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outputs/2026-06-01/23-08-51/.hydra/config.yaml

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+actor_rollout_ref:
+  actor:
+    optim:
+      _target_: verl.workers.config.FSDPOptimizerConfig
+      lr: 1.0e-06
+      lr_warmup_steps_ratio: 0.0
+      total_training_steps: -1
+      weight_decay: 0.01
+      lr_warmup_steps: -1
+      betas:
+      - 0.9
+      - 0.999
+      clip_grad: 1.0
+      min_lr_ratio: 0.0
+      num_cycles: 0.5
+      warmup_style: constant
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    _target_: verl.workers.config.FSDPActorConfig
+    strategy: fsdp
+    ppo_mini_batch_size: ${ppo_mini_batch_size}
+    ppo_micro_batch_size: null
+    ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+    use_dynamic_bsz: false
+    ppo_max_token_len_per_gpu: 16384
+    clip_ratio: 0.2
+    clip_ratio_low: 0.2
+    clip_ratio_high: 0.28
+    freeze_vision_tower: false
+    policy_loss:
+      _target_: verl.workers.config.PolicyLossConfig
+      loss_mode: vanilla
+      clip_cov_ratio: 0.0002
+      clip_cov_lb: 1.0
+      clip_cov_ub: 5.0
+      kl_cov_ratio: 0.0002
+      ppo_kl_coef: 0.1
+    clip_ratio_c: 3.0
+    loss_agg_mode: token-mean
+    entropy_coeff: 0.001
+    tis_imp_ratio_cap: -1
+    use_kl_loss: false
+    use_torch_compile: true
+    kl_loss_coef: 0.0
+    kl_loss_type: kl
+    ppo_epochs: 1
+    shuffle: false
+    checkpoint:
+      _target_: verl.trainer.config.CheckpointConfig
+      save_contents:
+      - model
+      - optimizer
+      - extra
+      load_contents: ${.save_contents}
+      async_save: false
+    use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: false
+      all_ranks: false
+      ranks: []
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config:
+        nsys:
+          _target_: verl.utils.profiler.config.NsightToolConfig
+          discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+        npu:
+          _target_: verl.utils.profiler.config.NPUToolConfig
+          contents: []
+          level: level1
+          analysis: true
+          discrete: false
+        torch:
+          _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+          step_start: 0
+          step_end: null
+        torch_memory:
+          _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+          trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+          stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+    grad_clip: 1.0
+    ulysses_sequence_parallel_size: 1
+    entropy_from_logits_with_chunking: false
+    entropy_checkpointing: false
+    use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+    use_ref: true
+    grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+    filter_loss_scaling: none
+  ref:
+    strategy: ${actor_rollout_ref.actor.strategy}
+    use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+    log_prob_micro_batch_size: null
+    log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+    log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+    log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: false
+      all_ranks: false
+      ranks: []
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config:
+        nsys:
+          _target_: verl.utils.profiler.config.NsightToolConfig
+          discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+        npu:
+          _target_: verl.utils.profiler.config.NPUToolConfig
+          contents: []
+          level: level1
+          analysis: true
+          discrete: false
+        torch:
+          _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+          step_start: 0
+          step_end: null
+        torch_memory:
+          _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+          trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+          stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    model: null
+    ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+    entropy_from_logits_with_chunking: false
+    entropy_checkpointing: false
+  rollout:
+    _target_: verl.workers.config.RolloutConfig
+    name: vllm
+    mode: sync
+    temperature: 1
+    top_k: -1
+    top_p: 1
+    prompt_length: 1
+    response_length: 400
+    dtype: bfloat16
+    gpu_memory_utilization: 0.7
+    ignore_eos: false
+    enforce_eager: true
+    cudagraph_capture_sizes: null
+    free_cache_engine: true
+    tensor_model_parallel_size: 1
+    data_parallel_size: 1
+    expert_parallel_size: 1
+    max_num_batched_tokens: 16384
+    max_model_len: 16384
+    max_num_seqs: 1024
+    enable_chunked_prefill: true
+    enable_prefix_caching: true
+    load_format: auto
+    log_prob_micro_batch_size: null
+    log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+    log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+    log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+    disable_log_stats: true
+    do_sample: true
+    'n': 1
+    over_sample_rate: 0
+    multi_stage_wake_up: false
+    engine_kwargs:
+      vllm: {}
+      sglang: {}
+    val_kwargs:
+      _target_: verl.workers.config.SamplingConfig
+      top_k: -1
+      top_p: 1.0
+      temperature: 0.5
+      'n': 1
+      do_sample: true
+    multi_turn:
+      _target_: verl.workers.config.MultiTurnConfig
+      enable: false
+      max_assistant_turns: null
+      tool_config_path: null
+      max_user_turns: null
+      max_parallel_calls: 1
+      max_tool_response_length: 256
+      tool_response_truncate_side: middle
+      interaction_config_path: null
+      use_inference_chat_template: false
+      tokenization_sanity_check_mode: strict
+      format: hermes
+      num_repeat_rollouts: null
+    calculate_log_probs: false
+    agent:
+      _target_: verl.workers.config.AgentLoopConfig
+      num_workers: 8
+      agent_loop_config_path: null
+      custom_async_server:
+        _target_: verl.workers.config.CustomAsyncServerConfig
+        path: null
+        name: null
+    update_weights_bucket_megabytes: 512
+    trace:
+      _target_: verl.workers.config.TraceConfig
+      backend: null
+      token2text: false
+    skip_rollout: false
+    skip_dump_dir: /tmp/rollout_dump
+    skip_tokenizer_init: true
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+      all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+      ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+    layered_summon: false
+    rollout_filter_value: 0.9
+    rollout_filter_strategy: top_p
+    rollout_filter_type: largest
+    rollout_filter_include_zero: true
+    rollout_filter_top_p_prob_mode: linear
+    rollout_filter_selection_eps: 0.01
+    rollout_filter_empty_stop_steps: 5
+    rollout_filter_metric: reward_variance
+    gradient_analysis_num_buckets: 6
+    gradient_analysis_bucket_mode: quantile
+  model:
+    _target_: verl.workers.config.HFModelConfig
+    path: ${model_path}
+    hf_config_path: null
+    tokenizer_path: null
+    use_shm: false
+    trust_remote_code: false
+    custom_chat_template: null
+    external_lib: null
+    override_config: {}
+    enable_gradient_checkpointing: true
+    enable_activation_offload: false
+    use_remove_padding: false
+    lora_rank: ${lora.rank}
+    lora_alpha: ${lora.alpha}
+    target_modules: ${lora.target_modules}
+    exclude_modules: null
+    use_liger: false
+    use_fused_kernels: false
+    fused_kernel_options:
+      impl_backend: torch
+  hybrid_engine: true
+  nccl_timeout: 600
+data:
+  tokenizer: null
+  use_shm: false
+  train_files: ~/data/rlhf/gsm8k/train.parquet
+  val_files: ~/data/rlhf/gsm8k/test.parquet
+  prompt_key: prompt
+  reward_fn_key: data_source
+  max_prompt_length: null
+  max_response_length: null
+  train_batch_size: null
+  val_batch_size: null
+  return_raw_input_ids: false
+  return_raw_chat: false
+  return_full_prompt: false
+  shuffle: true
+  dataloader_num_workers: 8
+  validation_shuffle: false
+  filter_overlong_prompts: false
+  filter_overlong_prompts_workers: 1
+  truncation: error
+  image_key: images
+  video_key: videos
+  trust_remote_code: false
+  custom_cls:
+    path: null
+    name: null
+  return_multi_modal_inputs: true
+  sampler:
+    class_path: null
+    class_name: null
+  datagen:
+    path: null
+    name: null
+  apply_chat_template_kwargs: {}
+critic:
+  optim:
+    _target_: verl.workers.config.FSDPOptimizerConfig
+    lr: 1.0e-05
+    lr_warmup_steps_ratio: 0.0
+    total_training_steps: -1
+    weight_decay: 0.01
+    lr_warmup_steps: -1
+    betas:
+    - 0.9
+    - 0.999
+    clip_grad: 1.0
+    min_lr_ratio: 0.0
+    num_cycles: 0.5
+    warmup_style: constant
+  model:
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    path: ${model_path}
+    tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+    override_config: {}
+    external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+    trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+    _target_: verl.workers.config.FSDPCriticModelCfg
+    use_shm: false
+    enable_gradient_checkpointing: true
+    enable_activation_offload: false
+    use_remove_padding: false
+    lora_rank: ${lora.rank}
+    lora_alpha: ${lora.alpha}
+    target_modules: ${lora.target_modules}
+  _target_: verl.workers.config.FSDPCriticConfig
+  rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+  strategy: fsdp
+  enable: null
+  ppo_mini_batch_size: ${ppo_mini_batch_size}
+  ppo_micro_batch_size: null
+  ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+  use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+  ppo_max_token_len_per_gpu: 32768
+  forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+  ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+  shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+  cliprange_value: 0.5
+  loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+  checkpoint:
+    _target_: verl.trainer.config.CheckpointConfig
+    save_contents:
+    - model
+    - optimizer
+    - extra
+    load_contents: ${.save_contents}
+    async_save: false
+  profiler:
+    _target_: verl.utils.profiler.ProfilerConfig
+    tool: ${oc.select:global_profiler.tool,null}
+    enable: false
+    all_ranks: false
+    ranks: []
+    save_path: ${oc.select:global_profiler.save_path,null}
+    tool_config:
+      nsys:
+        _target_: verl.utils.profiler.config.NsightToolConfig
+        discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+      npu:
+        _target_: verl.utils.profiler.config.NPUToolConfig
+        contents: []
+        level: level1
+        analysis: true
+        discrete: false
+      torch:
+        _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+        step_start: 0
+        step_end: null
+      torch_memory:
+        _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+        trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+        stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+  forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+  forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+  ulysses_sequence_parallel_size: 1
+  grad_clip: 1.0
+reward_model:
+  enable: false
+  enable_resource_pool: false
+  n_gpus_per_node: 0
+  nnodes: 0
+  strategy: fsdp
+  model:
+    input_tokenizer: ${actor_rollout_ref.model.path}
+    path: ~/models/FsfairX-LLaMA3-RM-v0.1
+    external_lib: ${actor_rollout_ref.model.external_lib}
+    trust_remote_code: false
+    use_shm: false
+    use_remove_padding: false
+    use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+  micro_batch_size: null
+  micro_batch_size_per_gpu: null
+  max_length: null
+  use_dynamic_bsz: ${critic.use_dynamic_bsz}
+  forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+  reward_manager: naive
+  launch_reward_fn_async: false
+  sandbox_fusion:
+    url: null
+    max_concurrent: 64
+    memory_limit_mb: 1024
+  profiler:
+    _target_: verl.utils.profiler.ProfilerConfig
+    tool: ${oc.select:global_profiler.tool,null}
+    enable: false
+    all_ranks: false
+    ranks: []
+    save_path: ${oc.select:global_profiler.save_path,null}
+    tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+  ulysses_sequence_parallel_size: 1
+custom_reward_function:
+  path: null
+  name: compute_score
+algorithm:
+  _target_: verl.trainer.config.AlgoConfig
+  gamma: 1.0
+  lam: 1.0
+  adv_estimator: gae
+  norm_adv_by_std_in_grpo: true
+  use_kl_in_reward: false
+  kl_penalty: kl
+  kl_ctrl:
+    _target_: verl.trainer.config.KLControlConfig
+    type: fixed
+    kl_coef: 0.0
+    horizon: 10000
+    target_kl: 0.1
+  use_pf_ppo: false
+  pf_ppo:
+    reweight_method: pow
+    weight_pow: 2.0
+  high_level_gamma: 0.95
+  bi_level_gae: false
+  zero_task_advantage: false
+  soft_advantage_reweight: false
+trainer:
+  balance_batch: true
+  total_epochs: 30
+  total_training_steps: 1000
+  project_name: ragen
+  experiment_name: sudoku_3b_baseline
+  logger:
+  - console
+  - wandb
+  log_val_generations: 0
+  rollout_data_dir: null
+  validation_data_dir: null
+  nnodes: 1
+  n_gpus_per_node: 8
+  save_freq: -1
+  esi_redundant_time: 0
+  resume_mode: auto
+  resume_from_path: null
+  val_before_train: true
+  val_only: false
+  test_freq: 10
+  critic_warmup: 0
+  default_hdfs_dir: null
+  del_local_ckpt_after_load: false
+  default_local_dir: checkpoints/${trainer.project_name}/${trainer.experiment_name}
+  max_actor_ckpt_to_keep: 1
+  max_critic_ckpt_to_keep: 1
+  ray_wait_register_center_timeout: 300
+  device: cuda
+  use_legacy_worker_impl: auto
+  local_log_dir: results/
+  validation_steps: 1
+  generations_to_log_to_wandb:
+    val: 20
+  log_group_rv_table: false
+  gradient_analysis_mode: false
+  gradient_analysis_every: 50
+  gradient_analysis_env_groups: null
+  gradient_analysis_group_size: null
+  gradient_analysis_log_prefilter: false
+  gradient_analysis_only: false
+  exit_after_gradient_analysis: false
+global_profiler:
+  _target_: verl.utils.profiler.ProfilerConfig
+  tool: null
+  steps: null
+  profile_continuous_steps: false
+  save_path: outputs/profile
+  global_tool_config:
+    nsys:
+      _target_: verl.utils.profiler.config.NsightToolConfig
+      discrete: false
+      controller_nsight_options:
+        trace: cuda,nvtx,cublas,ucx
+        cuda-memory-usage: 'true'
+        cuda-graph-trace: graph
+      worker_nsight_options:
+        trace: cuda,nvtx,cublas,ucx
+        cuda-memory-usage: 'true'
+        cuda-graph-trace: graph
+        capture-range: cudaProfilerApi
+        capture-range-end: null
+        kill: none
+    torch_memory:
+      trace_alloc_max_entries: 100000
+      stack_depth: 32
+      context: all
+      stacks: all
+      kw_args: {}
+ray_kwargs:
+  ray_init:
+    num_cpus: null
+  timeline_json_file: null
+custom_envs:
+  SimpleSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 20
+    env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+      \ when reasoning:\n1. First compare the box position with the target position;\
+      \ the useful push directions are usually the directions that reduce their row/column\
+      \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+      \ push direction. A move that only repositions the player can be useful if it\
+      \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+      \ dead end unless that square is the target or clearly on the only path to the\
+      \ target.\n4. Prefer short plans that move the single box steadily toward the\
+      \ target; avoid wandering moves that do not improve player position or box position.\n\
+      5. If the box and target are aligned in the same row or column, try to keep\
+      \ the box on that line and push along it.\n6. If they are not aligned, first\
+      \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+      7. Check that after each push, the player can still reach the next required\
+      \ pushing side of the box.\n8. Output only the required XML-like format and\
+      \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+      \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+      \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+      \ pull a box. \nThe answer should be a sequence of actions, like <answer>Right\
+      \ || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 2
+      max_steps: 100
+  LargerSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+      \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+      \ you can push it by moving in the same direction. \nYou cannot push a box through\
+      \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+      \ like <answer>Right || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 8
+      dim_y: 8
+      num_boxes: 2
+      max_steps: 100
+      search_depth: 10
+  SokobanDifferentGridVocab:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+      \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+      \ you can push it by moving in the same direction. \nYou cannot push a box through\
+      \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+      \ like <answer>Right || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      search_depth: 30
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      grid_lookup:
+        0: W
+        1: .
+        2: G
+        3: C
+        4: B
+        5: A
+        6: '@'
+      grid_vocab:
+        W: wall
+        .: empty
+        G: target
+        C: box on target
+        B: box
+        A: player
+        '@': player on target
+  CoordSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+      \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+      \ the zero-indexed coordinates of the player, each box, and each target. \n\
+      Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+      \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+      \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+      \ pull a box.\nThe answer should be a sequence of actions, like <answer>Right\
+      \ || Right || Up</answer>.\n"
+    max_tokens: 120
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      observation_format: grid_coord
+  VisualSimpleSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: You are solving the Sokoban puzzle. You are the player and you
+      need to push all boxes to targets. When you are right next to a box, you can
+      push it by moving in the same direction. You cannot push a box through a wall,
+      and you cannot pull a box. The answer should be a sequence of actions, like
+      <answer>Right || Right || Up</answer>
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      render_mode: rgb_array
+  Alfworld:
+    env_type: alfworld
+    max_actions_per_traj: 50
+    parallel_friendly: false
+    max_workers: 1
+    env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+      Complete household tasks by navigating and interacting with objects.
+
+
+      You should first reason step-by-step about the current situation. This reasoning
+      process MUST be enclosed within <think> </think> tags.
+
+      Once you''ve finished your reasoning, you should choose an admissible action
+      for current step and present it within <answer>...</answer> tags.
+
+      '
+    max_tokens: 512
+    env_config:
+      eval_dataset: eval_in_distribution
+  AlfworldOOD:
+    env_type: alfworld
+    max_actions_per_traj: 50
+    parallel_friendly: false
+    max_workers: 1
+    env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+      Complete household tasks by navigating and interacting with objects.
+
+
+      You should first reason step-by-step about the current situation. This reasoning
+      process MUST be enclosed within <think> </think> tags.
+
+      Once you''ve finished your reasoning, you should choose an admissible action
+      for current step and present it within <answer>...</answer> tags.
+
+      '
+    max_tokens: 512
+    env_config:
+      eval_dataset: eval_out_of_distribution
+  Countdown:
+    env_type: countdown
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving the Countdown puzzle. You should use the num
+      list to create an equation that equals the target. Example answer format: <think>
+      To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+      = 4. So the answer is 2 + 5 - 3 = 4. </think><answer>2 + 5 - 3</answer>'
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config: null
+  Bandit:
+    env_type: bandit
+    max_actions_per_traj: 1
+    env_instruction: ''
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      split: train
+  BanditTest:
+    env_type: bandit
+    max_actions_per_traj: 1
+    env_instruction: ''
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      split: test
+  DeepCoder:
+    env_type: deepcoder
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving a coding task. Provide a complete Python function
+      solution only. Format: <answer>...</answer>'
+    max_tokens: 8000
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 1
+  FrozenLake:
+    env_type: frozen_lake
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+      go to the target. You may move to the unintended direction due to the slippery
+      ice. Example answer format: <think>To forbid the hole and go to the target,
+      I should go left then go up.</think><answer>Left || Up</answer>'
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      success_rate: 0.8
+  CoordFrozenLake:
+    env_type: frozen_lake
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+      both a symbol grid and zero-indexed coordinates for the start, goal, player,
+      and any holes.
+
+      Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+      (5, 5).
+
+      Beware that the ice is slippery, so the agent might slide and end up in an unintended
+      tile.
+
+      Respond with a sequence of actions such as <answer>Left || Up || Up</answer>.
+
+      '
+    max_tokens: 120
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      observation_format: grid_coord
+      success_rate: 0.8
+  MetamathQA:
+    env_type: metamathqa
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving Math problems. '
+    max_tokens: 100
+    env_config: null
+  WebShopFull:
+    env_type: webshop
+    max_actions_per_traj: 15
+    env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+      environment.
+    max_tokens: 200
+    env_config:
+      dataset: full
+  WebShop:
+    env_type: webshop
+    max_actions_per_traj: 9
+    env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+      a product that close to the production description. You need to search, read
+      the search results, pick a product, choose the size and color and buy. You should
+      only choose action from the available actions list provided later.  Example
+      process: I need a gingko light and 20x20 pillow cover that is hand painted.
+      First search[gingko light 20x20 pillow cover hand painted], answer format: <answer>search[blanket
+      with fleece throw]</answer>. Valid answer is search[<keywords>] or click[<clickable>].'
+    max_tokens: 200
+    env_config:
+      dataset: small
+  Lean:
+    env_type: lean
+    max_actions_per_traj: 30
+    env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+      propose a sequence of tactics that completes the proof. Think step by step about
+      which tactics to apply next. Provide tactics separated by '||', for example
+      <answer>intro || simp || rfl</answer>.
+    max_tokens: 512
+    parallel_friendly: true
+    max_workers: 32
+    env_config: null
+  SimpleSudoku:
+    env_type: sudoku
+    max_actions_per_traj: 20
+    env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+      row, column, and 2x2 box contains the numbers 1-4 without repetition.
+
+      Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+      shown as dots (.).
+
+      Place numbers one at a time using the format: <answer>place 1 at row 2 col 3</answer>
+
+      Always output: <think> [brief constraint-based reasoning] </think> <answer>
+      [one placement] </answer>
+
+      The environment will provide feedback on valid/invalid moves and show conflicts
+      if any occur.
+
+      '
+    max_tokens: 150
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      grid_size: 4
+      difficulty: easy
+      render_format: with_feedback
+      show_conflicts: false
+      show_valid_numbers: false
+      max_steps: 20
+  MediumSudoku:
+    env_type: sudoku
+    max_actions_per_traj: 30
+    env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+      row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+      Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+      shown as dots (.).
+
+      Place numbers one at a time using the format: <answer>place 5 at row 2 col 3</answer>
+      or <answer>2,3,5</answer>
+
+      The environment will provide feedback on valid/invalid moves and show conflicts
+      if any occur.
+
+      '
+    max_tokens: 150
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      grid_size: 9
+      difficulty: medium
+      render_format: with_feedback
+      show_conflicts: true
+      show_valid_numbers: true
+      max_steps: 81
+  SearchQA:
+    env_type: search
+    max_actions_per_traj: 10
+    env_instruction: "You are a search agent answering questions by searching for\
+      \ information.\nUse search[your query] to find relevant documents, and finish[your\
+      \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+      \ about the current situation. This reasoning process MUST be enclosed within\
+      \ <think> </think> tags.\nThen provide your action within <answer>...</answer>\
+      \ tags.\n\nExamples:\n  <think>I need to find information about Ben Platt's\
+      \ father.</think><answer>search[Ben Platt father parent]</answer>\n  <think>Based\
+      \ on the search results, Ben Platt's father is Henry Platt.</think><answer>finish[Henry\
+      \ Platt]</answer>\n"
+    max_tokens: 300
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 10
+      max_search_results: 5
+  SearchQAMock:
+    env_type: search
+    max_actions_per_traj: 10
+    env_instruction: "You are a search agent answering questions by searching for\
+      \ information.\nUse search[your query] to find relevant documents, and finish[your\
+      \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+      \ about the current situation. This reasoning process MUST be enclosed within\
+      \ <think> </think> tags.\nThen provide your action within <answer>...</answer>\
+      \ tags.\n\nExamples:\n  <think>I need to find information about Ben Platt's\
+      \ father.</think><answer>search[Ben Platt father parent]</answer>\n  <think>Based\
+      \ on the search results, Ben Platt's father is Henry Platt.</think><answer>finish[Henry\
+      \ Platt]</answer>\n"
+    max_tokens: 300
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 10
+      max_search_results: 5
+      mock_mode: true
+  game_2048:
+    env_type: game_2048
+    max_actions_per_traj: 700
+    env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+      by sliding Up, Right, Down, or Left.
+
+      If a move is invalid (no tiles move), a small penalty is applied. Respond with
+      a single action.
+
+      Example: <answer>Up</answer>
+
+      '
+    max_tokens: 8192
+    env_config: null
+  rubikscube:
+    env_type: rubikscube
+    max_actions_per_traj: 20
+    env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+      is to restore the cube so that each of the faces consists of a single, unique
+      color.
+
+      Available actions use standard Singmaster notation for face rotations: U, U'',
+      D, D'', L, L'', R, R'', F, F'', B, B''.
+
+      - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+      - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+      prime ('') means 90° counter-clockwise (e.g., "R''").
+
+      Respond with a sequence of actions separated by "||".
+
+      Example: <answer>U</answer>
+
+      '
+    max_tokens: 96
+    env_config:
+      scramble_depth: 1
+      max_steps: 20
+      render_mode: text
+system:
+  CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+  train: 10000
+  val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/share/model/Qwen/Qwen2.5-3B-Instruct
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+  rank: 0
+  alpha: 64
+  target_modules: all-linear
+agent_proxy:
+  context_window_mode: full
+  max_context_window: -1
+  batch_adjust_mode: copy
+  max_turn: 20
+  action_sep: '||'
+  max_actions_per_turn: 3
+  use_turn_scores: false
+  enable_think: true
+  reward_normalization:
+    grouping: state
+    method: identity
+collapse_detection:
+  compute_freq: 5
+  micro_batch_size: 128
+  first_turn_enabled: true
+  multi_turn_enabled: true
+  num_samples: 64
+es_manager:
+  format_penalty: -0.1
+  train:
+    env_groups: 8
+    group_size: 16
+    env_configs:
+      tags:
+      - SimpleSudoku
+      n_groups:
+      - 8
+  val:
+    env_groups: 32
+    group_size: 16
+    env_configs:
+      tags:
+      - SimpleSudoku
+      n_groups:
+      - 32
+ctx_manager:
+  generation:
+    gen_config:
+      response_length: ${actor_rollout_ref.rollout.response_length}
+      temperature: ${actor_rollout_ref.rollout.temperature}
+      top_p: ${actor_rollout_ref.rollout.top_p}
+      top_k: ${actor_rollout_ref.rollout.top_k}
+      kwargs: null

