[model] feat: add NPU GRPO training scripts for Qwen2.5-32B/Qwen3-30B (Megaton/vLLM backends) #4984
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| Original file line number | Diff line number | Diff line change | ||||
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| @@ -0,0 +1,185 @@ | ||||||
| #!/bin/bash | ||||||
| set -xeuo pipefail | ||||||
| mkdir -p logs | ||||||
|
|
||||||
| # Project Configuration | ||||||
| project_name='GRPO-Qwen2.5-32B-BASE-MATH' | ||||||
| exp_name='GRPO-Qwen2.5-32B-BASE-Megatron-vLLM' | ||||||
|
|
||||||
| # Node Info | ||||||
| NNODES=${NNODES:-1} | ||||||
| NPUS_PER_NODE=${NPUS_PER_NODE:-16} | ||||||
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|
||||||
| # Model Weights Paths | ||||||
| MODEL_PATH=Qwen/Qwen2.5-32B | ||||||
| MCORE_MODEL_PATH=Qwen/Qwen2.5-32B-dist | ||||||
| RAY_DATA_HOME=${RAY_DATA_HOME:-"${HOME}/verl"} | ||||||
| CKPTS_DIR=${CKPTS_DIR:-"${RAY_DATA_HOME}/ckpts/${project_name}/${exp_name}"} | ||||||
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||||||
| # File System Paths | ||||||
| TRAIN_FILE=$RAY_DATA_HOME/dataset/gsm8k/train.parquet | ||||||
| TEST_FILE=$RAY_DATA_HOME/dataset/gsm8k/test.parquet | ||||||
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|
||||||
| # Data Configuration | ||||||
| max_prompt_length=$((1024 * 1)) | ||||||
| max_response_length=$((1024 * 1)) | ||||||
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|
||||||
| # Training Batch Configuration | ||||||
| train_prompt_bsz=128 | ||||||
| train_prompt_mini_bsz=32 | ||||||
| n_resp_per_prompt=16 | ||||||
|
|
||||||
| # Algorithm Configuration | ||||||
| adv_estimator=grpo | ||||||
| use_kl_in_reward=False | ||||||
| kl_coef=0.0 | ||||||
| use_kl_loss=True | ||||||
| kl_loss_coef=0.001 | ||||||
|
|
||||||
| # Performance and Memory Management Configuration | ||||||
| all_offload=True | ||||||
| use_dynamic_bsz=True | ||||||
| actor_ppo_max_token_len=$(((max_prompt_length + max_response_length) * 2)) | ||||||
| infer_ppo_max_token_len=$(((max_prompt_length + max_response_length) * 8)) | ||||||
| optimizer_offload_fraction=1 | ||||||
|
|
||||||
| # Megatron Configuration | ||||||
| train_tp=4 | ||||||
| train_ep=1 | ||||||
| train_etp=1 | ||||||
| train_pp=4 | ||||||
| train_cp=1 | ||||||
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|
||||||
| # vLLM Configuration | ||||||
| gen_tp=2 | ||||||
| gen_dp=1 | ||||||
| gen_ep=1 | ||||||
| gpu_memory_utilization=0.8 | ||||||
| max_model_len=$((max_prompt_length + max_response_length)) | ||||||
| max_num_batched_tokens=$(((max_prompt_length + max_response_length) * 1)) | ||||||
|
|
||||||
| # Data Configuration | ||||||
| DATA_CONFIG=( | ||||||
| data.train_files="${TRAIN_FILE}" | ||||||
| data.val_files="${TEST_FILE}" | ||||||
| data.prompt_key=prompt | ||||||
| data.train_batch_size=${train_prompt_bsz} | ||||||
| data.max_prompt_length=${max_prompt_length} | ||||||
| data.max_response_length=${max_response_length} | ||||||
| data.filter_overlong_prompts=False | ||||||
| data.truncation='left' | ||||||
| ) | ||||||
|
|
||||||
| # Model Configuration | ||||||
| MODEL_CONFIG=( | ||||||
