zhangsiyuan
766b4811be
- code/src/data/: data_generator, dataset, llm_judge, __init__ (multi-turn LLM dialogue generator, JSONL loader, LLM auto-annotator) - code/scripts/: generate_siliconflow.py (SiliconFlow async generator, 701 lines) run_detector.sh / run_intervention.sh / run_full_pipeline.sh (launch scripts) - code/configs/intervention_config.yaml: add reward.w1-w5 reference block (NOTE: v5 reward.py uses hardcoded constants; these fields are reference-only) - .gitignore: fix data/ pattern to /data/ to avoid matching code/src/data/ Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
38 lines
1.1 KiB
Bash
38 lines
1.1 KiB
Bash
#!/bin/bash
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# Train Module C (Intervention Policy) on 4x RTX 5090.
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#
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# Stage 1 — Behavior Cloning: all 4 GPUs (DDP, BF16)
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# Stage 2 — PPO fine-tuning: GPU-0 only (inherently sequential)
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#
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# Usage:
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# bash scripts/run_intervention.sh
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# bash scripts/run_intervention.sh data/processed/train.jsonl
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set -e
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TRAIN_DATA="${1:-data/processed/train.jsonl}"
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CONFIG="configs/intervention_config.yaml"
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NUM_GPUS=4
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echo "=============================================="
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echo " CompanionGuard-RL — Module C: Intervention"
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echo " Stage 1 (BC) : ${NUM_GPUS}x GPU (DDP, BF16)"
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echo " Stage 2 (PPO) : GPU-0 only"
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echo " Config : ${CONFIG}"
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echo " Train data : ${TRAIN_DATA}"
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echo "=============================================="
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ACTUAL_GPUS=$(nvidia-smi --query-gpu=name --format=csv,noheader | wc -l)
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if [ "$ACTUAL_GPUS" -lt "$NUM_GPUS" ]; then
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echo "[WARN] Expected ${NUM_GPUS} GPUs, found ${ACTUAL_GPUS}. Adjusting."
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NUM_GPUS=$ACTUAL_GPUS
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fi
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accelerate launch \
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--num_processes=${NUM_GPUS} \
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--mixed_precision=bf16 \
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--multi_gpu \
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scripts/train_intervention.py \
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--config ${CONFIG} \
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--train-data ${TRAIN_DATA}
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