outputs/2026-06-07/23-18-01/.hydra/hydra.yaml

@@ -0,0 +1,178 @@
+hydra:
+  run:
+    dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+  sweep:
+    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath:
+  - pkg://verl.trainer.config
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task:
+    - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+    - actor_rollout_ref.rollout.rollout_filter_value=0.9
+    - trainer.total_training_steps=200
+    - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_sokoban_box2_withthink_sas
+    - trainer.experiment_name=sokoban_3b_box2_withthink_sas
+  job:
+    name: train
+    chdir: null
+    override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_sokoban_box2_withthink_sas,trainer.experiment_name=sokoban_3b_box2_withthink_sas,trainer.total_training_steps=200
+    id: ???
+    num: ???
+    config_name: _2_sokoban
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /mnt/general/wanghy/RAGEN_v2
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /mnt/general/wanghy/RAGEN_v2/config
+      schema: file
+      provider: main
+    - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+      schema: file
+      provider: command-line
+    - path: verl.trainer.config
+      schema: pkg
+      provider: hydra.searchpath in main
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-07/23-18-01
+    choices:
+      reward_model: dp_reward_model
+      critic: dp_critic
+      critic/../engine@critic.model.fsdp_config: fsdp
+      critic/../optim@critic.optim: fsdp
+      model@actor_rollout_ref.model: hf_model
+      rollout@actor_rollout_ref.rollout: rollout
+      ref@actor_rollout_ref.ref: dp_ref
+      ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+      data: legacy_data
+      actor@actor_rollout_ref.actor: dp_actor
+      actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+      actor/../optim@actor_rollout_ref.actor.optim: fsdp
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

outputs/2026-06-09/00-36-11/.hydra/hydra.yaml

@@ -0,0 +1,177 @@
+hydra:
+  run:
+    dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+  sweep:
+    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task:
+    - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+    - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+    - actor_rollout_ref.rollout.rollout_filter_value=0.9
+    - trainer.total_training_steps=200
+    - trainer.n_gpus_per_node=8
+    - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_sas
+    - custom_envs.rubikscube.env_config.scramble_depth=1
+    - trainer.experiment_name=rubikscube1_withthink_sas
+  job:
+    name: train
+    chdir: null
+    override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=1,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_sas,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.experiment_name=rubikscube1_withthink_sas,trainer.n_gpus_per_node=8,trainer.total_training_steps=200
+    id: ???
+    num: ???
+    config_name: _10_rubikscube
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /mnt/general/wanghy/RAGEN_v2
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /mnt/general/wanghy/RAGEN_v2/config
+      schema: file
+      provider: main
+    - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-09/00-36-11
+    choices:
+      reward_model: dp_reward_model
+      critic: dp_critic
+      critic/../engine@critic.model.fsdp_config: fsdp
+      critic/../optim@critic.optim: fsdp
+      model@actor_rollout_ref.model: hf_model
+      rollout@actor_rollout_ref.rollout: rollout
+      ref@actor_rollout_ref.ref: dp_ref
+      ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+      data: legacy_data
+      actor@actor_rollout_ref.actor: dp_actor
+      actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+      actor/../optim@actor_rollout_ref.actor.optim: fsdp
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

