OFA-OCR / run_scripts /caption /evaluate_caption.sh
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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=1081
export CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7
export GPUS_PER_NODE=8
user_dir=../../ofa_module
bpe_dir=../../utils/BPE
data=../../dataset/caption_data/caption_test.tsv
path=../../checkpoints/caption_large_best_clean.pt
result_path=../../results/caption
selected_cols=1,4,2
split='test'
python3 -m torch.distributed.launch --nproc_per_node=${GPUS_PER_NODE} --master_port=${MASTER_PORT} ../../evaluate.py \
${data} \
--path=${path} \
--user-dir=${user_dir} \
--task=caption \
--batch-size=16 \
--log-format=simple --log-interval=10 \
--seed=7 \
--gen-subset=${split} \
--results-path=${result_path} \
--beam=5 \
--max-len-b=16 \
--no-repeat-ngram-size=3 \
--fp16 \
--num-workers=0 \
--model-overrides="{\"data\":\"${data}\",\"bpe_dir\":\"${bpe_dir}\",\"eval_cider\":False,\"selected_cols\":\"${selected_cols}\"}"
python coco_eval.py ../../results/caption/test_predict.json ../../dataset/caption_data/test_caption_coco_format.json