Linear Evaluation

We provide the linear evaluation scripts here. The evaluation setting mainly follows MAE, which uses 16384 batch size and LARS optimizer.

Train with torch.distributed.launch

This method supports training on multi-nodes with torch.distributed.launch. For example, to conduct linear evaluation on 2 nodes, run the command below.

On node 1:

  sh ./configs/linprobe/dist_linprobe_sim_base.sh ${MASTER_ADDR} 0 2 ${CKPT_PATH} ${DATA_PATH}

On node 2:

  sh ./configs/linprobe/dist_linprobe_sim_base.sh ${MASTER_ADDR} 1 2 ${CKPT_PATH} ${DATA_PATH}

Note: The ${MASTER_ADDR} is the ip address of rank 0 node. The second and third arguments specify the node rank and node number respectively. You need to adjust them if different node numbders are used.

Train on a slurm cluster

If you need to run the linear evaluation on a slurm cluster, use the command below to run on ${GPUS}/${GPUS_PER_NODE} nodes with ${GPUS_PER_NODE} gpus on each node:

  sh ./configs/linprobe/slurm_linprobe_sim_base.sh ${GPUS} ${GPUS_PER_NODE} ${QUOTATYPE} ${PARTITION} ${CKPT_PATH} ${DATA_PATH}