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#!/usr/bin/env bash
# The port for communication. Note that if you want to run multiple tasks on the same machine,
# you need to specify different port numbers.
export MASTER_PORT=6081
export CUDA_VISIBLE_DEVICES=4,5,6,7
export GPUS_PER_NODE=4
user_dir=../../ofa_module
bpe_dir=../../utils/BPE
selected_cols=0,2,3,4,5
data=../../dataset/snli_ve_data/snli_ve_dev.tsv
path=../../checkpoints/ofa_base.pt
result_path=../../results/snli_ve
split='snli_ve_zeroshot'
python3 -m torch.distributed.launch --nproc_per_node=${GPUS_PER_NODE} --master_port=${MASTER_PORT} ../../evaluate.py \
${data} \
--path=${path} \
--user-dir=${user_dir} \
--bpe-dir=${bpe_dir} \
--selected-cols=${selected_cols} \
--task=snli_ve \
--patch-image-size=384 \
--max-src-length=80 \
--batch-size=16 \
--log-format=simple --log-interval=10 \
--seed=7 \
--gen-subset=${split} \
--results-path=${result_path} \
--zero-shot \
--prompt-type='prev_output' \
--fp16 \
--num-workers=0 |