Add bootstrap step for machines without conda or the upstream clone

SETUP.md sent a fresh machine straight to setup_env.sh, which calls conda and
builds inside ~/sum-parts. Neither exists on a clean box, so the first command
failed. This repo only carries our scripts; the benchmark itself is a separate
clone.

bootstrap.sh installs miniconda into $HOME (no sudo), clones
tudelft3d/SUM-Parts-Benchmarks, and reports whether the GPU has room for the
paper's voxel_max=64000 (~16.5 GB). Idempotent - an existing install or clone
is reported and left alone.

Co-Authored-By: Claude Opus 5 (1M context) <noreply@anthropic.com>
This commit is contained in:
nbright
2026-08-21 11:22:22 +09:00
co-authored by Claude Opus 5
parent 609d9a6972
commit bcb085754c
3 changed files with 113 additions and 3 deletions
+14
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# Shell scripts and python run inside WSL/Linux. Checking them out with CRLF
# breaks them at the first line: `bash: $'\r': command not found`.
# Force LF regardless of the platform doing the checkout.
*.sh text eol=lf
*.py text eol=lf
*.yaml text eol=lf
*.yml text eol=lf
*.md text
*.html text
*.ply binary
*.obj binary
*.pth binary
+31 -3
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@@ -13,8 +13,18 @@ RTX 3090(24GB) 머신에서 SUM Parts + PointVector 학습을 재현하는 절
|---|---|
| OS | Windows + WSL2 (Ubuntu 22.04) 또는 네이티브 Linux |
| GPU | RTX 3090 24GB, 드라이버가 WSL에서 인식될 것 |
| 디스크 | 40GB 이상 여유 (데이터 13GB + 환경 + 체크포인트) |
| 디스크 | **35GB 이상 여유** |
| 계정 | HuggingFace 계정 (데이터 게이트 수락에 필요) |
| 도구 | `git`, `curl` (sudo는 불필요) |
디스크 내역 — 전부 이 절차가 만들어낸다:
| 항목 | 크기 |
|---|---|
| miniconda + 환경 | 12 GB |
| 업스트림 소스 | 1.7 GB |
| 데이터셋 (아카이브 포함) | 18 GB |
| 체크포인트·로그 | 1.5 GB |
WSL이면 `nvidia-smi`가 WSL 안에서 GPU를 보여야 한다. 안 보이면 여기서 멈추고 드라이버부터.
@@ -42,10 +52,28 @@ grep -rl '/mnt/d/MYCLAUDE_PROJECT/sum-parts-test/scripts' scripts/ \
---
## 2. 환경 구축 (약 40분)
## 2. 환경 구축 (약 50분)
먼저 부트스트랩. **새 머신에는 miniconda도 업스트림 소스도 없다**
이 레포에는 우리 스크립트만 들어 있고, 벤치마크 본체는 별도 clone이 필요하다.
```bash
bash scripts/setup_env.sh # conda + CUDA 11.8 + torch 2.0.1
bash scripts/bootstrap.sh # miniconda 설치 + 업스트림 clone + GPU 확인
```
이게 만드는 것:
| 경로 | 내용 | 크기 |
|---|---|---|
| `~/miniconda3` | conda (sudo 불필요, $HOME에 설치) | 0.5 GB |
| `~/sum-parts` | [SUM-Parts-Benchmarks](https://github.com/tudelft3d/SUM-Parts-Benchmarks) clone | 1.7 GB |
부트스트랩 끝에 GPU 용량을 찍어준다. **24GB면 `voxel_max=64000` 가능**하다고 알려준다.
이어서 환경:
```bash
bash scripts/setup_env.sh # conda env + CUDA 11.8 + torch 2.0.1
bash scripts/setup_pointnext.sh # 의존성 + CUDA 확장 5종 빌드
```
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#!/usr/bin/env bash
# SUM Parts - bring a bare machine to the point where setup_env.sh can run
#
# setup_env.sh and setup_pointnext.sh both assume two things already exist:
# ~/miniconda3 (they call conda directly)
# ~/sum-parts (the upstream benchmark clone they build inside)
#
# On a fresh machine neither is there, so this runs first. Idempotent: an
# existing miniconda or clone is left alone.
#
# No sudo anywhere. Miniconda installs to $HOME, and the CUDA toolkit comes
# from conda rather than apt, so this works on locked-down machines.
set -euo pipefail
CONDA_ROOT="$HOME/miniconda3"
REPO_DIR="$HOME/sum-parts"
UPSTREAM="https://github.com/tudelft3d/SUM-Parts-Benchmarks.git"
echo "=== [1/3] miniconda ==="
if [ -x "$CONDA_ROOT/bin/conda" ]; then
echo " present: $($CONDA_ROOT/bin/conda --version)"
else
echo " installing to $CONDA_ROOT"
TMP=$(mktemp -d)
curl -fsSL -o "$TMP/miniconda.sh" \
https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash "$TMP/miniconda.sh" -b -p "$CONDA_ROOT"
rm -rf "$TMP"
echo " installed: $($CONDA_ROOT/bin/conda --version)"
fi
echo
echo "=== [2/3] upstream benchmark repo ==="
if [ -d "$REPO_DIR/.git" ]; then
echo " present: $REPO_DIR ($(cd "$REPO_DIR" && git log --oneline -1))"
else
echo " cloning $UPSTREAM"
git clone --depth 1 "$UPSTREAM" "$REPO_DIR"
echo " cloned: $(cd "$REPO_DIR" && git log --oneline -1)"
fi
BUNDLE="$REPO_DIR/semantic_segmentation/PointNeXt_bundle"
if [ ! -d "$BUNDLE" ]; then
echo "error: $BUNDLE missing -- upstream layout changed?" >&2
exit 1
fi
echo " bundle: $BUNDLE"
echo
echo "=== [3/3] GPU visible ==="
if ! command -v nvidia-smi > /dev/null; then
echo " WARNING: nvidia-smi not found. On WSL2 this means the driver is not"
echo " exposing the GPU; fix that before continuing -- nothing below works"
echo " without it."
else
nvidia-smi --query-gpu=name,memory.total,driver_version --format=csv,noheader
TOTAL=$(nvidia-smi --query-gpu=memory.total --format=csv,noheader,nounits | head -1)
echo
if [ "$TOTAL" -ge 20000 ]; then
echo " ${TOTAL} MiB -- the paper setting voxel_max=64000 (needs ~16.5 GB) fits."
else
echo " ${TOTAL} MiB -- voxel_max=64000 needs ~16.5 GB and will NOT fit."
echo " Use scripts/sweep_voxel_max.sh to find the largest value that does."
fi
fi
echo
echo "BOOTSTRAP DONE -- next: bash scripts/setup_env.sh"