96 lines
2.7 KiB
Bash
Executable File
96 lines
2.7 KiB
Bash
Executable File
#!/usr/bin/env bash
|
||
# Action Recognition 训练 — 基于 SubPattern 靶向生成的 AR30 题
|
||
#
|
||
# 三阶段:
|
||
# Phase 0: baseline infer (AR30 题 + VME benchmark 作为 test)
|
||
# Phase 1: create seed (ar30-baseline)
|
||
# Phase 2: train (3 epochs, per_category)
|
||
#
|
||
# 用法:
|
||
# CUDA_VISIBLE_DEVICES=0 bash scripts/train_ar30.sh
|
||
# MODE=mock bash scripts/train_ar30.sh # 跳过 Phase 0/1
|
||
#
|
||
# 与上次训练的区别:
|
||
# - 题目来源: generated-ar30（SubPattern 靶向）替代 generated-v2-360（OCR 污染）
|
||
# - seed 名: ar30-baseline（独立于旧的 v2ar-baseline）
|
||
# - workspace: workspaces/train-ar30
|
||
|
||
set -euo pipefail
|
||
|
||
cd "$(dirname "$0")/.."
|
||
|
||
CUDA_VISIBLE_DEVICES="${CUDA_VISIBLE_DEVICES:-0}"
|
||
export CUDA_VISIBLE_DEVICES
|
||
|
||
export HF_HUB_OFFLINE=1
|
||
export TRANSFORMERS_OFFLINE=1
|
||
export PYTHONUNBUFFERED=1
|
||
|
||
set -a
|
||
source .env
|
||
set +a
|
||
|
||
PYTHON="$(conda run -n Video-Tree-TRM which python)"
|
||
|
||
# ── Phase 0: Baseline infer（用 AR30 新题跑基线推理）──
|
||
if [[ "${MODE:-}" != "mock" ]]; then
|
||
echo "=== Phase 0: Baseline infer (AR30 新题 30 题) ==="
|
||
"${PYTHON}" main.py \
|
||
--config config/train_ar30.yaml \
|
||
--workspace-dir workspaces/default \
|
||
--store-dir store \
|
||
--mode infer \
|
||
--concurrency 24 \
|
||
--max-steps 40 \
|
||
--skill-mode auto \
|
||
--n-samples 0 \
|
||
--questions "generated-ar30" \
|
||
--skills-version v1 \
|
||
--prompts-version v1 \
|
||
--run-id ar30_baseline \
|
||
--task-types "Action Recognition"
|
||
fi
|
||
|
||
# ── Phase 1: Create seed ──
|
||
if [[ "${MODE:-}" != "mock" && ! -d "store/seeds/ar30-baseline" ]]; then
|
||
echo "=== Phase 1: Create seed ar30-baseline ==="
|
||
"${PYTHON}" -c "
|
||
from pathlib import Path
|
||
from app.harness.store import extract_run_db, init_seed
|
||
import tempfile
|
||
|
||
tmp = Path(tempfile.mkdtemp()) / 'baseline.db'
|
||
extract_run_db(
|
||
Path('workspaces/default/harness.db'),
|
||
tmp,
|
||
'infer_ar30_baseline',
|
||
)
|
||
init_seed(
|
||
store_dir=Path('store'),
|
||
name='ar30-baseline',
|
||
skills_dir=Path('store/skills/v1'),
|
||
prompts_dir=Path('store/prompts/v1'),
|
||
baseline_db=tmp,
|
||
baseline_run_id='infer_ar30_baseline',
|
||
parent=None,
|
||
description='AR30 SubPattern 靶向题 baseline (skills/v1)',
|
||
)
|
||
tmp.unlink()
|
||
print('Seed created: store/seeds/ar30-baseline/')
|
||
"
|
||
elif [[ -d "store/seeds/ar30-baseline" ]]; then
|
||
echo "=== Phase 1: Seed ar30-baseline 已存在，跳过 ==="
|
||
fi
|
||
|
||
# ── Phase 2: Train ──
|
||
echo "=== Phase 2: Train (3 epochs, AR30) ==="
|
||
"${PYTHON}" main.py \
|
||
--config config/train_ar30.yaml \
|
||
--fresh \
|
||
--seed ar30-baseline
|
||
|
||
echo "=== 训练完成 ==="
|
||
echo "结果查看:"
|
||
echo " cat workspaces/train-ar30/analyses/final_test_eval.json"
|
||
echo " sqlite3 workspaces/train-ar30/harness.db 'SELECT * FROM dual_metric'"
|