| actor_rollout_ref.model.path="${MODEL_PATH}" | ||||||
| actor_rollout_ref.model.use_remove_padding=True | ||||||
| ) | ||||||
|
|
||||||
| # Algorithm Configuration | ||||||
| ALGORITHM_CONFIG=( | ||||||
| algorithm.adv_estimator=${adv_estimator} | ||||||
| algorithm.use_kl_in_reward=${use_kl_in_reward} | ||||||
| algorithm.kl_ctrl.kl_coef=${kl_coef} | ||||||
| ) | ||||||
|
|
||||||
| # Actor Model Configuration | ||||||
| ACTOR_CONFIG=( | ||||||
| actor_rollout_ref.actor.use_torch_compile=False | ||||||
| actor_rollout_ref.actor.use_dynamic_bsz=${use_dynamic_bsz} | ||||||
| actor_rollout_ref.actor.use_kl_loss=${use_kl_loss} | ||||||
| actor_rollout_ref.actor.kl_loss_type=low_var_kl | ||||||
| actor_rollout_ref.actor.kl_loss_coef=${kl_loss_coef} | ||||||
| actor_rollout_ref.actor.entropy_coeff=0 | ||||||
| actor_rollout_ref.actor.ppo_epochs=1 | ||||||
| actor_rollout_ref.actor.ppo_micro_batch_size_per_gpu=1 | ||||||
| actor_rollout_ref.actor.ppo_max_token_len_per_gpu=${actor_ppo_max_token_len} | ||||||
| actor_rollout_ref.actor.ppo_mini_batch_size=${train_prompt_mini_bsz} | ||||||
| actor_rollout_ref.actor.kl_loss_type=low_var_kl | ||||||
| actor_rollout_ref.actor.optim.lr=1e-6 | ||||||
| +actor_rollout_ref.actor.optim.override_optimizer_config.optimizer_offload_fraction=${optimizer_offload_fraction} | ||||||
| +actor_rollout_ref.actor.optim.override_optimizer_config.use_precision_aware_optimizer=True | ||||||
| +actor_rollout_ref.actor.optim.override_optimizer_config.optimizer_cpu_offload=True | ||||||
| actor_rollout_ref.actor.megatron.tensor_model_parallel_size=${train_tp} | ||||||
| actor_rollout_ref.actor.megatron.pipeline_model_parallel_size=${train_pp} | ||||||
| actor_rollout_ref.actor.megatron.context_parallel_size=${train_cp} | ||||||
| actor_rollout_ref.actor.megatron.expert_model_parallel_size=${train_ep} | ||||||
| actor_rollout_ref.actor.megatron.expert_tensor_parallel_size=${train_etp} | ||||||
| actor_rollout_ref.actor.megatron.param_offload=${all_offload} | ||||||
| actor_rollout_ref.actor.megatron.optimizer_offload=${all_offload} | ||||||
| actor_rollout_ref.actor.megatron.grad_offload=${all_offload} | ||||||
| actor_rollout_ref.actor.megatron.dist_checkpointing_path=${MCORE_MODEL_PATH} | ||||||
| actor_rollout_ref.actor.megatron.use_dist_checkpointing=False | ||||||
| +actor_rollout_ref.actor.megatron.override_transformer_config.use_flash_attn=True | ||||||
|
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| ) | ||||||
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||||||
| # Reference Model Configuration | ||||||
| REF_CONFIG=( | ||||||
| actor_rollout_ref.ref.use_torch_compile=False | ||||||
| actor_rollout_ref.ref.log_prob_micro_batch_size_per_gpu=1 | ||||||
| actor_rollout_ref.ref.log_prob_use_dynamic_bsz=${use_dynamic_bsz} | ||||||
| actor_rollout_ref.ref.log_prob_max_token_len_per_gpu=${infer_ppo_max_token_len} | ||||||
| actor_rollout_ref.ref.megatron.tensor_model_parallel_size=${train_tp} | ||||||
| actor_rollout_ref.ref.megatron.pipeline_model_parallel_size=${train_pp} | ||||||
| actor_rollout_ref.ref.megatron.context_parallel_size=${train_cp} | ||||||