outputs/2026-06-09/02-32-07/.hydra/config.yaml

@@ -0,0 +1,1003 @@
+actor_rollout_ref:
+  actor:
+    optim:
+      _target_: verl.workers.config.FSDPOptimizerConfig
+      lr: 1.0e-06
+      lr_warmup_steps_ratio: 0.0
+      total_training_steps: -1
+      weight_decay: 0.01
+      lr_warmup_steps: -1
+      betas:
+      - 0.9
+      - 0.999
+      clip_grad: 1.0
+      min_lr_ratio: 0.0
+      num_cycles: 0.5
+      warmup_style: constant
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    _target_: verl.workers.config.FSDPActorConfig
+    strategy: fsdp
+    ppo_mini_batch_size: ${ppo_mini_batch_size}
+    ppo_micro_batch_size: null
+    ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+    use_dynamic_bsz: false
+    ppo_max_token_len_per_gpu: 16384
+    clip_ratio: 0.2
+    clip_ratio_low: 0.2
+    clip_ratio_high: 0.28
+    freeze_vision_tower: false
+    policy_loss:
+      _target_: verl.workers.config.PolicyLossConfig
+      loss_mode: vanilla
+      clip_cov_ratio: 0.0002
+      clip_cov_lb: 1.0
+      clip_cov_ub: 5.0
+      kl_cov_ratio: 0.0002
+      ppo_kl_coef: 0.1
+    clip_ratio_c: 3.0
+    loss_agg_mode: token-mean
+    entropy_coeff: 0.001
+    tis_imp_ratio_cap: -1
+    use_kl_loss: false
+    use_torch_compile: true
+    kl_loss_coef: 0.0
+    kl_loss_type: kl
+    ppo_epochs: 1
+    shuffle: false
+    checkpoint:
+      _target_: verl.trainer.config.CheckpointConfig
+      save_contents:
+      - model
+      - optimizer
+      - extra
+      load_contents: ${.save_contents}
+      async_save: false
+    use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: false
+      all_ranks: false
+      ranks: []
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config:
+        nsys:
+          _target_: verl.utils.profiler.config.NsightToolConfig
+          discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+        npu:
+          _target_: verl.utils.profiler.config.NPUToolConfig
+          contents: []
+          level: level1
+          analysis: true
+          discrete: false
+        torch:
+          _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+          step_start: 0
+          step_end: null
+        torch_memory:
+          _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+          trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+          stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+    grad_clip: 1.0
+    ulysses_sequence_parallel_size: 1
+    entropy_from_logits_with_chunking: false
+    entropy_checkpointing: false
+    use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+    use_ref: true
+    grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+    filter_loss_scaling: none
+  ref:
+    strategy: ${actor_rollout_ref.actor.strategy}
+    use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+    log_prob_micro_batch_size: null
+    log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+    log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+    log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: false
+      all_ranks: false
+      ranks: []
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config:
+        nsys:
+          _target_: verl.utils.profiler.config.NsightToolConfig
+          discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+        npu:
+          _target_: verl.utils.profiler.config.NPUToolConfig
+          contents: []
+          level: level1
+          analysis: true
+          discrete: false
+        torch:
+          _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+          step_start: 0
+          step_end: null
+        torch_memory:
+          _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+          trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+          stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    model: null
+    ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+    entropy_from_logits_with_chunking: false
+    entropy_checkpointing: false
+  rollout:
+    _target_: verl.workers.config.RolloutConfig
+    name: vllm
+    mode: sync
+    temperature: 1
+    top_k: -1
+    top_p: 1
+    prompt_length: 1
+    response_length: 500
+    dtype: bfloat16
+    gpu_memory_utilization: 0.7
+    ignore_eos: false
+    enforce_eager: true
+    cudagraph_capture_sizes: null
+    free_cache_engine: true
+    tensor_model_parallel_size: 1
+    data_parallel_size: 1
+    expert_parallel_size: 1
+    max_num_batched_tokens: 16384
+    max_model_len: 16384
+    max_num_seqs: 1024
+    enable_chunked_prefill: true
+    enable_prefix_caching: true
+    load_format: auto
+    log_prob_micro_batch_size: null
+    log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+    log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+    log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+    disable_log_stats: true
+    do_sample: true
+    'n': 1
+    over_sample_rate: 0
+    multi_stage_wake_up: false
+    engine_kwargs:
+      vllm: {}
+      sglang: {}
+    val_kwargs:
+      _target_: verl.workers.config.SamplingConfig
+      top_k: -1
+      top_p: 1.0
+      temperature: 0.5
+      'n': 1
+      do_sample: true
+    multi_turn:
+      _target_: verl.workers.config.MultiTurnConfig
+      enable: false
+      max_assistant_turns: null
+      tool_config_path: null
+      max_user_turns: null
+      max_parallel_calls: 1
+      max_tool_response_length: 256
+      tool_response_truncate_side: middle
+      interaction_config_path: null
+      use_inference_chat_template: false
+      tokenization_sanity_check_mode: strict
+      format: hermes
+      num_repeat_rollouts: null
+    calculate_log_probs: false
+    agent:
+      _target_: verl.workers.config.AgentLoopConfig
+      num_workers: 8
+      agent_loop_config_path: null
+      custom_async_server:
+        _target_: verl.workers.config.CustomAsyncServerConfig
+        path: null
+        name: null
+    update_weights_bucket_megabytes: 512
+    trace:
+      _target_: verl.workers.config.TraceConfig
+      backend: null
+      token2text: false
+    skip_rollout: false
+    skip_dump_dir: /tmp/rollout_dump
+    skip_tokenizer_init: true
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+      all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+      ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+    layered_summon: false
+    rollout_filter_value: 0.9
+    rollout_filter_strategy: top_p
+    rollout_filter_type: largest
+    rollout_filter_include_zero: true
+    rollout_filter_top_p_prob_mode: linear
+    rollout_filter_selection_eps: 0.01
+    rollout_filter_empty_stop_steps: 5
+    rollout_filter_metric: reward_variance
+    gradient_analysis_num_buckets: 6
+    gradient_analysis_bucket_mode: quantile
+  model:
+    _target_: verl.workers.config.HFModelConfig
+    path: ${model_path}
+    hf_config_path: null
+    tokenizer_path: null
+    use_shm: false
+    trust_remote_code: false
+    custom_chat_template: null
+    external_lib: null
+    override_config: {}
+    enable_gradient_checkpointing: true
+    enable_activation_offload: false
+    use_remove_padding: false
+    lora_rank: ${lora.rank}
+    lora_alpha: ${lora.alpha}
+    target_modules: ${lora.target_modules}
+    exclude_modules: null
+    use_liger: false
+    use_fused_kernels: false
+    fused_kernel_options:
+      impl_backend: torch
+  hybrid_engine: true
+  nccl_timeout: 600
+data:
+  tokenizer: null
+  use_shm: false
+  train_files: ~/data/rlhf/gsm8k/train.parquet
+  val_files: ~/data/rlhf/gsm8k/test.parquet
+  prompt_key: prompt
+  reward_fn_key: data_source
+  max_prompt_length: null
+  max_response_length: null
+  train_batch_size: null
+  val_batch_size: null
+  return_raw_input_ids: false
+  return_raw_chat: false
+  return_full_prompt: false
+  shuffle: true
+  dataloader_num_workers: 8
+  validation_shuffle: false
+  filter_overlong_prompts: false
+  filter_overlong_prompts_workers: 1
+  truncation: error
+  image_key: images
+  video_key: videos
+  trust_remote_code: false
+  custom_cls:
+    path: null
+    name: null
+  return_multi_modal_inputs: true
+  sampler:
+    class_path: null
+    class_name: null
+  datagen:
+    path: null
+    name: null
+  apply_chat_template_kwargs: {}
+critic:
+  optim:
+    _target_: verl.workers.config.FSDPOptimizerConfig
+    lr: 1.0e-05
+    lr_warmup_steps_ratio: 0.0
+    total_training_steps: -1
+    weight_decay: 0.01
+    lr_warmup_steps: -1
+    betas:
+    - 0.9
+    - 0.999
+    clip_grad: 1.0
+    min_lr_ratio: 0.0
+    num_cycles: 0.5
+    warmup_style: constant
+  model:
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    path: ${model_path}
+    tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+    override_config: {}
+    external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+    trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+    _target_: verl.workers.config.FSDPCriticModelCfg
+    use_shm: false
+    enable_gradient_checkpointing: true
+    enable_activation_offload: false
+    use_remove_padding: false
+    lora_rank: ${lora.rank}
+    lora_alpha: ${lora.alpha}
+    target_modules: ${lora.target_modules}
+  _target_: verl.workers.config.FSDPCriticConfig
+  rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+  strategy: fsdp
+  enable: null
+  ppo_mini_batch_size: ${ppo_mini_batch_size}
+  ppo_micro_batch_size: null
+  ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+  use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+  ppo_max_token_len_per_gpu: 32768
+  forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+  ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+  shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+  cliprange_value: 0.5
+  loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+  checkpoint:
+    _target_: verl.trainer.config.CheckpointConfig
+    save_contents:
+    - model
+    - optimizer
+    - extra
+    load_contents: ${.save_contents}
+    async_save: false
+  profiler:
+    _target_: verl.utils.profiler.ProfilerConfig
+    tool: ${oc.select:global_profiler.tool,null}
+    enable: false
+    all_ranks: false
+    ranks: []
+    save_path: ${oc.select:global_profiler.save_path,null}
+    tool_config:
+      nsys:
+        _target_: verl.utils.profiler.config.NsightToolConfig
+        discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+      npu:
+        _target_: verl.utils.profiler.config.NPUToolConfig
+        contents: []
+        level: level1
+        analysis: true
+        discrete: false
+      torch:
+        _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+        step_start: 0
+        step_end: null
+      torch_memory:
+        _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+        trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+        stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+  forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+  forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+  ulysses_sequence_parallel_size: 1
+  grad_clip: 1.0
+reward_model:
+  enable: false
+  enable_resource_pool: false
+  n_gpus_per_node: 0
+  nnodes: 0
+  strategy: fsdp
+  model:
+    input_tokenizer: ${actor_rollout_ref.model.path}
+    path: ~/models/FsfairX-LLaMA3-RM-v0.1
+    external_lib: ${actor_rollout_ref.model.external_lib}
+    trust_remote_code: false
+    use_shm: false
+    use_remove_padding: false
+    use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+  micro_batch_size: null
+  micro_batch_size_per_gpu: null
+  max_length: null
+  use_dynamic_bsz: ${critic.use_dynamic_bsz}
+  forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+  reward_manager: naive
+  launch_reward_fn_async: false
+  sandbox_fusion:
+    url: null
+    max_concurrent: 64
+    memory_limit_mb: 1024
+  profiler:
+    _target_: verl.utils.profiler.ProfilerConfig
+    tool: ${oc.select:global_profiler.tool,null}
+    enable: false
+    all_ranks: false
+    ranks: []
+    save_path: ${oc.select:global_profiler.save_path,null}
+    tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+  ulysses_sequence_parallel_size: 1
+custom_reward_function:
+  path: null
+  name: compute_score
+algorithm:
+  _target_: verl.trainer.config.AlgoConfig
+  gamma: 1.0
+  lam: 1.0
+  adv_estimator: gae
+  norm_adv_by_std_in_grpo: true
+  use_kl_in_reward: false
+  kl_penalty: kl
+  kl_ctrl:
+    _target_: verl.trainer.config.KLControlConfig
+    type: fixed
+    kl_coef: 0.0
+    horizon: 10000
+    target_kl: 0.1
+  use_pf_ppo: false
+  pf_ppo:
+    reweight_method: pow
+    weight_pow: 2.0
+  high_level_gamma: 0.95
+  bi_level_gae: false
+  zero_task_advantage: false
+  soft_advantage_reweight: false
+trainer:
+  balance_batch: true
+  total_epochs: 30
+  total_training_steps: 200
+  project_name: ragen
+  experiment_name: rubikscube2_withthink_sas
+  logger:
+  - console
+  - wandb
+  log_val_generations: 0
+  rollout_data_dir: null
+  validation_data_dir: null
+  nnodes: 1
+  n_gpus_per_node: 8
+  save_freq: -1
+  esi_redundant_time: 0
+  resume_mode: auto
+  resume_from_path: null
+  val_before_train: true
+  val_only: false
+  test_freq: 10
+  critic_warmup: 0
+  default_hdfs_dir: null
+  del_local_ckpt_after_load: false
+  default_local_dir: checkpoints/${trainer.project_name}/${trainer.experiment_name}
+  max_actor_ckpt_to_keep: 1
+  max_critic_ckpt_to_keep: 1
+  ray_wait_register_center_timeout: 300
+  device: cuda
+  use_legacy_worker_impl: auto
+  local_log_dir: results/
+  validation_steps: 1
+  generations_to_log_to_wandb:
+    val: 20
+  log_group_rv_table: false
+  gradient_analysis_mode: false
+  gradient_analysis_every: 50
+  gradient_analysis_env_groups: null
+  gradient_analysis_group_size: null
+  gradient_analysis_log_prefilter: false
+  gradient_analysis_only: false
+  exit_after_gradient_analysis: false
+global_profiler:
+  _target_: verl.utils.profiler.ProfilerConfig
+  tool: null
+  steps: null
+  profile_continuous_steps: false
+  save_path: outputs/profile
+  global_tool_config:
+    nsys:
+      _target_: verl.utils.profiler.config.NsightToolConfig
+      discrete: false
+      controller_nsight_options:
+        trace: cuda,nvtx,cublas,ucx
+        cuda-memory-usage: 'true'
+        cuda-graph-trace: graph
+      worker_nsight_options:
+        trace: cuda,nvtx,cublas,ucx
+        cuda-memory-usage: 'true'
+        cuda-graph-trace: graph
+        capture-range: cudaProfilerApi
+        capture-range-end: null
+        kill: none
+    torch_memory:
+      trace_alloc_max_entries: 100000
+      stack_depth: 32
+      context: all
+      stacks: all
+      kw_args: {}
+ray_kwargs:
+  ray_init:
+    num_cpus: null
+  timeline_json_file: null
+custom_envs:
+  SimpleSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 20
+    env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+      \ when reasoning:\n1. First compare the box position with the target position;\
+      \ the useful push directions are usually the directions that reduce their row/column\
+      \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+      \ push direction. A move that only repositions the player can be useful if it\
+      \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+      \ dead end unless that square is the target or clearly on the only path to the\
+      \ target.\n4. Prefer short plans that move the single box steadily toward the\
+      \ target; avoid wandering moves that do not improve player position or box position.\n\
+      5. If the box and target are aligned in the same row or column, try to keep\
+      \ the box on that line and push along it.\n6. If they are not aligned, first\
+      \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+      7. Check that after each push, the player can still reach the next required\
+      \ pushing side of the box.\n8. Output only the required XML-like format and\
+      \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+      \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+      \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+      \ pull a box. \nThe answer should be a sequence of actions, like <answer>Right\
+      \ || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 2
+      max_steps: 100
+  LargerSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+      \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+      \ you can push it by moving in the same direction. \nYou cannot push a box through\
+      \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+      \ like <answer>Right || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 8
+      dim_y: 8
+      num_boxes: 2
+      max_steps: 100
+      search_depth: 10
+  SokobanDifferentGridVocab:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+      \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+      \ you can push it by moving in the same direction. \nYou cannot push a box through\
+      \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+      \ like <answer>Right || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      search_depth: 30
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      grid_lookup:
+        0: W
+        1: .
+        2: G
+        3: C
+        4: B
+        5: A
+        6: '@'
+      grid_vocab:
+        W: wall
+        .: empty
+        G: target
+        C: box on target
+        B: box
+        A: player
+        '@': player on target
+  CoordSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 20
+    env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+      \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+      \ the zero-indexed coordinates of the player, each box, and each target. \n\
+      Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+      \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+      \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+      \ pull a box.\nThe answer should be a sequence of actions, like <answer>Right\
+      \ || Right || Up</answer>.\n"
+    max_tokens: 120
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 2
+      max_steps: 100
+      observation_format: grid_coord
+  VisualSimpleSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: You are solving the Sokoban puzzle. You are the player and you
+      need to push all boxes to targets. When you are right next to a box, you can
+      push it by moving in the same direction. You cannot push a box through a wall,
+      and you cannot pull a box. The answer should be a sequence of actions, like
+      <answer>Right || Right || Up</answer>
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      render_mode: rgb_array
+  Alfworld:
+    env_type: alfworld
+    max_actions_per_traj: 50
+    parallel_friendly: false
+    max_workers: 1
+    env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+      Complete household tasks by navigating and interacting with objects.
+
+
+      You should first reason step-by-step about the current situation. This reasoning
+      process MUST be enclosed within <think> </think> tags.
+
+      Once you''ve finished your reasoning, you should choose an admissible action
+      for current step and present it within <answer>...</answer> tags.
+
+      '
+    max_tokens: 512
+    env_config:
+      eval_dataset: eval_in_distribution
+  AlfworldOOD:
+    env_type: alfworld
+    max_actions_per_traj: 50
+    parallel_friendly: false
+    max_workers: 1
+    env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+      Complete household tasks by navigating and interacting with objects.
+
+
+      You should first reason step-by-step about the current situation. This reasoning
+      process MUST be enclosed within <think> </think> tags.
+
+      Once you''ve finished your reasoning, you should choose an admissible action
+      for current step and present it within <answer>...</answer> tags.
+
+      '
+    max_tokens: 512
+    env_config:
+      eval_dataset: eval_out_of_distribution
+  Countdown:
+    env_type: countdown
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving the Countdown puzzle. You should use the num
+      list to create an equation that equals the target. Example answer format: <think>
+      To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+      = 4. So the answer is 2 + 5 - 3 = 4. </think><answer>2 + 5 - 3</answer>'
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config: null
+  Bandit:
+    env_type: bandit
+    max_actions_per_traj: 1
+    env_instruction: ''
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      split: train
+  BanditTest:
+    env_type: bandit
+    max_actions_per_traj: 1
+    env_instruction: ''
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      split: test
+  DeepCoder:
+    env_type: deepcoder
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving a coding task. Provide a complete Python function
+      solution only. Format: <answer>...</answer>'
+    max_tokens: 8000
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 1
+  FrozenLake:
+    env_type: frozen_lake
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+      go to the target. You may move to the unintended direction due to the slippery
+      ice. Example answer format: <think>To forbid the hole and go to the target,
+      I should go left then go up.</think><answer>Left || Up</answer>'
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      success_rate: 0.8
+  CoordFrozenLake:
+    env_type: frozen_lake
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+      both a symbol grid and zero-indexed coordinates for the start, goal, player,
+      and any holes.
+
+      Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+      (5, 5).
+
+      Beware that the ice is slippery, so the agent might slide and end up in an unintended
+      tile.
+
+      Respond with a sequence of actions such as <answer>Left || Up || Up</answer>.
+
+      '
+    max_tokens: 120
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      observation_format: grid_coord
+      success_rate: 0.8
+  MetamathQA:
+    env_type: metamathqa
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving Math problems. '
+    max_tokens: 100
+    env_config: null
+  WebShopFull:
+    env_type: webshop
+    max_actions_per_traj: 15
+    env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+      environment.
+    max_tokens: 200
+    env_config:
+      dataset: full
+  WebShop:
+    env_type: webshop
+    max_actions_per_traj: 9
+    env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+      a product that close to the production description. You need to search, read
+      the search results, pick a product, choose the size and color and buy. You should
+      only choose action from the available actions list provided later.  Example
+      process: I need a gingko light and 20x20 pillow cover that is hand painted.
+      First search[gingko light 20x20 pillow cover hand painted], answer format: <answer>search[blanket
+      with fleece throw]</answer>. Valid answer is search[<keywords>] or click[<clickable>].'
+    max_tokens: 200
+    env_config:
+      dataset: small
+  Lean:
+    env_type: lean
+    max_actions_per_traj: 30
+    env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+      propose a sequence of tactics that completes the proof. Think step by step about
+      which tactics to apply next. Provide tactics separated by '||', for example
+      <answer>intro || simp || rfl</answer>.
+    max_tokens: 512
+    parallel_friendly: true
+    max_workers: 32
+    env_config: null
+  SimpleSudoku:
+    env_type: sudoku
+    max_actions_per_traj: 20
+    env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+      row, column, and 2x2 box contains the numbers 1-4 without repetition.
+
+      Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+      shown as dots (.).
+
+      Place numbers one at a time using the format, for example: <answer>place 1 at
+      row 2 col 3</answer> or <answer>1,2,3</answer>
+
+      The environment will provide feedback on valid/invalid moves and show conflicts
+      if any occur.
+
+      '
+    max_tokens: 150
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      grid_size: 4
+      difficulty: easy
+      render_format: with_feedback
+      show_conflicts: false
+      show_valid_numbers: false
+      max_steps: 20
+  MediumSudoku:
+    env_type: sudoku
+    max_actions_per_traj: 30
+    env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+      row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+      Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+      shown as dots (.).
+
+      Place numbers one at a time using the format: <answer>place 5 at row 2 col 3</answer>
+      or <answer>2,3,5</answer>
+
+      The environment will provide feedback on valid/invalid moves and show conflicts
+      if any occur.
+
+      '
+    max_tokens: 150
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      grid_size: 9
+      difficulty: medium
+      render_format: with_feedback
+      show_conflicts: true
+      show_valid_numbers: true
+      max_steps: 81
+  SearchQA:
+    env_type: search
+    max_actions_per_traj: 10
+    env_instruction: "You are a search agent answering questions by searching for\
+      \ information.\nUse search[your query] to find relevant documents, and finish[your\
+      \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+      \ about the current situation. This reasoning process MUST be enclosed within\
+      \ <think> </think> tags.\nThen provide your action within <answer>...</answer>\
+      \ tags.\n\nExamples:\n  <think>I need to find information about Ben Platt's\
+      \ father.</think><answer>search[Ben Platt father parent]</answer>\n  <think>Based\
+      \ on the search results, Ben Platt's father is Henry Platt.</think><answer>finish[Henry\
+      \ Platt]</answer>\n"
+    max_tokens: 300
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 10
+      max_search_results: 5
+  SearchQAMock:
+    env_type: search
+    max_actions_per_traj: 10
+    env_instruction: "You are a search agent answering questions by searching for\
+      \ information.\nUse search[your query] to find relevant documents, and finish[your\
+      \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+      \ about the current situation. This reasoning process MUST be enclosed within\
+      \ <think> </think> tags.\nThen provide your action within <answer>...</answer>\
+      \ tags.\n\nExamples:\n  <think>I need to find information about Ben Platt's\
+      \ father.</think><answer>search[Ben Platt father parent]</answer>\n  <think>Based\
+      \ on the search results, Ben Platt's father is Henry Platt.</think><answer>finish[Henry\
+      \ Platt]</answer>\n"
+    max_tokens: 300
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 10
+      max_search_results: 5
+      mock_mode: true
+  game_2048:
+    env_type: game_2048
+    max_actions_per_traj: 700
+    env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+      by sliding Up, Right, Down, or Left.
+
+      If a move is invalid (no tiles move), a small penalty is applied. Respond with
+      a single action.
+
+      Example: <answer>Up</answer>
+
+      '
+    max_tokens: 8192
+    env_config: null
+  rubikscube:
+    env_type: rubikscube
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+      is to restore the cube so that each of the faces consists of a single, unique
+      color.
+
+      Available actions use standard Singmaster notation for face rotations: U, U'',
+      D, D'', L, L'', R, R'', F, F'', B, B''.
+
+      - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+      - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+      prime ('') means 90° counter-clockwise (e.g., "R''").
+
+      Respond with a sequence of actions separated by "||".
+
+      Example: <answer>U</answer>
+
+      '
+    max_tokens: 96
+    env_config:
+      scramble_depth: 2
+      max_steps: 10
+      render_mode: text
+system:
+  CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+  train: 10000
+  val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_sas
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+  rank: 0
+  alpha: 64
+  target_modules: all-linear
+agent_proxy:
+  context_window_mode: full
+  max_context_window: 5
+  batch_adjust_mode: copy
+  max_turn: 25
+  action_sep: '||'
+  max_actions_per_turn: 4
+  use_turn_scores: false
+  enable_think: true
+  reward_normalization:
+    grouping: state
+    method: identity
+collapse_detection:
+  compute_freq: 5
+  micro_batch_size: 128
+  first_turn_enabled: true
+  multi_turn_enabled: true
+  num_samples: 64
+es_manager:
+  format_penalty: -0.1
+  train:
+    env_groups: 8
+    group_size: 16
+    env_configs:
+      tags:
+      - rubikscube
+      n_groups:
+      - 8
+  val:
+    env_groups: 512
+    group_size: 1
+    env_configs:
+      tags:
+      - rubikscube
+      n_groups:
+      - 512
+ctx_manager:
+  generation:
+    gen_config:
+      response_length: ${actor_rollout_ref.rollout.response_length}
+      temperature: ${actor_rollout_ref.rollout.temperature}
+      top_p: ${actor_rollout_ref.rollout.top_p}
+      top_k: ${actor_rollout_ref.rollout.top_k}
+      kwargs: null

