Release of PromptSRC with pretrained models.

scripts/promptsrc/base2new_test.sh

@@ -0,0 +1,53 @@
+#!/bin/bash
+
+
+# custom config
+DATA="/path/to/dataset/folder"
+TRAINER=PromptSRC
+
+DATASET=$1
+SEED=$2
+
+CFG=vit_b16_c2_ep20_batch4_4+4ctx
+SHOTS=16
+LOADEP=20
+SUB=new
+
+
+COMMON_DIR=${DATASET}/shots_${SHOTS}/${TRAINER}/${CFG}/seed${SEED}
+MODEL_DIR=output/base2new/train_base/${COMMON_DIR}
+DIR=output/base2new/test_${SUB}/${COMMON_DIR}
+if [ -d "$DIR" ]; then
+    echo "Evaluating model"
+    echo "Results are available in ${DIR}. Resuming..."
+
+    python train.py \
+    --root ${DATA} \
+    --seed ${SEED} \
+    --trainer ${TRAINER} \
+    --dataset-config-file configs/datasets/${DATASET}.yaml \
+    --config-file configs/trainers/${TRAINER}/${CFG}.yaml \
+    --output-dir ${DIR} \
+    --model-dir ${MODEL_DIR} \
+    --load-epoch ${LOADEP} \
+    --eval-only \
+    DATASET.NUM_SHOTS ${SHOTS} \
+    DATASET.SUBSAMPLE_CLASSES ${SUB}
+
+else
+    echo "Evaluating model"
+    echo "Runing the first phase job and save the output to ${DIR}"
+
+    python train.py \
+    --root ${DATA} \
+    --seed ${SEED} \
+    --trainer ${TRAINER} \
+    --dataset-config-file configs/datasets/${DATASET}.yaml \
+    --config-file configs/trainers/${TRAINER}/${CFG}.yaml \
+    --output-dir ${DIR} \
+    --model-dir ${MODEL_DIR} \
+    --load-epoch ${LOADEP} \
+    --eval-only \
+    DATASET.NUM_SHOTS ${SHOTS} \
+    DATASET.SUBSAMPLE_CLASSES ${SUB}
+fi

scripts/promptsrc/base2new_train.sh

@@ -0,0 +1,37 @@
+#!/bin/bash
+
+# custom config
+DATA="/path/to/dataset/folder"
+TRAINER=PromptSRC
+
+DATASET=$1
+SEED=$2
+
+CFG=vit_b16_c2_ep20_batch4_4+4ctx
+SHOTS=16
+
+
+DIR=output/base2new/train_base/${DATASET}/shots_${SHOTS}/${TRAINER}/${CFG}/seed${SEED}
+if [ -d "$DIR" ]; then
+    echo "Results are available in ${DIR}. Resuming..."
+    python train.py \
+    --root ${DATA} \
+    --seed ${SEED} \
+    --trainer ${TRAINER} \
+    --dataset-config-file configs/datasets/${DATASET}.yaml \
+    --config-file configs/trainers/${TRAINER}/${CFG}.yaml \
+    --output-dir ${DIR} \
+    DATASET.NUM_SHOTS ${SHOTS} \
+    DATASET.SUBSAMPLE_CLASSES base
+else
+    echo "Run this job and save the output to ${DIR}"
+    python train.py \
+    --root ${DATA} \
+    --seed ${SEED} \
+    --trainer ${TRAINER} \
+    --dataset-config-file configs/datasets/${DATASET}.yaml \
+    --config-file configs/trainers/${TRAINER}/${CFG}.yaml \
+    --output-dir ${DIR} \
+    DATASET.NUM_SHOTS ${SHOTS} \
+    DATASET.SUBSAMPLE_CLASSES base
+fi