| actor_rollout_ref.ref.megatron.expert_model_parallel_size=${train_ep} | ||||||
| actor_rollout_ref.ref.megatron.expert_tensor_parallel_size=${train_etp} | ||||||
| actor_rollout_ref.ref.megatron.param_offload=${all_offload} | ||||||
| actor_rollout_ref.ref.megatron.dist_checkpointing_path=${MCORE_MODEL_PATH} | ||||||
| actor_rollout_ref.ref.megatron.use_dist_checkpointing=False | ||||||
| ) | ||||||
|
|
||||||
| # Rollout Configuration | ||||||
| ROLLOUT_CONFIG=( | ||||||
| actor_rollout_ref.rollout.name=vllm | ||||||
| actor_rollout_ref.rollout.n=${n_resp_per_prompt} | ||||||
| actor_rollout_ref.rollout.top_p=1.0 | ||||||
| actor_rollout_ref.rollout.top_k=-1 | ||||||
| actor_rollout_ref.rollout.temperature=1.0 | ||||||
| actor_rollout_ref.rollout.log_prob_micro_batch_size_per_gpu=1 | ||||||
| actor_rollout_ref.rollout.log_prob_use_dynamic_bsz=${use_dynamic_bsz} | ||||||
| actor_rollout_ref.rollout.log_prob_max_token_len_per_gpu=${infer_ppo_max_token_len} | ||||||
| actor_rollout_ref.rollout.gpu_memory_utilization=${gpu_memory_utilization} | ||||||
| actor_rollout_ref.rollout.max_num_batched_tokens=${max_num_batched_tokens} | ||||||
| actor_rollout_ref.rollout.max_model_len=${max_model_len} | ||||||
| actor_rollout_ref.rollout.tensor_model_parallel_size=${gen_tp} | ||||||
| actor_rollout_ref.rollout.data_parallel_size=${gen_dp} | ||||||
| actor_rollout_ref.rollout.expert_parallel_size=${gen_ep} | ||||||
| actor_rollout_ref.rollout.enable_chunked_prefill=True | ||||||
| actor_rollout_ref.rollout.enable_prefix_caching=True | ||||||
| actor_rollout_ref.rollout.enforce_eager=True | ||||||
| actor_rollout_ref.rollout.free_cache_engine=True | ||||||
| actor_rollout_ref.rollout.val_kwargs.n=1 | ||||||
| actor_rollout_ref.rollout.val_kwargs.do_sample=True | ||||||
| actor_rollout_ref.rollout.val_kwargs.top_p=1.0 | ||||||
| actor_rollout_ref.rollout.val_kwargs.top_k=-1 | ||||||
| actor_rollout_ref.rollout.val_kwargs.temperature=1.0 | ||||||
| ) | ||||||
|
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||||||
| # Trainer Configuration | ||||||
| TRAINER_CONFIG=( | ||||||
| trainer.logger='["console","tensorboard"]' | ||||||
| trainer.project_name="${project_name}" | ||||||
| trainer.experiment_name="${exp_name}" | ||||||
| trainer.nnodes="${NNODES}" | ||||||
| trainer.n_gpus_per_node="${NPUS_PER_NODE}" | ||||||
| trainer.device='npu' | ||||||
| trainer.total_epochs=15 | ||||||
| trainer.val_before_train=False | ||||||
| trainer.test_freq=-1 | ||||||
| trainer.save_freq=-1 | ||||||
| trainer.default_local_dir="${CKPTS_DIR}" | ||||||
| ) | ||||||
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||||||
| # Main GRPO Training Command | ||||||
| python3 -m verl.trainer.main_ppo \ | ||||||
| --config-path=config \ | ||||||
| --config-name='ppo_megatron_trainer.yaml' \ | ||||||
| "${DATA_CONFIG[@]}" \ | ||||||
| "${MODEL_CONFIG[@]}" \ | ||||||
| "${ACTOR_CONFIG[@]}" \ | ||||||
| "${REF_CONFIG[@]}" \ | ||||||
| "${ROLLOUT_CONFIG[@]}" \ | ||||||
| "${ALGORITHM_CONFIG[@]}" \ | ||||||
| "${TRAINER_CONFIG[@]}" \ | ||||||
| "$@" | tee logs/run_qwen2_5-32b_grpo_megatron_vllm_npu.log | ||||||
