Release of PromptSRC with pretrained models.
This commit is contained in:
uzair khattak
54
scripts/maple/base2new_test_maple.sh
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54
scripts/maple/base2new_test_maple.sh
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#!/bin/bash
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#cd ../..
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# custom config
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DATA="/home/gamerx/Documents/datasets"
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TRAINER=MaPLe
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DATASET=$1
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SEED=$2
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CFG=vit_b16_c2_ep5_batch4_2ctx
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SHOTS=16
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LOADEP=5
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SUB=new
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COMMON_DIR=${DATASET}/shots_${SHOTS}/${TRAINER}/${CFG}/seed${SEED}
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MODEL_DIR=output/base2new/train_base/${COMMON_DIR}
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DIR=output/base2new/test_${SUB}/${COMMON_DIR}
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if [ -d "$DIR" ]; then
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echo "Evaluating model"
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echo "Results are available in ${DIR}. Resuming..."
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python train.py \
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--root ${DATA} \
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--seed ${SEED} \
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--trainer ${TRAINER} \
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--dataset-config-file configs/datasets/${DATASET}.yaml \
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--config-file configs/trainers/${TRAINER}/${CFG}.yaml \
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--output-dir ${DIR} \
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--model-dir ${MODEL_DIR} \
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--load-epoch ${LOADEP} \
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--eval-only \
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DATASET.NUM_SHOTS ${SHOTS} \
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DATASET.SUBSAMPLE_CLASSES ${SUB}
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else
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echo "Evaluating model"
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echo "Runing the first phase job and save the output to ${DIR}"
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python train.py \
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--root ${DATA} \
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--seed ${SEED} \
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--trainer ${TRAINER} \
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--dataset-config-file configs/datasets/${DATASET}.yaml \
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--config-file configs/trainers/${TRAINER}/${CFG}.yaml \
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--output-dir ${DIR} \
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--model-dir ${MODEL_DIR} \
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--load-epoch ${LOADEP} \
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--eval-only \
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DATASET.NUM_SHOTS ${SHOTS} \
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DATASET.SUBSAMPLE_CLASSES ${SUB}
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fi
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39
scripts/maple/base2new_train_maple.sh
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39
scripts/maple/base2new_train_maple.sh
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#!/bin/bash
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#cd ../..
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# custom config
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DATA="/home/gamerx/Documents/datasets"
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TRAINER=MaPLe
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DATASET=$1
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SEED=$2
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CFG=vit_b16_c2_ep5_batch4_2ctx
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SHOTS=16
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DIR=output/base2new/train_base/${DATASET}/shots_${SHOTS}/${TRAINER}/${CFG}/seed${SEED}
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if [ -d "$DIR" ]; then
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echo "Results are available in ${DIR}. Resuming..."
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python train.py \
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--root ${DATA} \
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--seed ${SEED} \
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--trainer ${TRAINER} \
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--dataset-config-file configs/datasets/${DATASET}.yaml \
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--config-file configs/trainers/${TRAINER}/${CFG}.yaml \
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--output-dir ${DIR} \
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DATASET.NUM_SHOTS ${SHOTS} \
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DATASET.SUBSAMPLE_CLASSES base
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else
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echo "Run this job and save the output to ${DIR}"
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python train.py \
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--root ${DATA} \
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--seed ${SEED} \
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--trainer ${TRAINER} \
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--dataset-config-file configs/datasets/${DATASET}.yaml \
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--config-file configs/trainers/${TRAINER}/${CFG}.yaml \
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--output-dir ${DIR} \
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DATASET.NUM_SHOTS ${SHOTS} \
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DATASET.SUBSAMPLE_CLASSES base
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fi
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58
scripts/maple/reproduce_maple.sh
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58
scripts/maple/reproduce_maple.sh
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#!/bin/bash
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#cd ../..
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# custom config
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DATA="/path/to/dataset/folder"
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TRAINER=MaPLe
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DATASET=$1
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SEED=$2
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WEIGHTSPATH=$3
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CFG=vit_b16_c2_ep5_batch4_2ctx
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SHOTS=16
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LOADEP=5
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SUB_base=base
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SUB_novel=new
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COMMON_DIR=${DATASET}/shots_${SHOTS}/${TRAINER}/${CFG}/seed${SEED}
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MODEL_DIR=${WEIGHTSPATH}/base/seed${SEED}
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DIR_base=output/base2new/test_${SUB_base}/${COMMON_DIR}
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DIR_novel=output/base2new/test_${SUB_novel}/${COMMON_DIR}
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if [ -d "$DIR" ]; then
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echo "Results are already available in ${DIR}. Skipping..."
