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#!/bin/bash |
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set -ex |
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gpu_rank=$1 |
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quantize_size=$2 |
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model_path=$3 |
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eval_json=$4 |
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ann_json=$5 |
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dir_path=`dirname $model_path` |
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file_name=`basename $model_path` |
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eval_name=$(echo "$eval_json" | sed -E 's/.*finetune_(.*)\.json.*/\1/' | sed 's/_/./') |
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template_post_name=$(echo "$eval_json" | sed 's/.*\.json//' ) |
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eval_out_post_name=".eval.${eval_name}${template_post_name}" |
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result_post_name="${eval_out_post_name}.result" |
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master_port=$((RANDOM%1000+20000)) |
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cat $eval_json | CUDA_VISIBLE_DEVICES=$gpu_rank python -m torch.distributed.launch --nproc_per_node=1 --master_port=$master_port evaluation/caption_obj_few_shot.py None \ |
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--task generation_obj \ |
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--path $model_path \ |
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--model-overrides "{'visual_pretrained': '', |
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'dict_path':'data/dict.txt'}" \ |
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--dict-path 'data/dict.txt' \ |
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--required-batch-size-multiple 1 \ |
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--remove-bpe=sentencepiece \ |
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--max-len-b 500 \ |
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--add-bos-token \ |
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--beam 1 \ |
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--buffer-size 10 \ |
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--image-feature-length 64 \ |
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--locate-special-token 1 \ |
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--batch-size 1 \ |
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--nbest 1 \ |
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--no-repeat-ngram-size 3 \ |
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--location-bin-size $quantize_size > $dir_path/${file_name}$eval_out_post_name |
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python evaluation/refcoco/refexp_evaluate.py $dir_path/${file_name}$eval_out_post_name ${ann_json} --quantized_size $quantize_size > $dir_path/${file_name}$result_post_name |
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tail -n 6 $dir_path/${file_name}$result_post_name |