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| Original file line number | Diff line number | Diff line change | ||||||||||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| @@ -0,0 +1,188 @@ | ||||||||||||||||||
| #!/bin/bash | ||||||||||||||||||
| set -xeuo pipefail | ||||||||||||||||||
| mkdir -p logs | ||||||||||||||||||
|
|
||||||||||||||||||
| # Project Configuration | ||||||||||||||||||
| project_name='GRPO-Qwen3-30b-A3B-BASE-MATH' | ||||||||||||||||||
| exp_name='GRPO-Qwen3-30B-A3B-BASE-Megatron-vLLM' | ||||||||||||||||||
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||||||||||||||||||
| # Node Info | ||||||||||||||||||
| NNODES=${NNODES:-1} | ||||||||||||||||||
| NPUS_PER_NODE=${NPUS_PER_NODE:-16} | ||||||||||||||||||
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||||||||||||||||||
| # Model Weights Paths | ||||||||||||||||||
| MODEL_PATH=Qwen/Qwen3-30B-A3B-Base | ||||||||||||||||||
| MCORE_MODEL_PATH=Qwen/Qwen3-30B-A3B-Base-dist | ||||||||||||||||||
| RAY_DATA_HOME=${RAY_DATA_HOME:-"${HOME}/verl"} | ||||||||||||||||||
| CKPTS_DIR=${CKPTS_DIR:-"${RAY_DATA_HOME}/ckpts/${project_name}/${exp_name}"} | ||||||||||||||||||
|
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| # File System Paths | ||||||||||||||||||
| TRAIN_FILE=$RAY_DATA_HOME/dataset/gsm8k/train.parquet | ||||||||||||||||||
| TEST_FILE=$RAY_DATA_HOME/dataset/gsm8k/test.parquet | ||||||||||||||||||
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||||||||||||||||||
| # Data Configuration | ||||||||||||||||||
| max_prompt_length=$((1024 * 1)) | ||||||||||||||||||
| max_response_length=$((1024 * 1)) | ||||||||||||||||||
|
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||||||||||||||||||
| # Training Batch Configuration | ||||||||||||||||||
| train_prompt_bsz=128 | ||||||||||||||||||
| train_prompt_mini_bsz=32 | ||||||||||||||||||
| n_resp_per_prompt=16 | ||||||||||||||||||
|
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||||||||||||||||||
| # Algorithm Configuration | ||||||||||||||||||
| adv_estimator=grpo | ||||||||||||||||||
| use_kl_in_reward=False | ||||||||||||||||||
| kl_coef=0.0 | ||||||||||||||||||
| use_kl_loss=True | ||||||||||||||||||
| kl_loss_coef=0.001 | ||||||||||||||||||
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||||||||||||||||||
| # Performance and Memory Management Configuration | ||||||||||||||||||
| all_offload=True | ||||||||||||||||||
| use_dynamic_bsz=True | ||||||||||||||||||
| actor_ppo_max_token_len=$(((max_prompt_length + max_response_length) * 4)) | ||||||||||||||||||
| infer_ppo_max_token_len=$(((max_prompt_length + max_response_length) * 8)) | ||||||||||||||||||
| optimizer_offload_fraction=1 | ||||||||||||||||||
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||||||||||||||||||
| # Megatron Configuration | ||||||||||||||||||
| train_tp=2 | ||||||||||||||||||
| train_ep=8 | ||||||||||||||||||
| train_etp=1 | ||||||||||||||||||
| train_pp=2 | ||||||||||||||||||
| train_cp=1 | ||||||||||||||||||
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| # vLLM Configuration | ||||||||||||||||||
