can you provide 0.02% S3DIS experiment scripts？
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FIXME mask mode grid, size 8, ratio 0.75
FIXME unp weight 0.
FIXME mask weight 5
CUDA_VISIBLE_DEVICES=4 python launch.py --master_port=27536 ddp_train.py --config config.exp/default-pazhou001.yaml
GENERAL.exp_name 2e-4_percentage_ts_notAlign_PSD_nogColorJitter_noUnp_jsV2_mask075GridSize8_extraMaskStreamSelfCorr_weight5_noThres
TRAINER.name TwoStreamTrainer
MODEL.out_channels 13
DATA.name StanfordDataLoader
DATA.dataset StanfordArea5Dataset
DATA.voxel_size 0.05
DATA.batch_size 2
DATA.train_limit_numpoints 1000000
OPTIMIZER.lr 0.01
OPTIMIZER.weight_decay 0.001
SCHEDULER.name PolyLR
TRAINER.epochs 180
EVALUATOR.iou_num_class 13
DATA.stanford3d_sampled_inds /home/liulizhao/datasets/stanford_fully_supervised_preprocessed/points/percentage0.0002evenc
DATA.sparse_label False
DATA.two_stream True
MODEL.two_stream_model_apply True
TRAINER.two_stream_feats_key semantic_scores
TRAINER.two_stream_loss_mode js_divergence_v2
TRAINER.two_stream_seg_both True
TRAINER.two_stream_loss_weight 0.0
AUGMENTATION.use_color_jitter False
TRAINER.two_stream_mask_ratio 0.75
TRAINER.two_stream_mask_mode grid
TRAINER.two_stream_loss_mask_mode js_divergence_v2
TRAINER.two_stream_mask_extra_stream True
TRAINER.two_stream_mask_feats_key semantic_scores
TRAINER.two_stream_mask_corr_loss True
TRAINER.two_stream_mask_self_loss True
TRAINER.two_stream_loss_mask_weight 5.
TRAINER.two_stream_mask_loss_threshold -1.
TRAINER.empty_cache_every 1