export http_proxy=http://127.0.0.1:1082
export https_proxy=http://127.0.0.1:1082
export HTTP_PROXY=http://127.0.0.1:1082
export HTTPS_PROXY=http://127.0.0.1:1082
unset all_proxy ALL_PROXY

CUDA_VISIBLE_DEVICES=1 python sample_msn_v3.py \
    dataset.root_dir='/mnt/nas1/disk01/weidongguo/dataset/medshapenet/data_in_category_with_one_component_crop_zoom56_pad64_sdf_new_64' \
    dataset.name='msn' \
    dataset.batch_size=12 \
    dataset.minibatch_size=4 \
    dataset.text_embedding_file='data_preproc/claude_sonnet_4.5_prompt_qwen3_32b_embedding.json' \
    model.timesteps=50 \
    model.use_mask_guide=False \
    model.use_mask_cond=True \
    model.cond_num=3 \
    model.use_oneplane=False \
    model.use_triplane=True \
    model.use_multiplane=True \
    model.use_broken=True \
    model.output_dir='output-farm02/COND3__use_triplane__use_multiplane__use_broken__cp20' \
    model.checkpoint_for_sample='EXP/COND/LR0.001__BS24__TS50__COND3__use_triplane__use_multiplane__use_broken/model-20.pt' \
    vae.pvqvae_ckpt='pretrained_models/pvqvae.pth'