mirror of
https://github.com/RYDE-WORK/lnp_ml.git
synced 2026-09-18 19:13:21 +08:00
95 lines
3.4 KiB
Bash
95 lines
3.4 KiB
Bash
#!/usr/bin/env bash
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# 完整 nested CV：MPNN + MoE + Qwen2.5-7B QLoRA + soft-RAG
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# 单卡一个分片。被 OOM / 抢占 / 断连杀掉后自动等显存并续跑。
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set -uo pipefail
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GPU=${GPU:?必须指定，例如 GPU=0}
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SEED=${SEED:-42}
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FOLDS=${FOLDS:-} # 空=跑全部 5 折；"0,1,2"=只跑这三折
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REG_BYPASS=${REG_BYPASS:-on} # on=delivery/size 绕开 MoE+LLM；off=接入
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BATCH=${BATCH:-8} # 显存紧就设 4
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N_OUTER=${N_OUTER:-5}
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N_INNER=${N_INNER:-3}
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N_TRIALS=${N_TRIALS:-20}
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EPOCHS=${EPOCHS:-20}
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PATIENCE=${PATIENCE:-5}
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MIN_FREE_MB=${MIN_FREE_MB:-14000}
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MAX_RETRY=${MAX_RETRY:-50}
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RETRY_WAIT=${RETRY_WAIT:-300}
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MIN_OK_SEC=${MIN_OK_SEC:-180} # 存活不足这么久就挂 → 判为配置/代码错误，立即停止重试
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PRETRAIN=${PRETRAIN:-} # 非空且文件存在才注入 --init-from-pretrain
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RUN_DIR="models/final_cv/${REG_BYPASS}_seed${SEED}"
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TAG="gpu${GPU}$([ -n "${FOLDS}" ] && echo "_folds$(echo "${FOLDS}" | tr -d ',')")"
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LOG="${RUN_DIR}/${TAG}.log"
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export TRANSFORMERS_OFFLINE=1
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export PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True
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export TOKENIZERS_PARALLELISM=false
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export CUDA_VISIBLE_DEVICES=${GPU}
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mkdir -p "${RUN_DIR}"
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# nvidia-smi 不受 CUDA_VISIBLE_DEVICES 影响，-i 用物理卡号
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wait_free() {
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while :; do
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local free
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free=$(nvidia-smi --query-gpu=memory.free --format=csv,noheader,nounits -i "${GPU}")
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[ "${free}" -ge "${MIN_FREE_MB}" ] && return 0
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echo "[$(date '+%F %T')] GPU${GPU} 仅空 ${free}MiB < ${MIN_FREE_MB}MiB，60s 后重试" >>"${LOG}"
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sleep 60
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done
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}
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EXTRA=()
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if [ -n "${FOLDS}" ]; then
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# 注意：需先给 nested_cv_optuna.main 增加 --only-folds 选项，否则 Typer 直接报错
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EXTRA+=(--only-folds "${FOLDS}")
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fi
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if [ -n "${PRETRAIN}" ] && [ -f "${PRETRAIN}" ]; then
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EXTRA+=(--init-from-pretrain "${PRETRAIN}")
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elif [ -n "${PRETRAIN}" ]; then
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echo "[$(date '+%F %T')] 警告：${PRETRAIN} 不存在，跳过预训练初始化" >>"${LOG}"
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fi
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for attempt in $(seq 1 "${MAX_RETRY}"); do
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wait_free
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echo "[$(date '+%F %T')] ATTEMPT ${attempt}/${MAX_RETRY} gpu=${GPU} seed=${SEED} folds=${FOLDS:-all} reg_bypass=${REG_BYPASS} batch=${BATCH} trials=${N_TRIALS}" >>"${LOG}"
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t0=${SECONDS}
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python -u -m lnp_ml.modeling.nested_cv_optuna \
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--input-path data/interim/internal.csv \
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--output-dir models/final_cv \
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--resume-dir "${RUN_DIR}" \
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--seed ${SEED} \
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--use-mpnn \
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--use-moe \
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--reg-bypass ${REG_BYPASS} \
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--use-llm --use-rag --rag-top-k 4 \
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--use-soft-prompt --llm-use-qlora \
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--llm-model-path models/qwen2.5-7b-instruct \
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--no-llm-freeze \
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--llm-max-length 1536 \
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--n-outer-folds ${N_OUTER} --n-inner-folds ${N_INNER} \
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--n-trials ${N_TRIALS} --epochs-per-trial ${EPOCHS} \
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--inner-patience ${PATIENCE} \
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--batch-size ${BATCH} --device cuda \
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${EXTRA[@]+"${EXTRA[@]}"} \
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>>"${LOG}" 2>&1
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rc=$?
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dt=$((SECONDS - t0))
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if [ ${rc} -eq 0 ]; then
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echo "[$(date '+%F %T')] DONE gpu=${GPU} folds=${FOLDS:-all}（用时 ${dt}s）" >>"${LOG}"
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exit 0
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fi
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if [ ${dt} -lt ${MIN_OK_SEC} ]; then
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echo "[$(date '+%F %T')] 仅存活 ${dt}s 即以 ${rc} 退出，判定为配置/代码错误而非抢占，停止重试" >>"${LOG}"
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exit ${rc}
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fi
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echo "[$(date '+%F %T')] 运行 ${dt}s 后以 ${rc} 退出，${RETRY_WAIT}s 后带 --resume-dir 续跑" >>"${LOG}"
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sleep "${RETRY_WAIT}"
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done
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echo "[$(date '+%F %T')] 超过 MAX_RETRY 次仍失败，放弃" >>"${LOG}"
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exit 1 |