outputs/2026-06-09/02-32-07/.hydra/hydra.yaml

@@ -0,0 +1,177 @@
+hydra:
+  run:
+    dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+  sweep:
+    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task:
+    - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+    - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+    - actor_rollout_ref.rollout.rollout_filter_value=0.9
+    - trainer.total_training_steps=200
+    - trainer.n_gpus_per_node=8
+    - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_sas
+    - custom_envs.rubikscube.env_config.scramble_depth=2
+    - trainer.experiment_name=rubikscube2_withthink_sas
+  job:
+    name: train
+    chdir: null
+    override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=2,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_sas,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.experiment_name=rubikscube2_withthink_sas,trainer.n_gpus_per_node=8,trainer.total_training_steps=200
+    id: ???
+    num: ???
+    config_name: _10_rubikscube
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /mnt/general/wanghy/RAGEN_v2
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /mnt/general/wanghy/RAGEN_v2/config
+      schema: file
+      provider: main
+    - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-09/02-32-07
+    choices:
+      reward_model: dp_reward_model
+      critic: dp_critic
+      critic/../engine@critic.model.fsdp_config: fsdp
+      critic/../optim@critic.optim: fsdp
+      model@actor_rollout_ref.model: hf_model
+      rollout@actor_rollout_ref.rollout: rollout
+      ref@actor_rollout_ref.ref: dp_ref
+      ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+      data: legacy_data
+      actor@actor_rollout_ref.actor: dp_actor
+      actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+      actor/../optim@actor_rollout_ref.actor.optim: fsdp
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

outputs/2026-06-09/02-32-07/.hydra/overrides.yaml

@@ -0,0 +1,8 @@
+- system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- trainer.n_gpus_per_node=8
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_sas
+- custom_envs.rubikscube.env_config.scramble_depth=2
+- trainer.experiment_name=rubikscube2_withthink_sas