| gen_tp=2 | ||||||||||||||||||
| gen_dp=1 | ||||||||||||||||||
| gen_ep=1 | ||||||||||||||||||
| gpu_memory_utilization=0.8 | ||||||||||||||||||
| max_model_len=$((max_prompt_length + max_response_length)) | ||||||||||||||||||
| max_num_batched_tokens=$(((max_prompt_length + max_response_length) * 1)) | ||||||||||||||||||
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||||||||||||||||||
| # Data Configuration | ||||||||||||||||||
| DATA_CONFIG=( | ||||||||||||||||||
| data.train_files="${TRAIN_FILE}" | ||||||||||||||||||
| data.val_files="${TEST_FILE}" | ||||||||||||||||||
| data.prompt_key=prompt | ||||||||||||||||||
| data.train_batch_size=${train_prompt_bsz} | ||||||||||||||||||
| data.max_prompt_length=${max_prompt_length} | ||||||||||||||||||
| data.max_response_length=${max_response_length} | ||||||||||||||||||
| data.filter_overlong_prompts=False | ||||||||||||||||||
| data.truncation='left' | ||||||||||||||||||
| ) | ||||||||||||||||||
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||||||||||||||||||
| # Model Configuration | ||||||||||||||||||
| MODEL_CONFIG=( | ||||||||||||||||||
| actor_rollout_ref.model.path="${MODEL_PATH}" | ||||||||||||||||||
| actor_rollout_ref.model.use_remove_padding=True | ||||||||||||||||||
| ) | ||||||||||||||||||
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||||||||||||||||||
| # Algorithm Configuration | ||||||||||||||||||
| ALGORITHM_CONFIG=( | ||||||||||||||||||
| algorithm.adv_estimator=${adv_estimator} | ||||||||||||||||||
| algorithm.use_kl_in_reward=${use_kl_in_reward} | ||||||||||||||||||
| algorithm.kl_ctrl.kl_coef=${kl_coef} | ||||||||||||||||||
| ) | ||||||||||||||||||
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||||||||||||||||||
| # Actor Model Configuration | ||||||||||||||||||
| ACTOR_CONFIG=( | ||||||||||||||||||
| actor_rollout_ref.actor.use_torch_compile=False | ||||||||||||||||||
| actor_rollout_ref.actor.use_dynamic_bsz=${use_dynamic_bsz} | ||||||||||||||||||
| actor_rollout_ref.actor.use_kl_loss=${use_kl_loss} | ||||||||||||||||||
| actor_rollout_ref.actor.kl_loss_type=low_var_kl | ||||||||||||||||||
| actor_rollout_ref.actor.kl_loss_coef=${kl_loss_coef} | ||||||||||||||||||
| actor_rollout_ref.actor.entropy_coeff=0 | ||||||||||||||||||
| actor_rollout_ref.actor.ppo_epochs=1 | ||||||||||||||||||
| actor_rollout_ref.actor.ppo_micro_batch_size_per_gpu=1 | ||||||||||||||||||
| actor_rollout_ref.actor.ppo_max_token_len_per_gpu=${actor_ppo_max_token_len} | ||||||||||||||||||
| actor_rollout_ref.actor.ppo_mini_batch_size=${train_prompt_mini_bsz} | ||||||||||||||||||
| actor_rollout_ref.actor.kl_loss_type=low_var_kl | ||||||||||||||||||
| actor_rollout_ref.actor.optim.lr=1e-6 | ||||||||||||||||||
| +actor_rollout_ref.actor.optim.override_optimizer_config.optimizer_offload_fraction=${optimizer_offload_fraction} | ||||||||||||||||||
| +actor_rollout_ref.actor.optim.override_optimizer_config.use_precision_aware_optimizer=True | ||||||||||||||||||
| +actor_rollout_ref.actor.optim.override_optimizer_config.optimizer_cpu_offload=True | ||||||||||||||||||
