#!/bin/bash
# Resume Integrated_EVA-B_DINOv2-B_560 实验

data_root=/opt/tiger/xiaomoguhzz/standard_coco
pretrain_ckpt=/opt/tiger/xiaomoguhzz/EVA02_CLIP_B_psz16_s8B.pt
exp_name=Integrated_EVA-B_DINOv2-B_560
resume_ckpt=logs/${exp_name}/checkpoints/epoch_5.pt

cd /mnt/bn/strategy-mllm-train/user/wangjunjie/code/xiaomoguhzz/DeCLIP_private

echo "Resuming: $exp_name"
echo "Checkpoint: $resume_ckpt"

CUDA_VISIBLE_DEVICES=0,1,2,3,4,5,6,7 torchrun --nproc_per_node 8 --master_port 12349 \
    -m training.main \
    --batch-size=2 \
    --lr=1e-5 \
    --wd=0.1 \
    --epochs=6 \
    --workers=4 \
    --model EVA02-CLIP-B-16 \
    --pretrained eva \
    --warmup 1000 \
    --zeroshot-frequency 6 \
    --dataset-type grid_distill \
    --test-type coco_panoptic \
    --train-data ${data_root}/annotations/instances_train2017.json \
    --val-data ${data_root}/annotations/panoptic_val2017.json \
    --embed-path metadata/coco_panoptic_clip_hand_craft_EVACLIP_ViTB16.npy \
    --train-image-root ${data_root}/train2017 \
    --val-image-root ${data_root}/val2017 \
    --cache-dir ${pretrain_ckpt} \
    --log-every-n-steps 100 \
    --lock-image \
    --save-frequency 1 \
    --lock-image-unlocked-groups 12 \
    --name ${exp_name} \
    --downsample-factor 16 \
    --det-image-size 560 \
    --val-segm-root ${data_root}/annotations/panoptic_val2017 \
    --alpha 0.7 \
    --mode vanilla \
    --use_vfm dinov2-B \
    --loss_context_weight 1.0 \
    --loss_content_weight 1.0 \
    --loss_region_weight 0.05 \
    --repa_layer_idx -1 \
    --version integrated \
    --resume ${resume_ckpt}