| #SBATCH --job-name=al2_test_loss_102k | |
| #SBATCH --mail-type=FAIL,END | |
| #SBATCH --mail-user=dingqy@umich.edu | |
| #SBATCH --nodes=1 | |
| #SBATCH --ntasks-per-node=1 | |
| #SBATCH --cpus-per-task=4 | |
| #SBATCH --mem-per-cpu=11GB | |
| #SBATCH --time=1:00:00 | |
| #SBATCH --account=ahowens1 | |
| #SBATCH --partition=spgpu | |
| #SBATCH --qos=foe | |
| #SBATCH --reservation=spgpu_foe_nodes | |
| #SBATCH --gres=gpu:a40:1 | |
| #SBATCH --output=/nfs/turbo/coe-ahowens-nobackup/dingqy/al2_test_loss_102k-%j.log | |
| # | |
| # Sweep 102k-110k from the latest training. 102-108k on HF; 110k still local. | |
| set -eu | |
| source /nfs/turbo/coe-ahowens-nobackup/dingqy/miniforge3/etc/profile.d/conda.sh | |
| source /home/dingqy/.hf_token | |
| export HF_CACHE=/nfs/turbo/coe-ahowens-nobackup/dingqy/.cache/huggingface | |
| conda activate new_audioldm | |
| OUT=/nfs/turbo/coe-ahowens-nobackup/dingqy/al2_test_loss_shard_102k.json | |
| CKPTS=$(printf 'audioldm2_bg2fg_controlnet_rebalance/step_%08d ' \ | |
| 102000 104000 106000 108000) | |
| LOCAL_BASE=/nfs/turbo/coe-ahowens-nobackup/dingqy/AudioLDM-training-finetuning/log/audioldm2_v2/audioldm2_bg2fg_controlnet_rebalance | |
| CKPTS="$CKPTS $LOCAL_BASE/step_00110000" | |
| echo "ckpts: $CKPTS" | |
| echo "out: $OUT" | |
| python /nfs/turbo/coe-ahowens-nobackup/dingqy/eval_audioldm2_test_loss.py \ | |
| --ckpts $CKPTS \ | |
| --out "$OUT" \ | |
| --batch-size 8 --num-workers 4 | |
| echo "" | |
| echo "=== sorted by step ===" | |
| python -c " | |
| import json, re | |
| r = json.load(open('$OUT')) | |
| def step(k): return int(re.search(r'step_0*(\d+)', k).group(1)) | |
| for k in sorted(r.keys(), key=step): | |
| print(f' step={step(k):>6} loss={r[k][\"test_loss\"]:.5f}') | |
| " | |