pretrain_convmae.sh

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# 
# Licensed under the Apache License, Version 2.0 (the "License");
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# 
#     http://www.apache.org/licenses/LICENSE-2.0
# 
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unset PADDLE_TRAINER_ENDPOINTS
export PADDLE_NNODES=3
export PADDLE_MASTER="10.67.228.16:12538"
export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
export PADDLE_JOB_ID=ConvMAE

# 3 nodes for pretrain
ACCUM_ITER=1
IMAGENET_DIR=./dataset/ILSVRC2012/
python -m paddle.distributed.launch \
    --nnodes=$PADDLE_NNODES \
    --master=$PADDLE_MASTER \
    --devices=$CUDA_VISIBLE_DEVICES \
    main_pretrain.py \
    --accum_iter $ACCUM_ITER \
    --batch_size 128 \
    --model convmae_convvit_base_patch16 \
    --norm_pix_loss \
    --mask_ratio 0.75 \
    --epochs 1600 \
    --warmup_epochs 40 \
    --blr 1.5e-4 --weight_decay 0.05 \
    --data_path ${IMAGENET_DIR}