iomgaa
dec7346da3
- PerCategoryPoolStrategy: filter test pool by task_types - RunConfig: add run_holdout_eval toggle (default true) - load_config: fix YAML task_types list-to-tuple conversion - Runner: conditionally skip _holdout_four_way when disabled - CLI: add --no-run-holdout-eval flag - New config/train_action_recognition.yaml (3 epochs, per_category) - New scripts/train_action_recognition.sh (baseline + seed + train)
91 lines
2.6 KiB
Bash
Executable File
91 lines
2.6 KiB
Bash
Executable File
#!/usr/bin/env bash
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# Action Recognition 单题型训练实验
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# 设计文档: research-wiki/designs/2026-07-14-action-recognition-training-design.md
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#
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# 三阶段:
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# Phase 0: baseline infer (v2-360 Action Recognition 30 题)
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# Phase 1: create seed (v2ar-baseline)
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# Phase 2: train (3 epochs, per_category)
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#
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# 用法:
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# CUDA_VISIBLE_DEVICES=0 bash scripts/train_action_recognition.sh
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# MODE=mock bash scripts/train_action_recognition.sh # 跳过 Phase 0/1
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set -euo pipefail
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cd "$(dirname "$0")/.."
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CUDA_VISIBLE_DEVICES="${CUDA_VISIBLE_DEVICES:-0}"
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export CUDA_VISIBLE_DEVICES
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export HF_HUB_OFFLINE=1
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export TRANSFORMERS_OFFLINE=1
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export PYTHONUNBUFFERED=1
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set -a
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source .env
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set +a
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PYTHON="$(conda run -n Video-Tree-TRM which python)"
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# ── Phase 0: Baseline infer ──
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if [[ "${MODE:-}" != "mock" ]]; then
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echo "=== Phase 0: Baseline infer (v2-360 Action Recognition 30 题) ==="
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"${PYTHON}" main.py \
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--config config/default.yaml \
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--workspace-dir workspaces/default \
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--store-dir store \
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--mode infer \
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--concurrency 24 \
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--max-steps 40 \
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--skill-mode auto \
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--n-samples 0 \
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--questions "generated-v2-360" \
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--skills-version v1 \
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--prompts-version v1 \
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--run-id v2ar_baseline \
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--task-types "Action Recognition"
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fi
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# ── Phase 1: Create seed ──
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if [[ "${MODE:-}" != "mock" && ! -d "store/seeds/v2ar-baseline" ]]; then
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echo "=== Phase 1: Create seed v2ar-baseline ==="
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"${PYTHON}" -c "
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from pathlib import Path
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from app.harness.store import extract_run_db, init_seed
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import tempfile
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tmp = Path(tempfile.mkdtemp()) / 'baseline.db'
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extract_run_db(
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Path('workspaces/default/harness.db'),
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tmp,
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'infer_v2ar_baseline',
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)
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init_seed(
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store_dir=Path('store'),
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name='v2ar-baseline',
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skills_dir=Path('store/skills/v1'),
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prompts_dir=Path('store/prompts/v1'),
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baseline_db=tmp,
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baseline_run_id='infer_v2ar_baseline',
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parent=None,
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description='v2-360 Action Recognition 30 题 baseline (skills/v1)',
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)
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tmp.unlink()
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print('Seed created: store/seeds/v2ar-baseline/')
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"
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elif [[ -d "store/seeds/v2ar-baseline" ]]; then
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echo "=== Phase 1: Seed v2ar-baseline 已存在，跳过 ==="
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fi
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# ── Phase 2: Train ──
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echo "=== Phase 2: Train (3 epochs, Action Recognition) ==="
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"${PYTHON}" main.py \
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--config config/train_action_recognition.yaml \
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--fresh \
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--seed v2ar-baseline
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echo "=== 训练完成 ==="
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echo "结果查看:"
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echo " cat workspaces/train-action-recognition/analyses/final_test_eval.json"
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echo " sqlite3 workspaces/train-action-recognition/harness.db 'SELECT * FROM dual_metric'"
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