outputs/2026-06-09/05-39-33/.hydra/config.yaml

@@ -0,0 +1,1003 @@
+actor_rollout_ref:
+  actor:
+    optim:
+      _target_: verl.workers.config.FSDPOptimizerConfig
+      lr: 1.0e-06
+      lr_warmup_steps_ratio: 0.0
+      total_training_steps: -1
+      weight_decay: 0.01
+      lr_warmup_steps: -1
+      betas:
+      - 0.9
+      - 0.999
+      clip_grad: 1.0
+      min_lr_ratio: 0.0
+      num_cycles: 0.5
+      warmup_style: constant
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    _target_: verl.workers.config.FSDPActorConfig
+    strategy: fsdp
+    ppo_mini_batch_size: ${ppo_mini_batch_size}
+    ppo_micro_batch_size: null
+    ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+    use_dynamic_bsz: false
+    ppo_max_token_len_per_gpu: 16384
+    clip_ratio: 0.2
+    clip_ratio_low: 0.2
+    clip_ratio_high: 0.28
+    freeze_vision_tower: false
+    policy_loss:
+      _target_: verl.workers.config.PolicyLossConfig
+      loss_mode: vanilla
+      clip_cov_ratio: 0.0002
+      clip_cov_lb: 1.0
+      clip_cov_ub: 5.0
+      kl_cov_ratio: 0.0002
+      ppo_kl_coef: 0.1
+    clip_ratio_c: 3.0
+    loss_agg_mode: token-mean
+    entropy_coeff: 0.001
+    tis_imp_ratio_cap: -1
+    use_kl_loss: false
+    use_torch_compile: true
+    kl_loss_coef: 0.0
+    kl_loss_type: kl
+    ppo_epochs: 1
+    shuffle: false
+    checkpoint:
+      _target_: verl.trainer.config.CheckpointConfig
+      save_contents:
+      - model
+      - optimizer
+      - extra
+      load_contents: ${.save_contents}
+      async_save: false
+    use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: false
+      all_ranks: false
+      ranks: []
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config:
+        nsys:
+          _target_: verl.utils.profiler.config.NsightToolConfig
+          discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+        npu:
+          _target_: verl.utils.profiler.config.NPUToolConfig
+          contents: []
+          level: level1
+          analysis: true
+          discrete: false
+        torch:
+          _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+          step_start: 0
+          step_end: null
+        torch_memory:
+          _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+          trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+          stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+    grad_clip: 1.0
+    ulysses_sequence_parallel_size: 1
+    entropy_from_logits_with_chunking: false
+    entropy_checkpointing: false
+    use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+    use_ref: true
+    grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+    filter_loss_scaling: none
+  ref:
+    strategy: ${actor_rollout_ref.actor.strategy}
+    use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+    log_prob_micro_batch_size: null
+    log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+    log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+    log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: false
+      all_ranks: false
+      ranks: []
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config:
+        nsys:
+          _target_: verl.utils.profiler.config.NsightToolConfig
+          discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+        npu:
+          _target_: verl.utils.profiler.config.NPUToolConfig
+          contents: []
+          level: level1
+          analysis: true
+          discrete: false
+        torch:
+          _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+          step_start: 0
+          step_end: null
+        torch_memory:
+          _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+          trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+          stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    model: null
+    ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+    entropy_from_logits_with_chunking: false
+    entropy_checkpointing: false
+  rollout:
+    _target_: verl.workers.config.RolloutConfig
+    name: vllm
+    mode: sync
+    temperature: 1
+    top_k: -1
+    top_p: 1
+    prompt_length: 1
+    response_length: 500
+    dtype: bfloat16
+    gpu_memory_utilization: 0.7
+    ignore_eos: false
+    enforce_eager: true
+    cudagraph_capture_sizes: null
+    free_cache_engine: true
+    tensor_model_parallel_size: 1
+    data_parallel_size: 1
+    expert_parallel_size: 1
+    max_num_batched_tokens: 16384
+    max_model_len: 16384
+    max_num_seqs: 1024
+    enable_chunked_prefill: true
+    enable_prefix_caching: true
+    load_format: auto
+    log_prob_micro_batch_size: null
+    log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+    log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+    log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+    disable_log_stats: true
+    do_sample: true
+    'n': 1
+    over_sample_rate: 0
+    multi_stage_wake_up: false
+    engine_kwargs:
+      vllm: {}
+      sglang: {}
+    val_kwargs:
+      _target_: verl.workers.config.SamplingConfig
+      top_k: -1
+      top_p: 1.0
+      temperature: 0.5
+      'n': 1
+      do_sample: true
+    multi_turn:
+      _target_: verl.workers.config.MultiTurnConfig
+      enable: false
+      max_assistant_turns: null
+      tool_config_path: null
+      max_user_turns: null
+      max_parallel_calls: 1
+      max_tool_response_length: 256
+      tool_response_truncate_side: middle
+      interaction_config_path: null
+      use_inference_chat_template: false
+      tokenization_sanity_check_mode: strict
+      format: hermes
+      num_repeat_rollouts: null
+    calculate_log_probs: false
+    agent:
+      _target_: verl.workers.config.AgentLoopConfig
+      num_workers: 8
+      agent_loop_config_path: null
+      custom_async_server:
+        _target_: verl.workers.config.CustomAsyncServerConfig
+        path: null
+        name: null
+    update_weights_bucket_megabytes: 512
+    trace:
+      _target_: verl.workers.config.TraceConfig
+      backend: null
+      token2text: false
+    skip_rollout: false
+    skip_dump_dir: /tmp/rollout_dump
+    skip_tokenizer_init: true
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+      all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+      ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+    layered_summon: false
+    rollout_filter_value: 0.9
+    rollout_filter_strategy: top_p
+    rollout_filter_type: largest
+    rollout_filter_include_zero: true
+    rollout_filter_top_p_prob_mode: linear
+    rollout_filter_selection_eps: 0.01
+    rollout_filter_empty_stop_steps: 5
+    rollout_filter_metric: reward_variance
+    gradient_analysis_num_buckets: 6
+    gradient_analysis_bucket_mode: quantile
+  model:
+    _target_: verl.workers.config.HFModelConfig
+    path: ${model_path}
+    hf_config_path: null
+    tokenizer_path: null
+    use_shm: false
+    trust_remote_code: false
+    custom_chat_template: null
+    external_lib: null
+    override_config: {}
+    enable_gradient_checkpointing: true
+    enable_activation_offload: false
+    use_remove_padding: false
+    lora_rank: ${lora.rank}
+    lora_alpha: ${lora.alpha}
+    target_modules: ${lora.target_modules}
+    exclude_modules: null
+    use_liger: false
+    use_fused_kernels: false
+    fused_kernel_options:
+      impl_backend: torch
+  hybrid_engine: true
+  nccl_timeout: 600
+data:
+  tokenizer: null
+  use_shm: false
+  train_files: ~/data/rlhf/gsm8k/train.parquet
+  val_files: ~/data/rlhf/gsm8k/test.parquet
+  prompt_key: prompt
+  reward_fn_key: data_source
+  max_prompt_length: null
+  max_response_length: null
+  train_batch_size: null
+  val_batch_size: null
+  return_raw_input_ids: false
+  return_raw_chat: false
+  return_full_prompt: false
+  shuffle: true
+  dataloader_num_workers: 8
+  validation_shuffle: false
+  filter_overlong_prompts: false
+  filter_overlong_prompts_workers: 1
+  truncation: error
+  image_key: images
+  video_key: videos
+  trust_remote_code: false
+  custom_cls:
+    path: null
+    name: null
+  return_multi_modal_inputs: true
+  sampler:
+    class_path: null
+    class_name: null
+  datagen:
+    path: null
+    name: null
+  apply_chat_template_kwargs: {}
+critic:
+  optim:
+    _target_: verl.workers.config.FSDPOptimizerConfig
+    lr: 1.0e-05
+    lr_warmup_steps_ratio: 0.0
+    total_training_steps: -1
+    weight_decay: 0.01
+    lr_warmup_steps: -1
+    betas:
+    - 0.9
+    - 0.999
+    clip_grad: 1.0
+    min_lr_ratio: 0.0
+    num_cycles: 0.5
+    warmup_style: constant
+  model:
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    path: ${model_path}
+    tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+    override_config: {}
+    external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+    trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+    _target_: verl.workers.config.FSDPCriticModelCfg
+    use_shm: false
+    enable_gradient_checkpointing: true
+    enable_activation_offload: false
+    use_remove_padding: false
+    lora_rank: ${lora.rank}
+    lora_alpha: ${lora.alpha}
+    target_modules: ${lora.target_modules}
+  _target_: verl.workers.config.FSDPCriticConfig
+  rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+  strategy: fsdp
+  enable: null
+  ppo_mini_batch_size: ${ppo_mini_batch_size}
+  ppo_micro_batch_size: null
+  ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+  use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+  ppo_max_token_len_per_gpu: 32768
+  forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+  ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+  shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+  cliprange_value: 0.5
+  loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+  checkpoint:
+    _target_: verl.trainer.config.CheckpointConfig
+    save_contents:
+    - model
+    - optimizer
+    - extra
+    load_contents: ${.save_contents}
+    async_save: false
+  profiler:
+    _target_: verl.utils.profiler.ProfilerConfig
+    tool: ${oc.select:global_profiler.tool,null}
+    enable: false
+    all_ranks: false
+    ranks: []
+    save_path: ${oc.select:global_profiler.save_path,null}
+    tool_config:
+      nsys:
+        _target_: verl.utils.profiler.config.NsightToolConfig
+        discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+      npu:
+        _target_: verl.utils.profiler.config.NPUToolConfig
+        contents: []
+        level: level1
+        analysis: true
+        discrete: false
+      torch:
+        _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+        step_start: 0
+        step_end: null
+      torch_memory:
+        _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+        trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+        stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+  forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+  forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+  ulysses_sequence_parallel_size: 1
+  grad_clip: 1.0
+reward_model:
+  enable: false
+  enable_resource_pool: false
+  n_gpus_per_node: 0
+  nnodes: 0
+  strategy: fsdp
+  model:
+    input_tokenizer: ${actor_rollout_ref.model.path}
+    path: ~/models/FsfairX-LLaMA3-RM-v0.1
+    external_lib: ${actor_rollout_ref.model.external_lib}
+    trust_remote_code: false
+    use_shm: false
+    use_remove_padding: false
+    use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+  micro_batch_size: null
+  micro_batch_size_per_gpu: null
+  max_length: null
+  use_dynamic_bsz: ${critic.use_dynamic_bsz}
+  forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+  reward_manager: naive
+  launch_reward_fn_async: false
+  sandbox_fusion:
+    url: null
+    max_concurrent: 64
+    memory_limit_mb: 1024
+  profiler:
+    _target_: verl.utils.profiler.ProfilerConfig
+    tool: ${oc.select:global_profiler.tool,null}
+    enable: false
+    all_ranks: false
+    ranks: []
+    save_path: ${oc.select:global_profiler.save_path,null}
+    tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+  ulysses_sequence_parallel_size: 1
+custom_reward_function:
+  path: null
+  name: compute_score
+algorithm:
+  _target_: verl.trainer.config.AlgoConfig
+  gamma: 1.0
+  lam: 1.0
+  adv_estimator: gae
+  norm_adv_by_std_in_grpo: true
+  use_kl_in_reward: false
+  kl_penalty: kl
+  kl_ctrl:
+    _target_: verl.trainer.config.KLControlConfig
+    type: fixed
+    kl_coef: 0.0
+    horizon: 10000
+    target_kl: 0.1
+  use_pf_ppo: false
+  pf_ppo:
+    reweight_method: pow
+    weight_pow: 2.0
+  high_level_gamma: 0.95
+  bi_level_gae: false
+  zero_task_advantage: false
+  soft_advantage_reweight: false
+trainer:
+  balance_batch: true
+  total_epochs: 30
+  total_training_steps: 200
+  project_name: ragen
+  experiment_name: rubikscube3_withthink_sas
+  logger:
+  - console
+  - wandb
+  log_val_generations: 0
+  rollout_data_dir: null
+  validation_data_dir: null
+  nnodes: 1
+  n_gpus_per_node: 8
+  save_freq: -1
+  esi_redundant_time: 0
+  resume_mode: auto
+  resume_from_path: null
+  val_before_train: true
+  val_only: false
+  test_freq: 10
+  critic_warmup: 0
+  default_hdfs_dir: null
+  del_local_ckpt_after_load: false
+  default_local_dir: checkpoints/${trainer.project_name}/${trainer.experiment_name}
+  max_actor_ckpt_to_keep: 1
+  max_critic_ckpt_to_keep: 1
+  ray_wait_register_center_timeout: 300
+  device: cuda
+  use_legacy_worker_impl: auto
+  local_log_dir: results/
+  validation_steps: 1
+  generations_to_log_to_wandb:
+    val: 20
+  log_group_rv_table: false
+  gradient_analysis_mode: false
+  gradient_analysis_every: 50
+  gradient_analysis_env_groups: null
+  gradient_analysis_group_size: null
+  gradient_analysis_log_prefilter: false
+  gradient_analysis_only: false
+  exit_after_gradient_analysis: false
+global_profiler:
+  _target_: verl.utils.profiler.ProfilerConfig
+  tool: null
+  steps: null
+  profile_continuous_steps: false
+  save_path: outputs/profile
+  global_tool_config:
+    nsys:
+      _target_: verl.utils.profiler.config.NsightToolConfig
+      discrete: false
+      controller_nsight_options:
+        trace: cuda,nvtx,cublas,ucx
+        cuda-memory-usage: 'true'
+        cuda-graph-trace: graph
+      worker_nsight_options:
+        trace: cuda,nvtx,cublas,ucx
+        cuda-memory-usage: 'true'
+        cuda-graph-trace: graph
+        capture-range: cudaProfilerApi
+        capture-range-end: null
+        kill: none
+    torch_memory:
+      trace_alloc_max_entries: 100000
+      stack_depth: 32
+      context: all
+      stacks: all
+      kw_args: {}
+ray_kwargs:
+  ray_init:
+    num_cpus: null
+  timeline_json_file: null
+custom_envs:
+  SimpleSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 20
+    env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+      \ when reasoning:\n1. First compare the box position with the target position;\
+      \ the useful push directions are usually the directions that reduce their row/column\
+      \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+      \ push direction. A move that only repositions the player can be useful if it\
+      \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+      \ dead end unless that square is the target or clearly on the only path to the\
+      \ target.\n4. Prefer short plans that move the single box steadily toward the\
+      \ target; avoid wandering moves that do not improve player position or box position.\n\
+      5. If the box and target are aligned in the same row or column, try to keep\
+      \ the box on that line and push along it.\n6. If they are not aligned, first\
+      \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+      7. Check that after each push, the player can still reach the next required\
+      \ pushing side of the box.\n8. Output only the required XML-like format and\
+      \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+      \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+      \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+      \ pull a box. \nThe answer should be a sequence of actions, like <answer>Right\
+      \ || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 2
+      max_steps: 100
+  LargerSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+      \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+      \ you can push it by moving in the same direction. \nYou cannot push a box through\
+      \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+      \ like <answer>Right || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 8
+      dim_y: 8
+      num_boxes: 2
+      max_steps: 100
+      search_depth: 10
+  SokobanDifferentGridVocab:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+      \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+      \ you can push it by moving in the same direction. \nYou cannot push a box through\
+      \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+      \ like <answer>Right || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      search_depth: 30
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      grid_lookup:
+        0: W
+        1: .
+        2: G
+        3: C
+        4: B
+        5: A
+        6: '@'
+      grid_vocab:
+        W: wall
+        .: empty
+        G: target
+        C: box on target
+        B: box
+        A: player
+        '@': player on target
+  CoordSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 20
+    env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+      \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+      \ the zero-indexed coordinates of the player, each box, and each target. \n\
+      Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+      \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+      \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+      \ pull a box.\nThe answer should be a sequence of actions, like <answer>Right\
+      \ || Right || Up</answer>.\n"
+    max_tokens: 120
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 2
+      max_steps: 100
+      observation_format: grid_coord
+  VisualSimpleSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: You are solving the Sokoban puzzle. You are the player and you
+      need to push all boxes to targets. When you are right next to a box, you can
+      push it by moving in the same direction. You cannot push a box through a wall,
+      and you cannot pull a box. The answer should be a sequence of actions, like
+      <answer>Right || Right || Up</answer>
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      render_mode: rgb_array
+  Alfworld:
+    env_type: alfworld
+    max_actions_per_traj: 50
+    parallel_friendly: false
+    max_workers: 1
+    env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+      Complete household tasks by navigating and interacting with objects.
+
+
+      You should first reason step-by-step about the current situation. This reasoning
+      process MUST be enclosed within <think> </think> tags.
+
+      Once you''ve finished your reasoning, you should choose an admissible action
+      for current step and present it within <answer>...</answer> tags.
+
+      '
+    max_tokens: 512
+    env_config:
+      eval_dataset: eval_in_distribution
+  AlfworldOOD:
+    env_type: alfworld
+    max_actions_per_traj: 50
+    parallel_friendly: false
+    max_workers: 1
+    env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+      Complete household tasks by navigating and interacting with objects.
+
+
+      You should first reason step-by-step about the current situation. This reasoning
+      process MUST be enclosed within <think> </think> tags.
+
+      Once you''ve finished your reasoning, you should choose an admissible action
+      for current step and present it within <answer>...</answer> tags.
+
+      '
+    max_tokens: 512
+    env_config:
+      eval_dataset: eval_out_of_distribution
+  Countdown:
+    env_type: countdown
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving the Countdown puzzle. You should use the num
+      list to create an equation that equals the target. Example answer format: <think>
+      To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+      = 4. So the answer is 2 + 5 - 3 = 4. </think><answer>2 + 5 - 3</answer>'
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config: null
+  Bandit:
+    env_type: bandit
+    max_actions_per_traj: 1
+    env_instruction: ''
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      split: train
+  BanditTest:
+    env_type: bandit
+    max_actions_per_traj: 1
+    env_instruction: ''
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      split: test
+  DeepCoder:
+    env_type: deepcoder
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving a coding task. Provide a complete Python function
+      solution only. Format: <answer>...</answer>'
+    max_tokens: 8000
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 1
+  FrozenLake:
+    env_type: frozen_lake
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+      go to the target. You may move to the unintended direction due to the slippery
+      ice. Example answer format: <think>To forbid the hole and go to the target,
+      I should go left then go up.</think><answer>Left || Up</answer>'
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      success_rate: 0.8
+  CoordFrozenLake:
+    env_type: frozen_lake
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+      both a symbol grid and zero-indexed coordinates for the start, goal, player,
+      and any holes.
+
+      Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+      (5, 5).
+
+      Beware that the ice is slippery, so the agent might slide and end up in an unintended
+      tile.
+
+      Respond with a sequence of actions such as <answer>Left || Up || Up</answer>.
+
+      '
+    max_tokens: 120
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      observation_format: grid_coord
+      success_rate: 0.8
+  MetamathQA:
+    env_type: metamathqa
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving Math problems. '
+    max_tokens: 100
+    env_config: null
+  WebShopFull:
+    env_type: webshop
+    max_actions_per_traj: 15
+    env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+      environment.
+    max_tokens: 200
+    env_config:
+      dataset: full
+  WebShop:
+    env_type: webshop
+    max_actions_per_traj: 9
+    env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+      a product that close to the production description. You need to search, read
+      the search results, pick a product, choose the size and color and buy. You should
+      only choose action from the available actions list provided later.  Example
+      process: I need a gingko light and 20x20 pillow cover that is hand painted.
+      First search[gingko light 20x20 pillow cover hand painted], answer format: <answer>search[blanket
+      with fleece throw]</answer>. Valid answer is search[<keywords>] or click[<clickable>].'
+    max_tokens: 200
+    env_config:
+      dataset: small
+  Lean:
+    env_type: lean
+    max_actions_per_traj: 30
+    env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+      propose a sequence of tactics that completes the proof. Think step by step about
+      which tactics to apply next. Provide tactics separated by '||', for example
+      <answer>intro || simp || rfl</answer>.
+    max_tokens: 512
+    parallel_friendly: true
+    max_workers: 32
+    env_config: null
+  SimpleSudoku:
+    env_type: sudoku
+    max_actions_per_traj: 20
+    env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+      row, column, and 2x2 box contains the numbers 1-4 without repetition.
+
+      Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+      shown as dots (.).
+
+      Place numbers one at a time using the format, for example: <answer>place 1 at
+      row 2 col 3</answer> or <answer>1,2,3</answer>
+
+      The environment will provide feedback on valid/invalid moves and show conflicts
+      if any occur.
+
+      '
+    max_tokens: 150
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      grid_size: 4
+      difficulty: easy
+      render_format: with_feedback
+      show_conflicts: false
+      show_valid_numbers: false
+      max_steps: 20
+  MediumSudoku:
+    env_type: sudoku
+    max_actions_per_traj: 30
+    env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+      row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+      Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+      shown as dots (.).
+
+      Place numbers one at a time using the format: <answer>place 5 at row 2 col 3</answer>
+      or <answer>2,3,5</answer>
+
+      The environment will provide feedback on valid/invalid moves and show conflicts
+      if any occur.
+
+      '
+    max_tokens: 150
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      grid_size: 9
+      difficulty: medium
+      render_format: with_feedback
+      show_conflicts: true
+      show_valid_numbers: true
+      max_steps: 81
+  SearchQA:
+    env_type: search
+    max_actions_per_traj: 10
+    env_instruction: "You are a search agent answering questions by searching for\
+      \ information.\nUse search[your query] to find relevant documents, and finish[your\
+      \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+      \ about the current situation. This reasoning process MUST be enclosed within\
+      \ <think> </think> tags.\nThen provide your action within <answer>...</answer>\
+      \ tags.\n\nExamples:\n  <think>I need to find information about Ben Platt's\
+      \ father.</think><answer>search[Ben Platt father parent]</answer>\n  <think>Based\
+      \ on the search results, Ben Platt's father is Henry Platt.</think><answer>finish[Henry\
+      \ Platt]</answer>\n"
+    max_tokens: 300
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 10
+      max_search_results: 5
+  SearchQAMock:
+    env_type: search
+    max_actions_per_traj: 10
+    env_instruction: "You are a search agent answering questions by searching for\
+      \ information.\nUse search[your query] to find relevant documents, and finish[your\
+      \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+      \ about the current situation. This reasoning process MUST be enclosed within\
+      \ <think> </think> tags.\nThen provide your action within <answer>...</answer>\
+      \ tags.\n\nExamples:\n  <think>I need to find information about Ben Platt's\
+      \ father.</think><answer>search[Ben Platt father parent]</answer>\n  <think>Based\
+      \ on the search results, Ben Platt's father is Henry Platt.</think><answer>finish[Henry\
+      \ Platt]</answer>\n"
+    max_tokens: 300
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 10
+      max_search_results: 5
+      mock_mode: true
+  game_2048:
+    env_type: game_2048
+    max_actions_per_traj: 700
+    env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+      by sliding Up, Right, Down, or Left.
+
+      If a move is invalid (no tiles move), a small penalty is applied. Respond with
+      a single action.
+
+      Example: <answer>Up</answer>
+
+      '
+    max_tokens: 8192
+    env_config: null
+  rubikscube:
+    env_type: rubikscube
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+      is to restore the cube so that each of the faces consists of a single, unique
+      color.
+
+      Available actions use standard Singmaster notation for face rotations: U, U'',
+      D, D'', L, L'', R, R'', F, F'', B, B''.
+
+      - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+      - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+      prime ('') means 90° counter-clockwise (e.g., "R''").
+
+      Respond with a sequence of actions separated by "||".
+
+      Example: <answer>U</answer>
+
+      '
+    max_tokens: 96
+    env_config:
+      scramble_depth: 3
+      max_steps: 10
+      render_mode: text
+system:
+  CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+  train: 10000
+  val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube3_withthink_sas
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+  rank: 0
+  alpha: 64
+  target_modules: all-linear
+agent_proxy:
+  context_window_mode: full
+  max_context_window: 5
+  batch_adjust_mode: copy
+  max_turn: 25
+  action_sep: '||'
+  max_actions_per_turn: 4
+  use_turn_scores: false
+  enable_think: true
+  reward_normalization:
+    grouping: state
+    method: identity
+collapse_detection:
+  compute_freq: 5
+  micro_batch_size: 128
+  first_turn_enabled: true
+  multi_turn_enabled: true
+  num_samples: 64
+es_manager:
+  format_penalty: -0.1
+  train:
+    env_groups: 8
+    group_size: 16
+    env_configs:
+      tags:
+      - rubikscube
+      n_groups:
+      - 8
+  val:
+    env_groups: 512
+    group_size: 1
+    env_configs:
+      tags:
+      - rubikscube
+      n_groups:
+      - 512
+ctx_manager:
+  generation:
+    gen_config:
+      response_length: ${actor_rollout_ref.rollout.response_length}
+      temperature: ${actor_rollout_ref.rollout.temperature}
+      top_p: ${actor_rollout_ref.rollout.top_p}
+      top_k: ${actor_rollout_ref.rollout.top_k}
+      kwargs: null

