File size: 3,254 Bytes
a8eb6e5 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 | #!/bin/bash
# Preflight check: validates the training environment without GPUs or data
# Run inside the Docker container:
# docker run --rm pi05-training ./preflight.sh
PASS=0
FAIL=0
check() {
local name="$1"
shift
if "$@" > /dev/null 2>&1; then
echo " PASS $name"
PASS=$((PASS + 1))
else
echo " FAIL $name"
FAIL=$((FAIL + 1))
fi
}
echo "=== Preflight Checks ==="
echo ""
echo "-- Python & Core Packages --"
check "python 3.10" python -c "import sys; assert sys.version_info[:2] == (3,10)"
check "torch imports" python -c "import torch"
check "transformers >= 4.45" python -c "import transformers; v=transformers.__version__; assert tuple(int(x) for x in v.split('.')[:2]) >= (4,45), v"
check "accelerate imports" python -c "import accelerate"
check "lerobot imports" python -c "import lerobot"
check "wandb imports" python -c "import wandb"
check "huggingface_hub" python -c "import huggingface_hub"
echo ""
echo "-- PaliGemma Config (the previous crash) --"
check "PaliGemma registered" python -c "
from transformers import AutoConfig
# This is what crashed before - CONFIG_MAPPING['paligemma'] was None
c = AutoConfig.for_model('paligemma')
assert c is not None
"
echo ""
echo "-- FFmpeg --"
check "ffmpeg available" ffmpeg -version
check "ffmpeg version >= 6" python -c "
import subprocess, re
out = subprocess.check_output(['ffmpeg', '-version']).decode()
ver = int(re.search(r'ffmpeg version (\d+)', out).group(1))
assert ver >= 6, f'ffmpeg {ver} < 6'
"
echo ""
echo "-- Project Files --"
check "filtered_index.json" test -f /workspace/pi05-so100-diverse/filtered_index.json
check "norm_stats.json" test -f /workspace/pi05-so100-diverse/norm_stats.json
check "train_cloud.sh" test -f /workspace/pi05-so100-diverse/train_cloud.sh
check "so100_dataset.py" test -f /workspace/pi05-so100-diverse/so100_dataset.py
echo ""
echo "-- LeRobot Patches Applied --"
check "patched train script" python -c "
import lerobot.scripts.lerobot_train
import inspect
src = inspect.getsource(lerobot.scripts.lerobot_train)
assert 'early_stop_steps' in src, 'train patch not applied'
"
check "patched factory" python -c "
import lerobot.datasets.factory
import inspect
src = inspect.getsource(lerobot.datasets.factory)
assert 'so100:' in src, 'factory patch not applied'
"
echo ""
echo "-- Accelerate Multi-GPU Config --"
check "accelerate launch" accelerate launch --help
echo ""
echo "-- HuggingFace Auth --"
if [ -n "$HF_TOKEN" ]; then
check "HF_TOKEN valid" python -c "
from huggingface_hub import HfApi
api = HfApi(token='$HF_TOKEN')
api.whoami()
"
else
echo " SKIP HF_TOKEN not set (set it to validate auth + Gemma license)"
fi
echo ""
echo "-- Weights Download (dry check) --"
if [ -n "$HF_TOKEN" ]; then
check "pi05_base accessible" python -c "
from huggingface_hub import HfApi
api = HfApi(token='$HF_TOKEN')
info = api.model_info('lerobot/pi05_base')
assert info is not None
"
else
echo " SKIP Need HF_TOKEN to check model access"
fi
echo ""
echo "================================"
echo " Results: $PASS passed, $FAIL failed"
echo "================================"
[ "$FAIL" -eq 0 ] && exit 0 || exit 1
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