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DenseLabelDev
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#!/bin/bash -e

set -x
set -e


num_gpus=8
output_dir="./output2/eval_computational_cost/"


# REC R50
config_files=(
	#"configs/REFCOCO_VisualGrounding/ape_deta/ape_deta_r50_12ep.py" # bs=16 for training
	#"configs/REFCOCO_VisualGrounding/ape_deta/ape_deta_r50_vlf_12ep.py" # bs=16 for training
)

for config_file in ${config_files[@]}
do
	echo "=============================================================================================="
	echo ${config_file}
	#python3.9 tools/train_net.py --dist-url=tcp://127.0.0.1:49193 --config-file ${config_file} --num-gpus ${num_gpus} train.output_dir=${output_dir}/${config_file}/"`date +'%Y%m%d_%H%M%S'`" model.model_vision.segm_type=""
	#python3.9 tools/train_net.py --eval-only --dist-url=tcp://127.0.0.1:49193 --config-file ${config_file} --num-gpus ${num_gpus} train.output_dir=${output_dir}/${config_file}/"`date +'%Y%m%d_%H%M%S'`" model.model_vision.segm_type="" model.model_vision.num_classes=1 model.model_vision.select_box_nums_for_evaluation=1 model.model_vision.test_score_thresh=0.5
	#python3.9 tools/train_net.py --eval-only --dist-url=tcp://127.0.0.1:49193 --config-file ${config_file} --num-gpus ${num_gpus} train.output_dir=${output_dir}/${config_file}/"`date +'%Y%m%d_%H%M%S'`" model.model_vision.segm_type="" model.model_vision.num_classes=128 model.model_vision.select_box_nums_for_evaluation=128 model.model_vision.test_score_thresh=0.5
	#python3.9 tools/train_net.py --eval-only --dist-url=tcp://127.0.0.1:49193 --config-file ${config_file} --num-gpus ${num_gpus} train.output_dir=${output_dir}/${config_file}/"`date +'%Y%m%d_%H%M%S'`" model.model_vision.segm_type="" model.model_vision.num_classes=1280 model.model_vision.select_box_nums_for_evaluation=1280 model.model_vision.test_score_thresh=0.5
done


# REC ViT-L
config_files=(
	#"configs/REFCOCO_VisualGrounding/ape_deta/ape_deta_vitl_eva02_clip_lsj1024_12ep.py" # bs=8 for training
	#"configs/REFCOCO_VisualGrounding/ape_deta/ape_deta_vitl_eva02_clip_vlf_lsj1024_12ep.py"  # bs=8 for training
)

kwargs="dataloader.train.total_batch_size=8 model.model_vision.segm_type=\"\" model.model_vision.test_score_thresh=0.5 model.model_language.max_batch_size=128 model.model_vision.neck.in_features=[\"p3\",\"p4\",\"p5\",\"p6\"] model.model_vision.neck.num_outs=5 model.model_vision.transformer.num_feature_levels=5 model.model_vision.backbone.scale_factors=[2.0,1.0,0.5]"
for config_file in ${config_files[@]}
do
	echo "=============================================================================================="
	echo ${config_file}
	#python3.9 tools/train_net.py --dist-url=tcp://127.0.0.1:49193 --config-file ${config_file} --num-gpus ${num_gpus} train.output_dir=${output_dir}/${config_file}/"`date +'%Y%m%d_%H%M%S'`" ${kwargs}
	#python3.9 tools/train_net.py --eval-only --dist-url=tcp://127.0.0.1:49193 --config-file ${config_file} --num-gpus ${num_gpus} train.output_dir=${output_dir}/${config_file}/"`date +'%Y%m%d_%H%M%S'`" ${kwargs} model.model_vision.num_classes=1 model.model_vision.select_box_nums_for_evaluation=1
	#python3.9 tools/train_net.py --eval-only --dist-url=tcp://127.0.0.1:49193 --config-file ${config_file} --num-gpus ${num_gpus} train.output_dir=${output_dir}/${config_file}/"`date +'%Y%m%d_%H%M%S'`" ${kwargs} model.model_vision.num_classes=128 model.model_vision.select_box_nums_for_evaluation=128
	#python3.9 tools/train_net.py --eval-only --dist-url=tcp://127.0.0.1:49193 --config-file ${config_file} --num-gpus ${num_gpus} train.output_dir=${output_dir}/${config_file}/"`date +'%Y%m%d_%H%M%S'`" ${kwargs} model.model_vision.num_classes=1280 model.model_vision.select_box_nums_for_evaluation=1280
done


# OVD R50
config_files=(
	#"configs/COCO_InstanceSegmentation/ape_deta/ape_deta_r50_12ep.py" # bs=16 for training
	#"configs/LVIS_InstanceSegmentation/ape_deta/ape_deta_r50_24ep.py" # bs=16 for training
	#"configs/COCO_InstanceSegmentation/ape_deta/ape_deta_r50_vlf_12ep.py" # bs=16 for training
	#"configs/LVIS_InstanceSegmentation/ape_deta/ape_deta_r50_vlf_24ep.py" # bs=16 for training
)

for config_file in ${config_files[@]}
do
	echo "=============================================================================================="
	echo ${config_file}
	#python3.9 tools/train_net.py --dist-url=tcp://127.0.0.1:49193 --config-file ${config_file} --num-gpus ${num_gpus} train.output_dir=${output_dir}/${config_file}/"`date +'%Y%m%d_%H%M%S'`" model.model_vision.segm_type=""
	#python3.9 tools/train_net.py --eval-only --dist-url=tcp://127.0.0.1:49193 --config-file ${config_file} --num-gpus ${num_gpus} train.output_dir=${output_dir}/${config_file}/"`date +'%Y%m%d_%H%M%S'`" model.model_vision.segm_type="" model.model_vision.test_score_thresh=0.5
done

# OVD ViT-L
config_files=(
	#"configs/COCO_InstanceSegmentation/ape_deta/ape_deta_vitl_eva02_clip_lsj1024_cp_12ep.py" # bs=8 for training
	#"configs/LVIS_InstanceSegmentation/ape_deta/ape_deta_vitl_eva02_clip_lsj1024_cp_24ep.py" # bs=8 for training
	#"configs/COCO_InstanceSegmentation/ape_deta/ape_deta_vitl_eva02_clip_vlf_lsj1024_cp_12ep.py" # bs=8 for training
	"configs/LVIS_InstanceSegmentation/ape_deta/ape_deta_vitl_eva02_clip_vlf_lsj1024_cp_24ep.py" # bs=8 for training
)

kwargs="dataloader.train.total_batch_size=8 model.model_vision.segm_type=\"\" model.model_vision.test_score_thresh=0.5 model.model_language.max_batch_size=128 model.model_vision.neck.in_features=[\"p3\",\"p4\",\"p5\",\"p6\"] model.model_vision.neck.num_outs=5 model.model_vision.transformer.num_feature_levels=5 model.model_vision.backbone.scale_factors=[2.0,1.0,0.5]"

for config_file in ${config_files[@]}
do
	echo "=============================================================================================="
	echo ${config_file}
	#python3.9 tools/train_net.py --dist-url=tcp://127.0.0.1:49193 --config-file ${config_file} --num-gpus ${num_gpus} train.output_dir=${output_dir}/${config_file}/"`date +'%Y%m%d_%H%M%S'`" ${kwargs}
	python3.9 tools/train_net.py --eval-only --dist-url=tcp://127.0.0.1:49193 --config-file ${config_file} --num-gpus ${num_gpus} train.output_dir=${output_dir}/${config_file}/"`date +'%Y%m%d_%H%M%S'`" ${kwargs}
done