outputs/2026-06-09/13-00-35/.hydra/overrides.yaml

@@ -0,0 +1,8 @@
+- system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- trainer.n_gpus_per_node=8
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube3_withthink_sas
+- custom_envs.rubikscube.env_config.scramble_depth=3
+- trainer.experiment_name=rubikscube3_withthink_sas

outputs/2026-06-09/16-00-04/.hydra/config.yaml

@@ -0,0 +1,1003 @@
+actor_rollout_ref:
+  actor:
+    optim:
+      _target_: verl.workers.config.FSDPOptimizerConfig
+      lr: 1.0e-06
+      lr_warmup_steps_ratio: 0.0
+      total_training_steps: -1
+      weight_decay: 0.01
+      lr_warmup_steps: -1
+      betas:
+      - 0.9
+      - 0.999
+      clip_grad: 1.0
+      min_lr_ratio: 0.0
+      num_cycles: 0.5
+      warmup_style: constant
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    _target_: verl.workers.config.FSDPActorConfig
+    strategy: fsdp
+    ppo_mini_batch_size: ${ppo_mini_batch_size}
+    ppo_micro_batch_size: null
+    ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+    use_dynamic_bsz: false
+    ppo_max_token_len_per_gpu: 16384
+    clip_ratio: 0.2
+    clip_ratio_low: 0.2
+    clip_ratio_high: 0.28
+    freeze_vision_tower: false
+    policy_loss:
+      _target_: verl.workers.config.PolicyLossConfig
+      loss_mode: vanilla
+      clip_cov_ratio: 0.0002
+      clip_cov_lb: 1.0
+      clip_cov_ub: 5.0
+      kl_cov_ratio: 0.0002
+      ppo_kl_coef: 0.1
+    clip_ratio_c: 3.0
+    loss_agg_mode: token-mean
+    entropy_coeff: 0.001
+    tis_imp_ratio_cap: -1
+    use_kl_loss: false
+    use_torch_compile: true
+    kl_loss_coef: 0.0
+    kl_loss_type: kl
+    ppo_epochs: 1
+    shuffle: false
+    checkpoint:
+      _target_: verl.trainer.config.CheckpointConfig
+      save_contents:
+      - model
+      - optimizer
+      - extra
+      load_contents: ${.save_contents}
+      async_save: false
+    use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: false
+      all_ranks: false
+      ranks: []
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config:
+        nsys:
+          _target_: verl.utils.profiler.config.NsightToolConfig
+          discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+        npu:
+          _target_: verl.utils.profiler.config.NPUToolConfig
+          contents: []
+          level: level1
+          analysis: true
+          discrete: false
+        torch:
+          _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+          step_start: 0
+          step_end: null
+        torch_memory:
+          _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+          trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+          stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+    grad_clip: 1.0
+    ulysses_sequence_parallel_size: 1
+    entropy_from_logits_with_chunking: false
+    entropy_checkpointing: false
+    use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+    use_ref: true
+    grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+    filter_loss_scaling: none
+  ref:
+    strategy: ${actor_rollout_ref.actor.strategy}
+    use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+    log_prob_micro_batch_size: null
+    log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+    log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+    log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: false
+      all_ranks: false
+      ranks: []
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config:
+        nsys:
+          _target_: verl.utils.profiler.config.NsightToolConfig
+          discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+        npu:
+          _target_: verl.utils.profiler.config.NPUToolConfig
+          contents: []
+          level: level1
+          analysis: true
+          discrete: false
+        torch:
+          _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+          step_start: 0
+          step_end: null
+        torch_memory:
+          _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+          trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+          stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    model: null
+    ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+    entropy_from_logits_with_chunking: false
+    entropy_checkpointing: false
+  rollout:
+    _target_: verl.workers.config.RolloutConfig
+    name: vllm
+    mode: sync
+    temperature: 1
+    top_k: -1
+    top_p: 1
+    prompt_length: 1
+    response_length: 400
+    dtype: bfloat16
+    gpu_memory_utilization: 0.7
+    ignore_eos: false
+    enforce_eager: true
+    cudagraph_capture_sizes: null
+    free_cache_engine: true
+    tensor_model_parallel_size: 1
+    data_parallel_size: 1
+    expert_parallel_size: 1
+    max_num_batched_tokens: 16384
+    max_model_len: 16384
+    max_num_seqs: 1024
+    enable_chunked_prefill: true
+    enable_prefix_caching: true
+    load_format: auto
+    log_prob_micro_batch_size: null
+    log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+    log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+    log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+    disable_log_stats: true
+    do_sample: true
+    'n': 1
+    over_sample_rate: 0
+    multi_stage_wake_up: false
+    engine_kwargs:
+      vllm: {}
+      sglang: {}
+    val_kwargs:
+      _target_: verl.workers.config.SamplingConfig
+      top_k: -1
+      top_p: 1.0
+      temperature: 0.5
+      'n': 1
+      do_sample: true
+    multi_turn:
+      _target_: verl.workers.config.MultiTurnConfig
+      enable: false
+      max_assistant_turns: null
+      tool_config_path: null
+      max_user_turns: null
+      max_parallel_calls: 1
+      max_tool_response_length: 256
+      tool_response_truncate_side: middle
+      interaction_config_path: null
+      use_inference_chat_template: false
+      tokenization_sanity_check_mode: strict
+      format: hermes
+      num_repeat_rollouts: null
+    calculate_log_probs: false
+    agent:
+      _target_: verl.workers.config.AgentLoopConfig
+      num_workers: 8
+      agent_loop_config_path: null
+      custom_async_server:
+        _target_: verl.workers.config.CustomAsyncServerConfig
+        path: null
+        name: null
+    update_weights_bucket_megabytes: 512
+    trace:
+      _target_: verl.workers.config.TraceConfig
+      backend: null
+      token2text: false
+    skip_rollout: false
+    skip_dump_dir: /tmp/rollout_dump
+    skip_tokenizer_init: true
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+      all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+      ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+    layered_summon: false
+    rollout_filter_value: 0.9
+    rollout_filter_strategy: top_p
+    rollout_filter_type: largest
+    rollout_filter_include_zero: true
+    rollout_filter_top_p_prob_mode: linear
+    rollout_filter_selection_eps: 0.01
+    rollout_filter_empty_stop_steps: 5
+    rollout_filter_metric: reward_variance
+    gradient_analysis_num_buckets: 6
+    gradient_analysis_bucket_mode: quantile
+  model:
+    _target_: verl.workers.config.HFModelConfig
+    path: ${model_path}
+    hf_config_path: null
+    tokenizer_path: null
+    use_shm: false
+    trust_remote_code: false
+    custom_chat_template: null
+    external_lib: null
+    override_config: {}
+    enable_gradient_checkpointing: true
+    enable_activation_offload: false
+    use_remove_padding: false
+    lora_rank: ${lora.rank}
+    lora_alpha: ${lora.alpha}
+    target_modules: ${lora.target_modules}
+    exclude_modules: null
+    use_liger: false
+    use_fused_kernels: false
+    fused_kernel_options:
+      impl_backend: torch
+  hybrid_engine: true
+  nccl_timeout: 600
+data:
+  tokenizer: null
+  use_shm: false
+  train_files: ~/data/rlhf/gsm8k/train.parquet
+  val_files: ~/data/rlhf/gsm8k/test.parquet
+  prompt_key: prompt
+  reward_fn_key: data_source
+  max_prompt_length: null
+  max_response_length: null
+  train_batch_size: null
+  val_batch_size: null
+  return_raw_input_ids: false
+  return_raw_chat: false
+  return_full_prompt: false
+  shuffle: true
+  dataloader_num_workers: 8
+  validation_shuffle: false
+  filter_overlong_prompts: false
+  filter_overlong_prompts_workers: 1
+  truncation: error
+  image_key: images
+  video_key: videos
+  trust_remote_code: false
+  custom_cls:
+    path: null
+    name: null
+  return_multi_modal_inputs: true
+  sampler:
+    class_path: null
+    class_name: null
+  datagen:
+    path: null
+    name: null
+  apply_chat_template_kwargs: {}
+critic:
+  optim:
+    _target_: verl.workers.config.FSDPOptimizerConfig
+    lr: 1.0e-05
+    lr_warmup_steps_ratio: 0.0
+    total_training_steps: -1
+    weight_decay: 0.01
+    lr_warmup_steps: -1
+    betas:
+    - 0.9
+    - 0.999
+    clip_grad: 1.0
+    min_lr_ratio: 0.0
+    num_cycles: 0.5
+    warmup_style: constant
+  model:
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    path: ${model_path}
+    tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+    override_config: {}
+    external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+    trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+    _target_: verl.workers.config.FSDPCriticModelCfg
+    use_shm: false
+    enable_gradient_checkpointing: true
+    enable_activation_offload: false
+    use_remove_padding: false
+    lora_rank: ${lora.rank}
+    lora_alpha: ${lora.alpha}
+    target_modules: ${lora.target_modules}
+  _target_: verl.workers.config.FSDPCriticConfig
+  rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+  strategy: fsdp
+  enable: null
+  ppo_mini_batch_size: ${ppo_mini_batch_size}
+  ppo_micro_batch_size: null
+  ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+  use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+  ppo_max_token_len_per_gpu: 32768
+  forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+  ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+  shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+  cliprange_value: 0.5
+  loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+  checkpoint:
+    _target_: verl.trainer.config.CheckpointConfig
+    save_contents:
+    - model
+    - optimizer
+    - extra
+    load_contents: ${.save_contents}
+    async_save: false
+  profiler:
+    _target_: verl.utils.profiler.ProfilerConfig
+    tool: ${oc.select:global_profiler.tool,null}
+    enable: false
+    all_ranks: false
+    ranks: []
+    save_path: ${oc.select:global_profiler.save_path,null}
+    tool_config:
+      nsys:
+        _target_: verl.utils.profiler.config.NsightToolConfig
+        discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+      npu:
+        _target_: verl.utils.profiler.config.NPUToolConfig
+        contents: []
+        level: level1
+        analysis: true
+        discrete: false
+      torch:
+        _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+        step_start: 0
+        step_end: null
+      torch_memory:
+        _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+        trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+        stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+  forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+  forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+  ulysses_sequence_parallel_size: 1
+  grad_clip: 1.0
+reward_model:
+  enable: false
+  enable_resource_pool: false
+  n_gpus_per_node: 0
+  nnodes: 0
+  strategy: fsdp
+  model:
+    input_tokenizer: ${actor_rollout_ref.model.path}
+    path: ~/models/FsfairX-LLaMA3-RM-v0.1
+    external_lib: ${actor_rollout_ref.model.external_lib}
+    trust_remote_code: false
+    use_shm: false
+    use_remove_padding: false
+    use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+  micro_batch_size: null
+  micro_batch_size_per_gpu: null
+  max_length: null
+  use_dynamic_bsz: ${critic.use_dynamic_bsz}
+  forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+  reward_manager: naive
+  launch_reward_fn_async: false
+  sandbox_fusion:
+    url: null
+    max_concurrent: 64
+    memory_limit_mb: 1024
+  profiler:
+    _target_: verl.utils.profiler.ProfilerConfig
+    tool: ${oc.select:global_profiler.tool,null}
+    enable: false
+    all_ranks: false
+    ranks: []
+    save_path: ${oc.select:global_profiler.save_path,null}
+    tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+  ulysses_sequence_parallel_size: 1
+custom_reward_function:
+  path: null
+  name: compute_score
+algorithm:
+  _target_: verl.trainer.config.AlgoConfig
+  gamma: 1.0
+  lam: 1.0
+  adv_estimator: gae
+  norm_adv_by_std_in_grpo: true
+  use_kl_in_reward: false
+  kl_penalty: kl
+  kl_ctrl:
+    _target_: verl.trainer.config.KLControlConfig
+    type: fixed
+    kl_coef: 0.0
+    horizon: 10000
+    target_kl: 0.1
+  use_pf_ppo: false
+  pf_ppo:
+    reweight_method: pow
+    weight_pow: 2.0
+  high_level_gamma: 0.95
+  bi_level_gae: false
+  zero_task_advantage: false
+  soft_advantage_reweight: false
+trainer:
+  balance_batch: true
+  total_epochs: 30
+  total_training_steps: 200
+  project_name: ragen
+  experiment_name: sudoku_3b_action1_baseline
+  logger:
+  - console
+  - wandb
+  log_val_generations: 0
+  rollout_data_dir: null
+  validation_data_dir: null
+  nnodes: 1
+  n_gpus_per_node: 8
+  save_freq: -1
+  esi_redundant_time: 0
+  resume_mode: auto
+  resume_from_path: null
+  val_before_train: true
+  val_only: false
+  test_freq: 10
+  critic_warmup: 0
+  default_hdfs_dir: null
+  del_local_ckpt_after_load: false
+  default_local_dir: checkpoints/${trainer.project_name}/${trainer.experiment_name}
+  max_actor_ckpt_to_keep: 1
+  max_critic_ckpt_to_keep: 1
+  ray_wait_register_center_timeout: 300
+  device: cuda
+  use_legacy_worker_impl: auto
+  local_log_dir: results/
+  validation_steps: 1
+  generations_to_log_to_wandb:
+    val: 20
+  log_group_rv_table: false
+  gradient_analysis_mode: false
+  gradient_analysis_every: 50
+  gradient_analysis_env_groups: null
+  gradient_analysis_group_size: null
+  gradient_analysis_log_prefilter: false
+  gradient_analysis_only: false
+  exit_after_gradient_analysis: false
+global_profiler:
+  _target_: verl.utils.profiler.ProfilerConfig
+  tool: null
+  steps: null
+  profile_continuous_steps: false
+  save_path: outputs/profile
+  global_tool_config:
+    nsys:
+      _target_: verl.utils.profiler.config.NsightToolConfig
+      discrete: false
+      controller_nsight_options:
+        trace: cuda,nvtx,cublas,ucx
+        cuda-memory-usage: 'true'
+        cuda-graph-trace: graph
+      worker_nsight_options:
+        trace: cuda,nvtx,cublas,ucx
+        cuda-memory-usage: 'true'
+        cuda-graph-trace: graph
+        capture-range: cudaProfilerApi
+        capture-range-end: null
+        kill: none
