Giorgio Gilestro
84124de143
Clarity pass over the main text (36-item audit), Discussion rewrite and cut, acknowledgements, Souly et al. as ref 62, lettered SI panels, model section moved under Results; plus the untracked curriculum/society/compose/smol configs, runners, figures, stats and tests that the SI already cites. Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01Y64o8FKP7rCuXzC48pxpMm
43 lines
1.6 KiB
Bash
Executable file
43 lines
1.6 KiB
Bash
Executable file
#!/bin/bash
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# The composition campaign (prereg tasks/prereg-llm-compose-v3.md): one (seed, arm) per array
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# element. Seed 1 runs locally on the A4000 as the hedge; this array covers seeds 2-3 x 3 arms.
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# Each element trains its own founders (cached per seed under models/, first writer wins via the
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# adapter_config.json check) and checkpoints every generation, so a requeued element resumes.
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# submit: qsub hpc/llm_compose.pbs status: qstat -u $USER -t
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# index -> seed = 2 + (i-1)/3, arm = (dry grounded dry_cat)[(i-1)%3]
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#PBS -l select=1:ncpus=8:mem=64gb:ngpus=1:gpu_type=L40S
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#PBS -l walltime=08:00:00
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#PBS -N lam_compose
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#PBS -J 1-6
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cd "$PBS_O_WORKDIR"
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export HF_HOME="$EPHEMERAL/hf_cache"
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export HF_DATASETS_CACHE="$EPHEMERAL/hf_cache/datasets"
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export TOKENIZERS_PARALLELISM=false
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export UV_CACHE_DIR="$EPHEMERAL/uvcache"
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ARMS=(dry grounded dry_cat)
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I=$((PBS_ARRAY_INDEX - 1))
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SEED=$((2 + I / 3))
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ARM=${ARMS[$((I % 3))]}
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source .venv/bin/activate
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nvidia-smi --query-gpu=name,memory.total,driver_version --format=csv,noheader
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echo "seed=$SEED arm=$ARM start=$(date)"
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CFG="configs/llm/_gen/compose_s${SEED}_${ARM}.yaml"
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mkdir -p configs/llm/_gen
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python - "$SEED" "$ARM" "$CFG" <<'EOF'
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import sys, yaml
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seed, arm, out = int(sys.argv[1]), sys.argv[2], sys.argv[3]
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cfg = yaml.safe_load(open("configs/llm/compose_s1.yaml"))
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cfg["seed"] = seed
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cfg["arms"] = [arm]
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cfg["batch_size"] = 32 # L40S has 46 GB; the A4000 setting is 16
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cfg["score_batch_size"] = 8
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cfg["output"] = {"dir": f"results/llm_compose/s{seed}_{arm}"}
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yaml.safe_dump(cfg, open(out, "w"), sort_keys=False)
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EOF
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python -m llm.experiment "$CFG"
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echo "done: $(date)"
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