| #!/bin/bash |
| now=$(date +"%Y%m%d_%H%M%S") |
|
|
| epoch=20 |
| bs=24 |
| gpus=2 |
| lr=0.000005 |
| encoder=vitl |
| dataset=dense |
| img_size=266 |
| min_depth=0 |
| max_depth=1000 |
| event_voxel_chans=3 |
| pretrained_from=/home/sph/event/da2-prompt-tuning/exp/public_checkpoints/foundation_vitl/latest.pth |
| save_path=/home/sph/event/fuse_public/exp/fuse_dense_${encoder}_${dataset}_${finetune_mode}_${now} |
|
|
| mkdir -p $save_path |
|
|
| python3 -m torch.distributed.launch \ |
| --nproc_per_node=$gpus \ |
| --nnodes 1 \ |
| --node_rank=0 \ |
| --master_addr=localhost \ |
| --master_port=20596 \ |
| train.py --epoch $epoch --encoder $encoder --bs $bs --lr $lr --save-path $save_path --dataset $dataset \ |
| --img-size $img_size --min-depth $min_depth --max-depth $max_depth \ |
| --event_voxel_chans $event_voxel_chans \ |
| --pretrained-from $pretrained_from \ |
| --port 20596 2>&1 | tee -a $save_path/$now.log |
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