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| actor_rollout_ref.actor.megatron.tensor_model_parallel_size=${train_tp} | ||||||||||||||||||
| actor_rollout_ref.actor.megatron.pipeline_model_parallel_size=${train_pp} | ||||||||||||||||||
| actor_rollout_ref.actor.megatron.context_parallel_size=${train_cp} | ||||||||||||||||||
| actor_rollout_ref.actor.megatron.expert_model_parallel_size=${train_ep} | ||||||||||||||||||
| actor_rollout_ref.actor.megatron.expert_tensor_parallel_size=${train_etp} | ||||||||||||||||||
| actor_rollout_ref.actor.megatron.param_offload=${all_offload} | ||||||||||||||||||
| actor_rollout_ref.actor.megatron.optimizer_offload=${all_offload} | ||||||||||||||||||
| actor_rollout_ref.actor.megatron.grad_offload=${all_offload} | ||||||||||||||||||
| actor_rollout_ref.actor.megatron.dist_checkpointing_path=${MCORE_MODEL_PATH} | ||||||||||||||||||
| actor_rollout_ref.actor.megatron.use_dist_checkpointing=False | ||||||||||||||||||
| +actor_rollout_ref.actor.megatron.override_transformer_config.use_flash_attn=True | ||||||||||||||||||
| +actor_rollout_ref.actor.megatron.override_transformer_config.recompute_method=uniform | ||||||||||||||||||
| +actor_rollout_ref.actor.megatron.override_transformer_config.recompute_granularity=full | ||||||||||||||||||
| +actor_rollout_ref.actor.megatron.override_transformer_config.recompute_num_layers=1 | ||||||||||||||||||
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| ) | ||||||||||||||||||
|
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||||||||||||||||||
| # Reference Model Configuration | ||||||||||||||||||
| REF_CONFIG=( | ||||||||||||||||||
| actor_rollout_ref.ref.use_torch_compile=False | ||||||||||||||||||
| actor_rollout_ref.ref.log_prob_micro_batch_size_per_gpu=1 | ||||||||||||||||||
| actor_rollout_ref.ref.log_prob_use_dynamic_bsz=${use_dynamic_bsz} | ||||||||||||||||||
| actor_rollout_ref.ref.log_prob_max_token_len_per_gpu=${infer_ppo_max_token_len} | ||||||||||||||||||
| actor_rollout_ref.ref.megatron.tensor_model_parallel_size=${train_tp} | ||||||||||||||||||
| actor_rollout_ref.ref.megatron.pipeline_model_parallel_size=${train_pp} | ||||||||||||||||||
| actor_rollout_ref.ref.megatron.context_parallel_size=${train_cp} | ||||||||||||||||||
| actor_rollout_ref.ref.megatron.expert_model_parallel_size=${train_ep} | ||||||||||||||||||
| actor_rollout_ref.ref.megatron.expert_tensor_parallel_size=${train_etp} | ||||||||||||||||||
| actor_rollout_ref.ref.megatron.param_offload=${all_offload} | ||||||||||||||||||
| actor_rollout_ref.ref.megatron.dist_checkpointing_path=${MCORE_MODEL_PATH} | ||||||||||||||||||
| actor_rollout_ref.ref.megatron.use_dist_checkpointing=False | ||||||||||||||||||
| ) | ||||||||||||||||||
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||||||||||||||||||
| # Rollout Configuration | ||||||||||||||||||
| ROLLOUT_CONFIG=( | ||||||||||||||||||
| actor_rollout_ref.rollout.name=vllm | ||||||||||||||||||
| actor_rollout_ref.rollout.n=${n_resp_per_prompt} | ||||||||||||||||||
| actor_rollout_ref.rollout.top_p=1.0 | ||||||||||||||||||
| actor_rollout_ref.rollout.top_k=-1 | ||||||||||||||||||
| actor_rollout_ref.rollout.temperature=1.0 | ||||||||||||||||||
