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>
35 lines
1.0 KiB
Bash
35 lines
1.0 KiB
Bash
#!/bin/bash
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# Train Module B (Risk Detector) on 4x RTX 5090.
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#
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# Usage:
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# bash scripts/run_detector.sh
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# bash scripts/run_detector.sh --config configs/detector_config.yaml
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#
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# NVLink not required: DDP communicates via PCIe (sufficient for MacBERT-large).
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# Mixed precision: BF16 (native on RTX 5090, ~2x throughput vs FP32).
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set -e
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CONFIG="${1:---config configs/detector_config.yaml}"
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NUM_GPUS=4
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echo "=============================================="
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echo " CompanionGuard-RL — Module B: Detector"
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echo " GPUs : ${NUM_GPUS}x RTX 5090 (PCIe DDP)"
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echo " Precision : BF16"
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echo " Config : ${CONFIG}"
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echo "=============================================="
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# Verify GPU count
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ACTUAL_GPUS=$(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_detector.py ${CONFIG}
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