#!/bin/bash

CHECKPOINT=Marlo-Z/SegLLM/mr_refcoco_checkpoint
SEG_CONFIG_FILE=refcoco_val.yaml
CONV_DIR=refcoco_single_round_val
RESULTS_PATH=./val_results/templates_refcoco_eval_results.txt

# ------------------------------ Templates ---------------------------------

DATASETS=("refcoco" "refcoco+" "refcocog")
TEMPLATES=("lisa" "sesame")
for dataset in "${DATASETS[@]}"
do
    for template in "${TEMPLATES[@]}"
    do   
        VAL_DATA=${dataset}_val_${template}_templates.json
        deepspeed \
            --include "localhost:${LOCAL_HOST}" \
            --master_port 12343 \
            llava/train/train_mem.py \
            --deepspeed ./scripts/deepspeed_configs/zero2.json \
            --model_name_or_path liuhaotian/llava-v1.5-7b \
            --load $CHECKPOINT \
            --image_folder ./images_folder \
            --annotation_folder ./annotations_folder \
            --conversation_folder ./conversations_folder/${CONV_DIR} \
            --segmentation_config ./scripts/annotation_configs/val/${SEG_CONFIG_FILE} \
            --val_dataset $VAL_DATA \
            --val_results_save_file $RESULTS_PATH \
            --lora_enable False \
            --split_loading False \
            --version plain \
            --mm_use_seg True \
            --segmentator hipie \
            --vision_tower openai/clip-vit-large-patch14 \
            --mm_projector_type mlp2x_gelu \
            --tune_mm_mlp_adapter False \
            --mm_vision_select_layer -2 \
            --mm_use_im_start_end False \
            --mm_vision_select_feature patch \
            --mm_use_im_patch_token False \
            --bf16 True \
            --fp16 False \
            --tf32 False \
            --mm_use_gen True \
            --num_train_epochs 2 \
            --per_device_train_batch_size 4 \
            --gradient_accumulation_steps 1 \
            --evaluation_strategy "steps" \
            --save_strategy "steps" \
            --save_steps 500 \
            --save_total_limit 2 \
            --learning_rate 2e-5 \
            --weight_decay 0. \
            --eval_steps 1000 \
            --warmup_ratio 0.03 \
            --lr_scheduler_type "cosine" \
            --logging_steps 1 \
            --model_max_length 2048 \
            --gradient_checkpointing True \
            --dataloader_num_workers 4 \
            --lazy_preprocess True \
            --report_to wandb ${@:1} \
            --output_text \
            --do_eval \
            --eval_only \
            --output_dir ./val_output \
            --eval_use_gt_mask_encode True \
            --per_device_eval_batch_size 1
    done
done