaluate_conditional.py
--checkpoint "${CHECKPOINT}"
--data_dir "${DATA_DIR}"
--output_dir "${OUTPUT_DIR}"
--split test
--num_samples 8
--ddim_steps 50
)
if [[ -n "${TRAINING_ARGS}" ]]; then
EVAL_ARGS+=(--training_args "${TRAINING_ARGS}")
fi
"${EVAL_ARGS[@]}"
echo "==============================================="
echo "Evaluation completed at: $(date)"
echo "Plots and evaluation_data.npz under: ${OUTPUT_DIR}"
echo "==============================================="
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