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else
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echo "Evaluating model"
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echo "Runing the first phase job and save the output to ${DIR}"
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# Evaluate on base classes
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python train.py \
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--root ${DATA} \
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--seed ${SEED} \
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--trainer ${TRAINER} \
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--dataset-config-file configs/datasets/${DATASET}.yaml \
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--config-file configs/trainers/${TRAINER}/${CFG}.yaml \
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--output-dir ${DIR_base} \
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--model-dir ${MODEL_DIR} \
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--load-epoch ${LOADEP} \
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--eval-only \
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DATASET.NUM_SHOTS ${SHOTS} \
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DATASET.SUBSAMPLE_CLASSES ${SUB_base}
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# Evaluate on novel classes
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python train.py \
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--root ${DATA} \
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--seed ${SEED} \
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--trainer ${TRAINER} \
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--dataset-config-file configs/datasets/${DATASET}.yaml \
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--config-file configs/trainers/${TRAINER}/${CFG}.yaml \
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--output-dir ${DIR_novel} \
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--model-dir ${MODEL_DIR} \
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--load-epoch ${LOADEP} \
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--eval-only \
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DATASET.NUM_SHOTS ${SHOTS} \
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DATASET.SUBSAMPLE_CLASSES ${SUB_novel}
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fi
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38
scripts/maple/reproduce_maple_xd.sh
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38
scripts/maple/reproduce_maple_xd.sh
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#!/bin/bash
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#cd ../..
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# custom config
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DATA="/path/to/dataset/folder"
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TRAINER=MaPLe
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DATASET=$1
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SEED=$2
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WEIGHTSPATH=$3
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CFG=vit_b16_c2_ep5_batch4_2ctx_cross_datasets
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SHOTS=16
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LOADEP=2
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MODEL_DIR=${WEIGHTSPATH}/seed${SEED}
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DIR=output/evaluation/${TRAINER}/${CFG}_${SHOTS}shots/${DATASET}/seed${SEED}
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if [ -d "$DIR" ]; then
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echo "Results are already available in ${DIR}. Skipping..."
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else
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echo "Evaluating model"
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echo "Runing the first phase job and save the output to ${DIR}"
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# Evaluate on evaluation datasets
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python train.py \
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--root ${DATA} \
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--seed ${SEED} \
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--trainer ${TRAINER} \
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--dataset-config-file configs/datasets/${DATASET}.yaml \
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--config-file configs/trainers/${TRAINER}/${CFG}.yaml \
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--output-dir ${DIR} \
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--model-dir ${MODEL_DIR} \
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--load-epoch ${LOADEP} \
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--eval-only \
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DATASET.NUM_SHOTS ${SHOTS} \
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fi
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32
scripts/maple/xd_test_maple.sh
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32
scripts/maple/xd_test_maple.sh
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@@ -0,0 +1,32 @@
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#!/bin/bash
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#cd ../..
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# custom config
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DATA="/path/to/dataset/folder"
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TRAINER=MaPLe
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DATASET=$1
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SEED=$2
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CFG=vit_b16_c2_ep5_batch4_2ctx_cross_datasets
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SHOTS=16
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DIR=output/evaluation/${TRAINER}/${CFG}_${SHOTS}shots/${DATASET}/seed${SEED}
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if [ -d "$DIR" ]; then
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echo "Results are available in ${DIR}. Skip this job"
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else
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echo "Run this job and save the output to ${DIR}"
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python train.py \
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--root ${DATA} \
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--seed ${SEED} \
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--trainer ${TRAINER} \
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--dataset-config-file configs/datasets/${DATASET}.yaml \
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--config-file configs/trainers/${TRAINER}/${CFG}.yaml \
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--output-dir ${DIR} \
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--model-dir output/imagenet/${TRAINER}/${CFG}_${SHOTS}shots/seed${SEED} \
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--load-epoch 2 \
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--eval-only
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fi
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30
scripts/maple/xd_train_maple.sh
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30
scripts/maple/xd_train_maple.sh
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@@ -0,0 +1,30 @@
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#!/bin/bash
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#cd ../..
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# custom config
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DATA="/path/to/dataset/folder"
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TRAINER=MaPLe
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DATASET=$1
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SEED=$2
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CFG=vit_b16_c2_ep5_batch4_2ctx_cross_datasets
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SHOTS=16
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DIR=output/${DATASET}/${TRAINER}/${CFG}_${SHOTS}shots/seed${SEED}
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if [ -d "$DIR" ]; then
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echo "Results are available in ${DIR}."
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else
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echo "Run this job and save the output to ${DIR}"
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python train.py \
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--root ${DATA} \
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--seed ${SEED} \
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--trainer ${TRAINER} \
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--dataset-config-file configs/datasets/${DATASET}.yaml \
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--config-file configs/trainers/${TRAINER}/${CFG}.yaml \
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--output-dir ${DIR} \
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DATASET.NUM_SHOTS ${SHOTS}
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fi
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