| #!/bin/bash | |
| DATASET_ROOT=/dataset/imageNet100_sicy/train/ #/raid/common/imagenet-raw/ | |
| ## train ViT-large for 250 epochs | |
| OUTPUT_ROOT=./exps/vit_large_250ep | |
| NPROC_PER_NODE=40 # GPU numbers | |
| BATCH_SIZE_PER_GPU=16 | |
| DEBUG=false # debug = true, then we only load subset of the whole training dataset | |
| python -m torch.distributed.launch --nproc_per_node=$NPROC_PER_NODE main.py \ | |
| --data_path $DATASET_ROOT \ | |
| --output_dir $OUTPUT_ROOT \ | |
| --arch vit_large \ | |
| --instance_queue_size 65536 \ | |
| --local_group_queue_size 65536 \ | |
| --use_bn_in_head false \ | |
| --instance_out_dim 256 \ | |
| --instance_temp 0.2 \ | |
| --local_group_out_dim 256 \ | |
| --local_group_temp 0.2 \ | |
| --local_group_knn_top_n 8 \ | |
| --group_out_dim 65536 \ | |
| --group_student_temp 0.1 \ | |
| --group_warmup_teacher_temp 0.04 \ | |
| --group_teacher_temp 0.07 \ | |
| --group_warmup_teacher_temp_epochs 50 \ | |
| --norm_last_layer true \ | |
| --norm_before_pred true \ | |
| --batch_size_per_gpu $BATCH_SIZE_PER_GPU \ | |
| --epochs 250 \ | |
| --warmup_epochs 10 \ | |
| --clip_grad 3.0 \ | |
| --lr 0.0015 \ | |
| --min_lr 1.5e-4 \ | |
| --patch_embed_lr_mult 0.2 \ | |
| --drop_path_rate 0.3 \ | |
| --weight_decay 0.025 \ | |
| --weight_decay_end 0.12 \ | |
| --freeze_last_layer 3 \ | |
| --momentum_teacher 0.996 \ | |
| --use_fp16 false \ | |
| --local_crops_number 10 \ | |
| --size_crops 96 \ | |
| --global_crops_scale 0.25 1 \ | |
| --local_crops_scale 0.05 0.25 \ | |
| --timm_auto_augment_par rand-m9-mstd0.5-inc1 \ | |
| --prob 0.5 \ | |
| --use_prefetcher true \ | |
| --debug $DEBUG |