+    torch_memory:
+      trace_alloc_max_entries: 100000
+      stack_depth: 32
+      context: all
+      stacks: all
+      kw_args: {}
+ray_kwargs:
+  ray_init:
+    num_cpus: null
+  timeline_json_file: null
+custom_envs:
+  SimpleSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 20
+    env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+      \ when reasoning:\n1. First compare the box position with the target position;\
+      \ the useful push directions are usually the directions that reduce their row/column\
+      \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+      \ push direction. A move that only repositions the player can be useful if it\
+      \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+      \ dead end unless that square is the target or clearly on the only path to the\
+      \ target.\n4. Prefer short plans that move the single box steadily toward the\
+      \ target; avoid wandering moves that do not improve player position or box position.\n\
+      5. If the box and target are aligned in the same row or column, try to keep\
+      \ the box on that line and push along it.\n6. If they are not aligned, first\
+      \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+      7. Check that after each push, the player can still reach the next required\
+      \ pushing side of the box.\n8. Output only the required XML-like format and\
+      \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+      \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+      \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+      \ pull a box. \nThe answer should be a sequence of actions, like <answer>Right\
+      \ || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 2
+      max_steps: 100
+  LargerSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+      \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+      \ you can push it by moving in the same direction. \nYou cannot push a box through\
+      \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+      \ like <answer>Right || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 8
+      dim_y: 8
+      num_boxes: 2
+      max_steps: 100
+      search_depth: 10
+  SokobanDifferentGridVocab:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+      \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+      \ you can push it by moving in the same direction. \nYou cannot push a box through\
+      \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+      \ like <answer>Right || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      search_depth: 30
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      grid_lookup:
+        0: W
+        1: .
+        2: G
+        3: C
+        4: B
+        5: A
+        6: '@'
+      grid_vocab:
+        W: wall
+        .: empty
+        G: target
+        C: box on target
+        B: box
+        A: player
+        '@': player on target
+  CoordSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 20
+    env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+      \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+      \ the zero-indexed coordinates of the player, each box, and each target. \n\
+      Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+      \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+      \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+      \ pull a box.\nThe answer should be a sequence of actions, like <answer>Right\
+      \ || Right || Up</answer>.\n"
+    max_tokens: 120
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 2
+      max_steps: 100
+      observation_format: grid_coord
+  VisualSimpleSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: You are solving the Sokoban puzzle. You are the player and you
+      need to push all boxes to targets. When you are right next to a box, you can
+      push it by moving in the same direction. You cannot push a box through a wall,
+      and you cannot pull a box. The answer should be a sequence of actions, like
+      <answer>Right || Right || Up</answer>
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      render_mode: rgb_array
+  Alfworld:
+    env_type: alfworld
+    max_actions_per_traj: 50
+    parallel_friendly: false
+    max_workers: 1
+    env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+      Complete household tasks by navigating and interacting with objects.
+
+
+      You should first reason step-by-step about the current situation. This reasoning
+      process MUST be enclosed within <think> </think> tags.
+
+      Once you''ve finished your reasoning, you should choose an admissible action
+      for current step and present it within <answer>...</answer> tags.
+
+      '
+    max_tokens: 512
+    env_config:
+      eval_dataset: eval_in_distribution
+  AlfworldOOD:
+    env_type: alfworld
+    max_actions_per_traj: 50
+    parallel_friendly: false
+    max_workers: 1
+    env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+      Complete household tasks by navigating and interacting with objects.
+
+
+      You should first reason step-by-step about the current situation. This reasoning
+      process MUST be enclosed within <think> </think> tags.
+
+      Once you''ve finished your reasoning, you should choose an admissible action
+      for current step and present it within <answer>...</answer> tags.
+
+      '
+    max_tokens: 512
+    env_config:
+      eval_dataset: eval_out_of_distribution
+  Countdown:
+    env_type: countdown
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving the Countdown puzzle. You should use the num
+      list to create an equation that equals the target. Example answer format: <think>
+      To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+      = 4. So the answer is 2 + 5 - 3 = 4. </think><answer>2 + 5 - 3</answer>'
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config: null
+  Bandit:
+    env_type: bandit
+    max_actions_per_traj: 1
+    env_instruction: ''
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      split: train
+  BanditTest:
+    env_type: bandit
+    max_actions_per_traj: 1
+    env_instruction: ''
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      split: test
+  DeepCoder:
+    env_type: deepcoder
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving a coding task. Provide a complete Python function
+      solution only. Format: <answer>...</answer>'
+    max_tokens: 8000
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 1
+  FrozenLake:
+    env_type: frozen_lake
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+      go to the target. You may move to the unintended direction due to the slippery
+      ice. Example answer format: <think>To forbid the hole and go to the target,
+      I should go left then go up.</think><answer>Left || Up</answer>'
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      success_rate: 0.8
+  CoordFrozenLake:
+    env_type: frozen_lake
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+      both a symbol grid and zero-indexed coordinates for the start, goal, player,
+      and any holes.
+
+      Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+      (5, 5).
+
+      Beware that the ice is slippery, so the agent might slide and end up in an unintended
+      tile.
+
+      Respond with a sequence of actions such as <answer>Left || Up || Up</answer>.
+
+      '
+    max_tokens: 120
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      observation_format: grid_coord
+      success_rate: 0.8
+  MetamathQA:
+    env_type: metamathqa
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving Math problems. '
+    max_tokens: 100
+    env_config: null
+  WebShopFull:
+    env_type: webshop
+    max_actions_per_traj: 15
+    env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+      environment.
+    max_tokens: 200
+    env_config:
+      dataset: full
+  WebShop:
+    env_type: webshop
+    max_actions_per_traj: 9
+    env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+      a product that close to the production description. You need to search, read
+      the search results, pick a product, choose the size and color and buy. You should
+      only choose action from the available actions list provided later.  Example
+      process: I need a gingko light and 20x20 pillow cover that is hand painted.
+      First search[gingko light 20x20 pillow cover hand painted], answer format: <answer>search[blanket
+      with fleece throw]</answer>. Valid answer is search[<keywords>] or click[<clickable>].'
+    max_tokens: 200
+    env_config:
+      dataset: small
+  Lean:
+    env_type: lean
+    max_actions_per_traj: 30
+    env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+      propose a sequence of tactics that completes the proof. Think step by step about
+      which tactics to apply next. Provide tactics separated by '||', for example
+      <answer>intro || simp || rfl</answer>.
+    max_tokens: 512
+    parallel_friendly: true
+    max_workers: 32
+    env_config: null
+  SimpleSudoku:
+    env_type: sudoku
+    max_actions_per_traj: 20
+    env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+      row, column, and 2x2 box contains the numbers 1-4 without repetition.
+
+      Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+      shown as dots (.).
+
+      Place numbers one at a time using the format, for example: <answer>place 1 at
+      row 2 col 3</answer> or <answer>1,2,3</answer>
+
+      The environment will provide feedback on valid/invalid moves and show conflicts
+      if any occur.
+
+      '
+    max_tokens: 150
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      grid_size: 4
+      difficulty: easy
+      render_format: with_feedback
+      show_conflicts: false
+      show_valid_numbers: false
+      max_steps: 20
+  MediumSudoku:
+    env_type: sudoku
+    max_actions_per_traj: 30
+    env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+      row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+      Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+      shown as dots (.).
+
+      Place numbers one at a time using the format: <answer>place 5 at row 2 col 3</answer>
+      or <answer>2,3,5</answer>
+
+      The environment will provide feedback on valid/invalid moves and show conflicts
+      if any occur.
+
+      '
+    max_tokens: 150
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      grid_size: 9
+      difficulty: medium
+      render_format: with_feedback
+      show_conflicts: true
+      show_valid_numbers: true
+      max_steps: 81
+  SearchQA:
+    env_type: search
+    max_actions_per_traj: 10
+    env_instruction: "You are a search agent answering questions by searching for\
+      \ information.\nUse search[your query] to find relevant documents, and finish[your\
+      \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+      \ about the current situation. This reasoning process MUST be enclosed within\
+      \ <think> </think> tags.\nThen provide your action within <answer>...</answer>\
+      \ tags.\n\nExamples:\n  <think>I need to find information about Ben Platt's\
+      \ father.</think><answer>search[Ben Platt father parent]</answer>\n  <think>Based\
+      \ on the search results, Ben Platt's father is Henry Platt.</think><answer>finish[Henry\
+      \ Platt]</answer>\n"
+    max_tokens: 300
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 10
+      max_search_results: 5
+  SearchQAMock:
+    env_type: search
+    max_actions_per_traj: 10
+    env_instruction: "You are a search agent answering questions by searching for\
+      \ information.\nUse search[your query] to find relevant documents, and finish[your\
+      \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+      \ about the current situation. This reasoning process MUST be enclosed within\
+      \ <think> </think> tags.\nThen provide your action within <answer>...</answer>\
+      \ tags.\n\nExamples:\n  <think>I need to find information about Ben Platt's\
+      \ father.</think><answer>search[Ben Platt father parent]</answer>\n  <think>Based\
+      \ on the search results, Ben Platt's father is Henry Platt.</think><answer>finish[Henry\
+      \ Platt]</answer>\n"
+    max_tokens: 300
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 10
+      max_search_results: 5
+      mock_mode: true
+  game_2048:
+    env_type: game_2048
+    max_actions_per_traj: 700
+    env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+      by sliding Up, Right, Down, or Left.
+
+      If a move is invalid (no tiles move), a small penalty is applied. Respond with
+      a single action.
+
+      Example: <answer>Up</answer>
+
+      '
+    max_tokens: 8192
+    env_config: null
+  rubikscube:
+    env_type: rubikscube
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+      is to restore the cube so that each of the faces consists of a single, unique
+      color.
+
+      Available actions use standard Singmaster notation for face rotations: U, U'',
+      D, D'', L, L'', R, R'', F, F'', B, B''.
+
+      - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+      - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+      prime ('') means 90° counter-clockwise (e.g., "R''").
+
+      Respond with a sequence of actions separated by "||".
+
+      Example: <answer>U</answer>
+
+      '
+    max_tokens: 96
+    env_config:
+      scramble_depth: 1
+      max_steps: 7
+      render_mode: text
+system:
+  CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+  train: 10000
+  val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/share/model/Qwen/Qwen2.5-3B-Instruct
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+  rank: 0
+  alpha: 64
+  target_modules: all-linear
+agent_proxy:
+  context_window_mode: full
+  max_context_window: -1
+  batch_adjust_mode: copy
+  max_turn: 20
+  action_sep: '||'
+  max_actions_per_turn: 1
+  use_turn_scores: false
+  enable_think: true
+  reward_normalization:
+    grouping: state
+    method: identity
+collapse_detection:
+  compute_freq: 5
+  micro_batch_size: 128
+  first_turn_enabled: true
+  multi_turn_enabled: true
+  num_samples: 64
+es_manager:
+  format_penalty: -0.1
+  train:
+    env_groups: 8
+    group_size: 16
+    env_configs:
+      tags:
+      - SimpleSudoku
+      n_groups:
+      - 8
+  val:
+    env_groups: 32
+    group_size: 16
+    env_configs:
+      tags:
+      - SimpleSudoku
+      n_groups:
+      - 32
+ctx_manager:
+  generation:
+    gen_config:
+      response_length: ${actor_rollout_ref.rollout.response_length}
+      temperature: ${actor_rollout_ref.rollout.temperature}
+      top_p: ${actor_rollout_ref.rollout.top_p}
+      top_k: ${actor_rollout_ref.rollout.top_k}
+      kwargs: null