scripts/promptsrc/few_shot.sh

@@ -0,0 +1,27 @@
+#!/bin/bash
+
+# custom config
+DATA="/path/to/dataset/folder"
+TRAINER=PromptSRC
+
+DATASET=$1
+CFG=vit_b16_c2_ep50_batch4_4+4ctx_few_shot
+SHOTS=$2
+
+for SEED in 1 2 3
+do
+    DIR=output/${DATASET}/${TRAINER}/${CFG}_${SHOTS}shots/seed${SEED}
+    if [ -d "$DIR" ]; then
+        echo " The results exist at ${DIR}"
+    else
+        echo "Run this job and save the output to ${DIR}"
+        python train.py \
+        --root ${DATA} \
+        --seed ${SEED} \
+        --trainer ${TRAINER} \
+        --dataset-config-file configs/datasets/${DATASET}.yaml \
+        --config-file configs/trainers/${TRAINER}/${CFG}.yaml \
+        --output-dir ${DIR} \
+        DATASET.NUM_SHOTS ${SHOTS}
+    fi
+done

scripts/promptsrc/reproduce_base2novel_setting.sh

@@ -0,0 +1,54 @@
+#!/bin/bash
+
+# custom config
+DATA="/path/to/dataset/folder"
+TRAINER=PromptSRC
+
+DATASET=$1
+SEED=$2
+WEIGHTSPATH=$3
+
+CFG=vit_b16_c2_ep20_batch4_4+4ctx
+SHOTS=16
+LOADEP=20
+SUB_base=base
+SUB_novel=new
+
+COMMON_DIR=${DATASET}/shots_${SHOTS}/${TRAINER}/${CFG}/seed${SEED}
+MODEL_DIR=${WEIGHTSPATH}/base/seed${SEED}
+DIR_base=output/base2new/test_${SUB_base}/${COMMON_DIR}
+DIR_novel=output/base2new/test_${SUB_novel}/${COMMON_DIR}
+if [ -d "$DIR" ]; then
+    echo "Results are already available in ${DIR}. Skipping..."
+else
+    echo "Evaluating model"
+    echo "Runing the first phase job and save the output to ${DIR}"
+    # Evaluate on base classes
+    python train.py \
+    --root ${DATA} \
+    --seed ${SEED} \
+    --trainer ${TRAINER} \
+    --dataset-config-file configs/datasets/${DATASET}.yaml \
+    --config-file configs/trainers/${TRAINER}/${CFG}.yaml \
+    --output-dir ${DIR_base} \
+    --model-dir ${MODEL_DIR} \
+    --load-epoch ${LOADEP} \
+    --eval-only \
+    DATASET.NUM_SHOTS ${SHOTS} \
+    DATASET.SUBSAMPLE_CLASSES ${SUB_base}
+
+    # Evaluate on novel classes
+    python train.py \
+    --root ${DATA} \
+    --seed ${SEED} \
+    --trainer ${TRAINER} \
+    --dataset-config-file configs/datasets/${DATASET}.yaml \
+    --config-file configs/trainers/${TRAINER}/${CFG}.yaml \
+    --output-dir ${DIR_novel} \
+    --model-dir ${MODEL_DIR} \
+    --load-epoch ${LOADEP} \
+    --eval-only \
+    DATASET.NUM_SHOTS ${SHOTS} \
+    DATASET.SUBSAMPLE_CLASSES ${SUB_novel}
+
+fi

scripts/promptsrc/reproduce_few_shot.sh

@@ -0,0 +1,34 @@
+#!/bin/bash
+
+# custom config
+DATA="/path/to/dataset/folder"
+TRAINER=PromptSRC
+
+DATASET=$1
+SHOTS=$2
+WEIGHTSPATH=$3
+
+CFG=vit_b16_c2_ep50_batch4_4+4ctx_few_shot
+LOADEP=50
+
+for SEED in 1 2 3
+do
+    MODEL_DIR=${WEIGHTSPATH}/${SHOTS}shot/seed${SEED}
+    DIR=output/few_shot/${DATASET}/${TRAINER}/${CFG}_${SHOTS}shots/seed${SEED}
+    if [ -d "$DIR" ]; then
+        echo " The results exist at ${DIR}"
+    else
+        echo "Run this job and save the output to ${DIR}"
+        python train.py \
+        --root ${DATA} \
+        --seed ${SEED} \
+        --trainer ${TRAINER} \
+        --dataset-config-file configs/datasets/${DATASET}.yaml \
+        --config-file configs/trainers/${TRAINER}/${CFG}.yaml \
+        --output-dir ${DIR} \
+        --model-dir ${MODEL_DIR} \
+        --load-epoch ${LOADEP} \
+        --eval-only \
+        DATASET.NUM_SHOTS ${SHOTS}
+    fi
+done

