resources/rr.sh at main · Li-Yongwen/resources · GitHub

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ulimit -n 65535
set -x

# avoid delayed console log, may impact performance
export PYTHONUNBUFFERED=1

export CUDA_DEVICE_MAX_CONNECTIONS=1 # For megatron communication/computation overlapping
export RAY_DEDUP_LOGS=0
export HYDRA_FULL_ERROR=1
export RAY_DEBUG=1
export VLLM_ASCEND_ENABLE_NZ=0
# export VLLM_USE_V1=1


MODEL_PATH=
CKPTS_DIR=
TRAIN_FILE=
TEST_FILE=

offload=True
train_tp=2
train_pp=1
gen_tp=2

python3 -m verl.trainer.main_ppo --config-path=config \
    --config-name='fault_recover_ppo_megatron_trainer.yaml'\
    algorithm.adv_estimator=grpo \
    data.train_files="${TRAIN_FILE}" \
    data.val_files="${TEST_FILE}" \
    data.train_batch_size=8 \
    data.max_prompt_length=2048 \
    data.max_response_length=2048 \
    data.filter_overlong_prompts=True \
    data.truncation='error' \
    actor_rollout_ref.model.path=${MODEL_PATH} \
    actor_rollout_ref.actor.checkpoint.async_save=False \
    actor_rollout_ref.actor.optim.lr=1e-6 \
    actor_rollout_ref.model.use_remove_padding=True \
    actor_rollout_ref.actor.ppo_mini_batch_size=8 \
    actor_rollout_ref.actor.ppo_micro_batch_size_per_gpu=2 \
    actor_rollout_ref.actor.megatron.param_offload=${offload} \
    actor_rollout_ref.actor.megatron.optimizer_offload=${offload} \
    actor_rollout_ref.actor.megatron.grad_offload=${offload} \
    actor_rollout_ref.actor.megatron.pipeline_model_parallel_size=${train_pp} \
    actor_rollout_ref.actor.megatron.tensor_model_parallel_size=${train_tp} \
    actor_rollout_ref.actor.megatron.use_mbridge=True \
    actor_rollout_ref.actor.megatron.expert_model_parallel_size=8 \
    actor_rollout_ref.actor.megatron.expert_tensor_parallel_size=1 \
    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.actor.use_torch_compile=False \
    actor_rollout_ref.rollout.log_prob_micro_batch_size_per_gpu=2 \
    actor_rollout_ref.rollout.tensor_model_parallel_size=${gen_tp} \
    actor_rollout_ref.rollout.name=vllm \
    actor_rollout_ref.rollout.gpu_memory_utilization=0.6 \
    actor_rollout_ref.rollout.n=4 \
    actor_rollout_ref.rollout.agent.default_agent_loop=fault_recover_single_turn_agent \
    actor_rollout_ref.ref.use_torch_compile=False \
    actor_rollout_ref.ref.log_prob_micro_batch_size_per_gpu=2 \
    actor_rollout_ref.ref.megatron.pipeline_model_parallel_size=${train_pp} \
    actor_rollout_ref.ref.megatron.tensor_model_parallel_size=${train_tp} \
    actor_rollout_ref.ref.megatron.expert_model_parallel_size=8 \
    actor_rollout_ref.ref.megatron.expert_tensor_parallel_size=1 \
    actor_rollout_ref.ref.megatron.param_offload=${offload} \
    ++actor_rollout_ref.ref.megatron.override_transformer_config.use_flash_attn=True \
    +actor_rollout_ref.actor.megatron.override_transformer_config.use_flash_attn=True \
    +actor_rollout_ref.actor.megatron.override_transformer_config.apply_rope_fusion=True \
    +actor_rollout_ref.actor.megatron.override_transformer_config.gradient_accumulation_fusion=True \
    +actor_rollout_ref.actor.megatron.override_transformer_config.use_fused_ring_attention_update=True \
    +actor_rollout_ref.actor.megatron.override_transformer_config.use_distributed_optimizer=True \
    algorithm.use_kl_in_reward=False \
    trainer.critic_warmup=0 \
    trainer.logger='["console"]' \
    trainer.project_name=${project_name} \
    trainer.experiment_name=${exp_name} \
    trainer.n_gpus_per_node=8 \
    trainer.nnodes=1 \
    trainer.default_local_dir=${CKPTS_DIR} \
    trainer.resume_mode=auto \
    trainer.val_before_train=False \
    trainer.save_freq=-1 \
    trainer.test_freq=-1 \
    trainer.total_epochs=1 \
    trainer.total_training_step=6 \
    actor_rollout_ref.actor.router_replay.mode=R2