set -x
ENGINE=${1:-vllm}
EXP_NAME=captioner_qwen3b_virl39k_llm_ds_7b_2
export VLLM_ATTENTION_BACKEND=XFORMERS
export TENSORBOARD_DIR=/cache/exps/tensorboard_log/${EXP_NAME}

python3 -m verl.trainer.main_ppo_caption \
    algorithm.adv_estimator=grpo \
    data.train_files=/cache/data/huggingface_datasets/virl39k_no_deepscaler_caption.parquet \
    data.train_batch_size=256 \
    data.max_prompt_length=8192 \
    data.max_response_length=8192 \
    data.filter_overlong_prompts=True \
    data.truncation='error' \
    data.image_key=images \
    actor_rollout_ref.model.path=/cache/data/huggingface_models/Qwen2.5-VL-3B-Instruct \
    actor_rollout_ref.actor.optim.lr=1e-6 \
    actor_rollout_ref.model.use_remove_padding=True \
    actor_rollout_ref.actor.ppo_mini_batch_size=128 \
    actor_rollout_ref.actor.ppo_micro_batch_size_per_gpu=8 \
    actor_rollout_ref.actor.use_kl_loss=True \
    actor_rollout_ref.actor.kl_loss_coef=0.001 \
    actor_rollout_ref.actor.kl_loss_type=low_var_kl \
    actor_rollout_ref.actor.entropy_coeff=0 \
    actor_rollout_ref.model.enable_gradient_checkpointing=True \
    actor_rollout_ref.actor.fsdp_config.param_offload=False \
    actor_rollout_ref.actor.fsdp_config.optimizer_offload=False \
    actor_rollout_ref.rollout.log_prob_micro_batch_size_per_gpu=32 \
    actor_rollout_ref.rollout.tensor_model_parallel_size=1 \
    actor_rollout_ref.rollout.name=$ENGINE \
    actor_rollout_ref.rollout.gpu_memory_utilization=0.5 \
    actor_rollout_ref.rollout.enable_chunked_prefill=False \
    actor_rollout_ref.rollout.enforce_eager=False \
    actor_rollout_ref.rollout.free_cache_engine=False \
    actor_rollout_ref.rollout.n=4 \
    actor_rollout_ref.rollout.limit_images=8 \
    actor_rollout_ref.ref.log_prob_micro_batch_size_per_gpu=32 \
    actor_rollout_ref.ref.fsdp_config.param_offload=True \
    reason_rollout.model.path=/cache/data/huggingface_models/DeepSeek-R1-Distill-Qwen-7B \
    algorithm.use_kl_in_reward=False \
    trainer.critic_warmup=0 \
    trainer.logger=['console','tensorboard'] \
    trainer.project_name='captioner' \
    trainer.experiment_name=${EXP_NAME} \
    trainer.n_gpus_per_node=8 \
    trainer.nnodes=1 \
    trainer.save_freq=50 \
    trainer.total_epochs=20 $@