xda xdo script

2026-02-06 17:07:59 +08:00
parent 91e873c365
commit c94030588e
10 changed files with 120 additions and 212 deletions
--- a/configs/trainers/PromptSRC/vit_b16_c2_ep20_batch4_4+4ctx_cross_datasets.yaml
+++ b/configs/trainers/PromptSRC/vit_b16_c2_ep20_batch4_4+4ctx_cross_datasets.yaml
@@ -23,6 +23,7 @@ OPTIM:
  WARMUP_CONS_LR: 1e-5

 TRAIN:
+  CHECKPOINT_FREQ: 5
  PRINT_FREQ: 20

 MODEL:
--- a/configs/trainers/PromptSRC/vit_b16_c2_ep5_batch4_4+4ctx_cross_datasets.yaml
+++ b/configs/trainers/PromptSRC/vit_b16_c2_ep5_batch4_4+4ctx_cross_datasets.yaml
@@ -16,7 +16,7 @@ INPUT:
 OPTIM:
  NAME: "sgd"
  LR: 0.0025
-  MAX_EPOCH: 50
+  MAX_EPOCH: 5
  LR_SCHEDULER: "cosine"
  WARMUP_EPOCH: 1
  WARMUP_TYPE: "constant"
@@ -35,13 +35,9 @@ TRAINER:
    N_CTX_TEXT: 4
    CTX_INIT: "a photo of a"
    PREC: "fp16"
-    PROMPT_DEPTH_VISION: 9
-    PROMPT_DEPTH_TEXT: 9
+    PROMPT_DEPTH_VISION: 3
+    PROMPT_DEPTH_TEXT: 3
    TEXT_LOSS_WEIGHT: 25
    IMAGE_LOSS_WEIGHT: 10
-# Use the below configuration for: ImageNet, Caltech101, OxfordPets, Food101, UCF101 and  SUN397
-    GPA_MEAN: 30
-    GPA_STD: 30
-# Use the below configuration for: StanfordCars, Flowers102, FGVCAircraft, DTD and EuroSAT
-#    GPA_MEAN: 45
-#    GPA_STD: 5
+    GPA_MEAN: 6
+    GPA_STD: 10
--- a/scripts/promptsrc/few_shot.sh
+++ b/scripts/promptsrc/few_shot.sh
@@ -1,27 +0,0 @@
-#!/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
--- a/scripts/promptsrc/reproduce_base2novel_setting.sh
+++ b/scripts/promptsrc/reproduce_base2novel_setting.sh
@@ -1,54 +0,0 @@
-#!/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
--- a/scripts/promptsrc/reproduce_few_shot.sh
+++ b/scripts/promptsrc/reproduce_few_shot.sh
@@ -1,34 +0,0 @@
-#!/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
--- a/scripts/promptsrc/reproduce_xd.sh
+++ b/scripts/promptsrc/reproduce_xd.sh
@@ -1,36 +0,0 @@
-#!/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
--- a/scripts/promptsrc/xd_test.sh
+++ b/scripts/promptsrc/xd_test.sh
@@ -1,31 +0,0 @@
-#!/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
--- a/scripts/promptsrc/xd_train.sh
+++ b/scripts/promptsrc/xd_train.sh
@@ -1,29 +1,30 @@
 #!/bin/bash


-# custom config
-DATA="/path/to/dataset/folder"
+DATA=" ~/Datasets/CoOp"
 TRAINER=PromptSRC
-
-DATASET=$1
-SEED=$2
-
-CFG=vit_b16_c2_ep5_batch4_4+4ctx_cross_datasets
+SRC_DATASETS=imagenet
 SHOTS=16
+CFG=vit_b16_c2_ep5_batch4_4+4ctx_cross_datasets


-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 ${DIR}"
+for SEED in 1 2 3
+do
+    DIR=output_xd/base2new/train_base/${SRC_DATASETS}/shots_${SHOTS}/${TRAINER}/${CFG}/seed${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}"
+
+        CUDA_VISIBLE_DEVICES=0 python train.py \
+        --root ${DATA} \
+        --seed ${SEED} \
+        --trainer ${TRAINER} \
+        --dataset-config-file configs/datasets/${SRC_DATASETS}.yaml \
+        --config-file configs/trainers/${TRAINER}/${CFG}.yaml \
+        --output-dir ${DIR} \
+	DATASET.NUM_SHOTS ${SHOTS}
+    fi
+done

-    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 ${SHOTS}
-fi
--- a/scripts/promptsrc/xda_test.sh
+++ b/scripts/promptsrc/xda_test.sh
@@ -0,0 +1,46 @@
+#!/bin/bash
+
+
+# custom config
+DATA=" ~/Datasets/CoOp"
+TRAINER=PromptSRC
+
+
+SRC_DATASETS=imagenet 
+SHOTS=16
+CFG=vit_b16_c2_ep20_batch4_4+4ctx_cross_datasets
+LOADEP=20
+
+
+DATASETS=(dtd eurosat fgvc_aircraft food101 oxford_flowers oxford_pets stanford_cars ucf101 caltech101 sun397)
+SEEDS=(1 2 3)
+
+
+for DATASET in "${DATASETS[@]}"
+do
+    for SEED in "${SEEDS[@]}"
+    do
+        MODEL_DIR=output_xd/base2new/train_base/${SRC_DATASETS}/shots_${SHOTS}/${TRAINER}/${CFG}/seed${SEED}
+        
+        DIR=output_xd/base2new/test_new/${DATASET}/shots_${SHOTS}/${TRAINER}/${CFG}/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}"
+            echo "Loading model from ${MODEL_DIR}"
+
+            CUDA_VISIBLE_DEVICES=0 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 ${LOADEP} \
+            --eval-only
+        fi
+    done
+done
+
--- a/scripts/promptsrc/xdo_test.sh
+++ b/scripts/promptsrc/xdo_test.sh
@@ -0,0 +1,46 @@
+#!/bin/bash
+
+
+# custom config
+DATA=" ~/Datasets/CoOp"
+TRAINER=PromptSRC
+
+
+SRC_DATASETS=imagenet 
+SHOTS=16
+CFG=vit_b16_c2_ep20_batch4_4+4ctx_cross_datasets
+LOADEP=20
+
+
+DATASETS=(imagenetv2 imagenet_sketch imagenet_a imagenet_r)
+SEEDS=(1 2 3)
+
+
+for DATASET in "${DATASETS[@]}"
+do
+    for SEED in "${SEEDS[@]}"
+    do
+        MODEL_DIR=output_xd/base2new/train_base/${SRC_DATASETS}/shots_${SHOTS}/${TRAINER}/${CFG}/seed${SEED}
+        
+        DIR=output_xd/base2new/test_new/${DATASET}/shots_${SHOTS}/${TRAINER}/${CFG}/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}"
+            echo "Loading model from ${MODEL_DIR}"
+
+            CUDA_VISIBLE_DEVICES=0 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
+        fi
+    done
+done
+