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#!/bin/bash
# Visual-OPSD (offline) main training.
# CE + VT-sensitivity-weighted KL from cached teacher logprobs.
# Expected: ~6 hours on 4× H800.
SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
ROOT_DIR="$(cd "${SCRIPT_DIR}/../.." && pwd)"
cd "${ROOT_DIR}"
export PYTHONPATH="${ROOT_DIR}:${PYTHONPATH:-}"
export PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True
source .venv/bin/activate
MODEL_PATH=${1:-models/ThinkMorph-7B}
TEACHER_CACHE=${2:-traces/visual_opsd_teacher_cache}
KD_WEIGHT=${3:-0.5}
KD_TEMP=${4:-2.0}
TOTAL_STEPS=${5:-8000}
OUTPUT_NAME=${6:-visual-opsd-offline-lam${KD_WEIGHT}-tau${KD_TEMP}}
MASTER_ADDR=${ARNOLD_WORKER_0_HOST}
MASTER_PORT=(${ARNOLD_WORKER_0_PORT//,/ })
NPROC_PER_NODE=${ARNOLD_WORKER_GPU}
NNODES=${ARNOLD_WORKER_NUM}
NODE_RANK=${ARNOLD_ID}
echo "=== Visual-OPSD (offline) Training ==="
echo "Model: ${MODEL_PATH}"
echo "Teacher cache: ${TEACHER_CACHE}"
echo "λ=${KD_WEIGHT}, τ=${KD_TEMP}, steps=${TOTAL_STEPS}"
torchrun \
--nnodes=${NNODES} \
--node_rank=${NODE_RANK} \
--nproc_per_node=${NPROC_PER_NODE} \
--master_addr=${MASTER_ADDR} \
--master_port=${MASTER_PORT} \
scripts/visual_opsd/train_visual_opsd_offline.py \
--mode offline \
--model_path ${MODEL_PATH} \
--dataset_config_file ./data/configs/visual_opsd_offline.yaml \
--teacher_cache_dir ${TEACHER_CACHE} \
--finetune_from_hf True \
--resume_model_only True \
--finetune_from_ema False \
--resume_from ${MODEL_PATH} \
--results_dir results/${OUTPUT_NAME} \
--checkpoint_dir results/${OUTPUT_NAME}/checkpoints \
--lr 1e-5 \
--num_workers 4 \
--prefetch_factor 4 \
--max_num_tokens 10240 \
--gradient_accumulation_steps 1 \
--cpu_offload False \
--visual_gen False \
--total_steps ${TOTAL_STEPS} \
--save_every 1000 \
--num_shard ${NPROC_PER_NODE} \
--kd_weight ${KD_WEIGHT} \
--kd_temperature ${KD_TEMP} \
--kd_use_vt_weights True \
--wandb_project Visual-OPSD \
--wandb_name ${OUTPUT_NAME} \
--wandb_runid 2

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