scripts/promptsrc/reproduce_xd.sh

@@ -0,0 +1,36 @@
+#!/bin/bash
+
+# custom config
+DATA="/path/to/dataset/folder"
+TRAINER=PromptSRC
+
+DATASET=$1
+SEED=$2
+WEIGHTSPATH=$3
+
+CFG=vit_b16_c2_ep20_batch4_4+4ctx_cross_datasets
+SHOTS=16
+LOADEP=20
+
+MODEL_DIR=${WEIGHTSPATH}/seed${SEED}
+
+DIR=output/evaluation/${TRAINER}/${CFG}_${SHOTS}shots/${DATASET}/seed${SEED}
+if [ -d "$DIR" ]; then
+    echo "Results are already available in ${DIR}. Skipping..."
+else
+    echo "Evaluating model"
+    echo "Runing the first phase job and save the output to ${DIR}"
+    # Evaluate on evaluation datasets
+    python train.py \
+    --root ${DATA} \
+    --seed ${SEED} \
+    --trainer ${TRAINER} \
+    --dataset-config-file configs/datasets/${DATASET}.yaml \
+    --config-file configs/trainers/${TRAINER}/${CFG}.yaml \
+    --output-dir ${DIR} \
+    --model-dir ${MODEL_DIR} \
+    --load-epoch ${LOADEP} \
+    --eval-only \
+    DATASET.NUM_SHOTS ${SHOTS} \
+
+fi

scripts/promptsrc/xd_test.sh

@@ -0,0 +1,31 @@
+#!/bin/bash
+
+
+# custom config
+DATA="/path/to/dataset/folder"
+TRAINER=PromptSRC
+
+DATASET=$1
+SEED=$2
+
+CFG=vit_b16_c2_ep5_batch4_4+4ctx_cross_datasets
+SHOTS=16
+
+
+DIR=output/evaluation/${TRAINER}/${CFG}_${SHOTS}shots/${DATASET}/seed${SEED}
+if [ -d "$DIR" ]; then
+    echo "Results are available in ${DIR}. Skip this job"
+else
+    echo "Run this job and save the output to ${DIR}"
+
+    python train.py \
+    --root ${DATA} \
+    --seed ${SEED} \
+    --trainer ${TRAINER} \
+    --dataset-config-file configs/datasets/${DATASET}.yaml \
+    --config-file configs/trainers/${TRAINER}/${CFG}.yaml \
+    --output-dir ${DIR} \
+    --model-dir output/imagenet/${TRAINER}/${CFG}_${SHOTS}shots/seed${SEED} \
+    --load-epoch 20 \
+    --eval-only
+fi

scripts/promptsrc/xd_train.sh

@@ -0,0 +1,29 @@
+#!/bin/bash
+
+
+# custom config
+DATA="/path/to/dataset/folder"
+TRAINER=PromptSRC
+
+DATASET=$1
+SEED=$2
+
+CFG=vit_b16_c2_ep5_batch4_4+4ctx_cross_datasets
+SHOTS=16
+
+
+DIR=output/${DATASET}/${TRAINER}/${CFG}_${SHOTS}shots/seed${SEED}
+if [ -d "$DIR" ]; then
+    echo "Results are available in ${DIR}."
+else
+    echo "Run this job and save the output to ${DIR}"
+
+    python train.py \
+    --root ${DATA} \
+    --seed ${SEED} \
+    --trainer ${TRAINER} \
+    --dataset-config-file configs/datasets/${DATASET}.yaml \
+    --config-file configs/trainers/${TRAINER}/${CFG}.yaml \
+    --output-dir ${DIR} \
+    DATASET.NUM_SHOTS ${SHOTS}
+fi