| actor_rollout_ref.rollout.log_prob_micro_batch_size_per_gpu=1 | ||||||||||||||||||
| actor_rollout_ref.rollout.log_prob_use_dynamic_bsz=${use_dynamic_bsz} | ||||||||||||||||||
| actor_rollout_ref.rollout.log_prob_max_token_len_per_gpu=${infer_ppo_max_token_len} | ||||||||||||||||||
| actor_rollout_ref.rollout.gpu_memory_utilization=${gpu_memory_utilization} | ||||||||||||||||||
| actor_rollout_ref.rollout.max_num_batched_tokens=${max_num_batched_tokens} | ||||||||||||||||||
| actor_rollout_ref.rollout.max_model_len=${max_model_len} | ||||||||||||||||||
| actor_rollout_ref.rollout.tensor_model_parallel_size=${gen_tp} | ||||||||||||||||||
| actor_rollout_ref.rollout.data_parallel_size=${gen_dp} | ||||||||||||||||||
| actor_rollout_ref.rollout.expert_parallel_size=${gen_ep} | ||||||||||||||||||
| actor_rollout_ref.rollout.enable_chunked_prefill=True | ||||||||||||||||||
| actor_rollout_ref.rollout.enable_prefix_caching=True | ||||||||||||||||||
| actor_rollout_ref.rollout.enforce_eager=True | ||||||||||||||||||
| actor_rollout_ref.rollout.free_cache_engine=True | ||||||||||||||||||
| actor_rollout_ref.rollout.val_kwargs.n=1 | ||||||||||||||||||
| actor_rollout_ref.rollout.val_kwargs.do_sample=True | ||||||||||||||||||
| actor_rollout_ref.rollout.val_kwargs.top_p=1.0 | ||||||||||||||||||
| actor_rollout_ref.rollout.val_kwargs.top_k=-1 | ||||||||||||||||||
| actor_rollout_ref.rollout.val_kwargs.temperature=1.0 | ||||||||||||||||||
| ) | ||||||||||||||||||
|
|
||||||||||||||||||
| # Trainer Configuration | ||||||||||||||||||
| TRAINER_CONFIG=( | ||||||||||||||||||
| trainer.logger='["console","tensorboard"]' | ||||||||||||||||||
| trainer.project_name="${project_name}" | ||||||||||||||||||
| trainer.experiment_name="${exp_name}" | ||||||||||||||||||
| trainer.nnodes="${NNODES}" | ||||||||||||||||||
| trainer.n_gpus_per_node="${NPUS_PER_NODE}" | ||||||||||||||||||
| trainer.device='npu' | ||||||||||||||||||
| trainer.total_epochs=15 | ||||||||||||||||||
| trainer.val_before_train=False | ||||||||||||||||||
| trainer.test_freq=-1 | ||||||||||||||||||
| trainer.save_freq=-1 | ||||||||||||||||||
| trainer.default_local_dir="${CKPTS_DIR}" | ||||||||||||||||||
| ) | ||||||||||||||||||
|
|
||||||||||||||||||
| # Main GRPO Training Command | ||||||||||||||||||
| python3 -m verl.trainer.main_ppo \ | ||||||||||||||||||
| --config-path=config \ | ||||||||||||||||||
| --config-name='ppo_megatron_trainer.yaml' \ | ||||||||||||||||||
| "${DATA_CONFIG[@]}" \ | ||||||||||||||||||
| "${MODEL_CONFIG[@]}" \ | ||||||||||||||||||
| "${ACTOR_CONFIG[@]}" \ | ||||||||||||||||||
| "${REF_CONFIG[@]}" \ | ||||||||||||||||||
| "${ROLLOUT_CONFIG[@]}" \ | ||||||||||||||||||
| "${ALGORITHM_CONFIG[@]}" \ | ||||||||||||||||||
| "${TRAINER_CONFIG[@]}" \ | ||||||||||||||||||
| "$@" | tee logs/run_qwen3moe-30b_grpo_megatron_vllm_npu.log | ||||||||||||||||||
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These lines have a
+prefix, which is invalid syntax for a bash array assignment. This appears to be a copy-paste error from a diff and will cause the script to fail. Please remove the+prefixes.