trainer:
  nnodes: 1
  n_gpus_per_node: 8
  device: cuda

data:
  path: ~/data/rlhf/math/test.parquet
  prompt_key: prompt
  n_samples: 5
  output_path: /opt/tiger/math_Qwen2-7B-Instruct.parquet
  batch_size: 128

model:
  path: ~/models/Qwen2-7B-Instruct
  external_lib: null
rollout:
  _target_: verl.workers.config.RolloutConfig
  name: vllm
  mode: sync # sync: LLM, async: AsyncLLM
  temperature: 1.0
  top_k: 50 # 0 for hf rollout, -1 for vllm rollout
  top_p: 0.7
  prompt_length: 1536
  response_length: 512
  # for vllm rollout
  dtype: bfloat16 # should align with FSDP
  gpu_memory_utilization: 0.5
  ignore_eos: False
  enforce_eager: True
  free_cache_engine: True
  load_format: auto
  tensor_model_parallel_size: 1
  max_num_batched_tokens: 8192
  max_model_len: null
  max_num_seqs: 1024
  log_prob_micro_batch_size: null # will be deprecated, use log_prob_micro_batch_size_per_gpu
  log_prob_micro_batch_size_per_gpu: 8
  # for hf rollout
  do_sample: True
  disable_log_stats: True
  enable_chunked_prefill: True
  n: 1
  # support logging rollout prob for debugging purpose
  calculate_log_probs: False
actor:
  strategy: fsdp  # This is for backward-compatibility
  ulysses_sequence_parallel_size: 1 # sp size
  entropy_from_logits_with_chunking: False  # calculate entropy with chunking to reduce memory peak
  entropy_checkpointing: False  # recompute entropy
  fsdp_config:
    fsdp_size: -1
    forward_prefetch: False  # FSDP1 forward_prefetch configuration

ray_kwargs:
  ray_init:
    num_cpus: null # `None` means using all CPUs, which might cause hang if limited in systems like SLURM. Please set to a number allowed then.
  timeline_json_file: null
