code/train_spatial_l_phase2.sh

#!/bin/bash
# SpatialDiffuseSlot Phase-2: DiT UNFROZEN, encoder와 동일 warmup lr로 함께 학습.
# step380000 가중치(encoder+pool+DiT+cond) 로드 -> fresh optimizer/scheduler(공동 warmup).
# Usage: GPUS=0,1,2,3 bash train_spatial_l_phase2.sh
set -e
cd "$(dirname "$0")"
VENV=/NHNHOME/WORKSPACE/0226010398_A/sr_diffusion/clevr_sudoku/MNIST_debug/venv
[ -d "$VENV" ] && source "$VENV/bin/activate"
export CUDA_VISIBLE_DEVICES="${GPUS:-0,1,2,3}"
export TORCH_HOME=/NHNHOME/WORKSPACE/0226010398_A/torch_cache
export PHASE2_RESUME_STEP="${PHASE2_RESUME_STEP:-390000}"   # LR 스케줄을 step380000 지점부터 (원래 warmup 이어감)
NG=$(echo "$CUDA_VISIBLE_DEVICES" | tr ',' '\n' | wc -l)
accelerate launch --num_processes "$NG" --multi_gpu \
  train_net.py --cfg configs/tokenizer_l_spatial_phase2.yaml