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#!/bin/bash
export CUDA_VISIBLE_DEVICES="0,1,2,3,4,5,6,7"
gpu_list="${CUDA_VISIBLE_DEVICES:-0}"
IFS=',' read -ra GPULIST <<< "$gpu_list"
CHUNKS=${#GPULIST[@]}
echo "CHUNKS: $CHUNKS"
CKPT="voco_llava"
SPLIT="llava_vqav2_mscoco_test-dev2015"
for IDX in $(seq 0 $((CHUNKS-1))); do
CUDA_VISIBLE_DEVICES=${GPULIST[$IDX]} python -m llava.eval.model_vqa_loader \
--model-path ./checkpoints/voco_llava_ckpt \
--question-file ./playground/data/eval/vqav2/$SPLIT.jsonl \
--image-folder ./playground/data/eval/vqav2/test2015 \
--answers-file ./playground/data/eval/vqav2/answers/$SPLIT/$CKPT/${CHUNKS}_${IDX}.jsonl \
--voco_num 2 \
--num-chunks $CHUNKS \
--chunk-idx $IDX \
--temperature 0 \
--conv-mode vicuna_v1 &
done
wait
output_file=./playground/data/eval/vqav2/answers/$SPLIT/$CKPT/merge.jsonl
# Clear out the output file if it exists.
> "$output_file"
# Loop through the indices and concatenate each file.
for IDX in $(seq 0 $((CHUNKS-1))); do
cat ./playground/data/eval/vqav2/answers/$SPLIT/$CKPT/${CHUNKS}_${IDX}.jsonl >> "$output_file"
done
python scripts/convert_vqav2_for_submission.py --split $SPLIT --ckpt $CKPT
# CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 bash scripts/eval/vqav2.sh |