outputs/2026-06-09/16-05-29/.hydra/config.yaml

@@ -0,0 +1,1048 @@
+actor_rollout_ref:
+  actor:
+    optim:
+      _target_: verl.workers.config.FSDPOptimizerConfig
+      lr: 1.0e-06
+      lr_warmup_steps_ratio: 0.0
+      total_training_steps: -1
+      weight_decay: 0.01
+      lr_warmup_steps: -1
+      betas:
+      - 0.9
+      - 0.999
+      clip_grad: 1.0
+      min_lr_ratio: 0.0
+      num_cycles: 0.5
+      warmup_style: constant
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    _target_: verl.workers.config.FSDPActorConfig
+    strategy: fsdp
+    ppo_mini_batch_size: ${ppo_mini_batch_size}
+    ppo_micro_batch_size: null
+    ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+    use_dynamic_bsz: false
+    ppo_max_token_len_per_gpu: 16384
+    clip_ratio: 0.2
+    clip_ratio_low: 0.2
+    clip_ratio_high: 0.28
+    freeze_vision_tower: false
+    policy_loss:
+      _target_: verl.workers.config.PolicyLossConfig
+      loss_mode: vanilla
+      clip_cov_ratio: 0.0002
+      clip_cov_lb: 1.0
+      clip_cov_ub: 5.0
+      kl_cov_ratio: 0.0002
+      ppo_kl_coef: 0.1
+    clip_ratio_c: 3.0
+    loss_agg_mode: token-mean
+    entropy_coeff: 0.001
+    tis_imp_ratio_cap: -1
+    use_kl_loss: false
+    use_torch_compile: true
+    kl_loss_coef: 0.0
+    kl_loss_type: kl
+    ppo_epochs: 1
+    shuffle: false
+    checkpoint:
+      _target_: verl.trainer.config.CheckpointConfig
+      save_contents:
+      - model
+      - optimizer
+      - extra
+      load_contents: ${.save_contents}
+      async_save: false
+    use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: false
+      all_ranks: false
+      ranks: []
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config:
+        nsys:
+          _target_: verl.utils.profiler.config.NsightToolConfig
+          discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+        npu:
+          _target_: verl.utils.profiler.config.NPUToolConfig
+          contents: []
+          level: level1
+          analysis: true
+          discrete: false
+        torch:
+          _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+          step_start: 0
+          step_end: null
+        torch_memory:
+          _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+          trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+          stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+    grad_clip: 1.0
+    ulysses_sequence_parallel_size: 1
+    entropy_from_logits_with_chunking: false
+    entropy_checkpointing: false
+    use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+    use_ref: true
+    grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+    filter_loss_scaling: none
+  ref:
+    strategy: ${actor_rollout_ref.actor.strategy}
+    use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+    log_prob_micro_batch_size: null
+    log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+    log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+    log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: false
+      all_ranks: false
+      ranks: []
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config:
+        nsys:
+          _target_: verl.utils.profiler.config.NsightToolConfig
+          discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+        npu:
+          _target_: verl.utils.profiler.config.NPUToolConfig
+          contents: []
+          level: level1
+          analysis: true
+          discrete: false
+        torch:
+          _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+          step_start: 0
+          step_end: null
+        torch_memory:
+          _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+          trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+          stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    model: null
+    ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+    entropy_from_logits_with_chunking: false
+    entropy_checkpointing: false
+  rollout:
+    _target_: verl.workers.config.RolloutConfig
+    name: vllm
+    mode: sync
+    temperature: 1
+    top_k: -1
+    top_p: 1
+    prompt_length: 1
+    response_length: 400
+    dtype: bfloat16
+    gpu_memory_utilization: 0.7
+    ignore_eos: false
+    enforce_eager: true
+    cudagraph_capture_sizes: null
+    free_cache_engine: true
+    tensor_model_parallel_size: 1
+    data_parallel_size: 1
+    expert_parallel_size: 1
+    max_num_batched_tokens: 16384
+    max_model_len: 16384
+    max_num_seqs: 1024
+    enable_chunked_prefill: true
+    enable_prefix_caching: true
+    load_format: auto
+    log_prob_micro_batch_size: null
+    log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+    log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+    log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+    disable_log_stats: true
+    do_sample: true
+    'n': 1
+    over_sample_rate: 0
+    multi_stage_wake_up: false
+    engine_kwargs:
+      vllm: {}
+      sglang: {}
+    val_kwargs:
+      _target_: verl.workers.config.SamplingConfig
+      top_k: -1
+      top_p: 1.0
+      temperature: 0.5
+      'n': 1
+      do_sample: true
+    multi_turn:
+      _target_: verl.workers.config.MultiTurnConfig
+      enable: false
+      max_assistant_turns: null
+      tool_config_path: null
+      max_user_turns: null
+      max_parallel_calls: 1
+      max_tool_response_length: 256
+      tool_response_truncate_side: middle
+      interaction_config_path: null
+      use_inference_chat_template: false
+      tokenization_sanity_check_mode: strict
+      format: hermes
+      num_repeat_rollouts: null
+    calculate_log_probs: false
+    agent:
+      _target_: verl.workers.config.AgentLoopConfig
+      num_workers: 8
+      agent_loop_config_path: null
+      custom_async_server:
+        _target_: verl.workers.config.CustomAsyncServerConfig
+        path: null
+        name: null
+    update_weights_bucket_megabytes: 512
+    trace:
+      _target_: verl.workers.config.TraceConfig
+      backend: null
+      token2text: false
+    skip_rollout: false
+    skip_dump_dir: /tmp/rollout_dump
+    skip_tokenizer_init: true
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+      all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+      ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+    layered_summon: false
+    rollout_filter_value: 0.9
+    rollout_filter_strategy: top_p
+    rollout_filter_type: largest
+    rollout_filter_include_zero: true
+    rollout_filter_top_p_prob_mode: linear
+    rollout_filter_selection_eps: 0.01
+    rollout_filter_empty_stop_steps: 5
+    rollout_filter_metric: reward_variance
+    gradient_analysis_num_buckets: 6
+    gradient_analysis_bucket_mode: quantile
+  model:
+    _target_: verl.workers.config.HFModelConfig
+    path: ${model_path}
+    hf_config_path: null
+    tokenizer_path: null
+    use_shm: false
+    trust_remote_code: false
+    custom_chat_template: null
+    external_lib: null
+    override_config: {}
+    enable_gradient_checkpointing: true
+    enable_activation_offload: false
+    use_remove_padding: false
+    lora_rank: ${lora.rank}
+    lora_alpha: ${lora.alpha}
+    target_modules: ${lora.target_modules}
+    exclude_modules: null
+    use_liger: false
+    use_fused_kernels: false
+    fused_kernel_options:
+      impl_backend: torch
+  hybrid_engine: true
+  nccl_timeout: 600
+data:
+  tokenizer: null
+  use_shm: false
+  train_files: ~/data/rlhf/gsm8k/train.parquet
+  val_files: ~/data/rlhf/gsm8k/test.parquet
+  prompt_key: prompt
+  reward_fn_key: data_source
+  max_prompt_length: null
+  max_response_length: null
+  train_batch_size: null
+  val_batch_size: null
+  return_raw_input_ids: false
+  return_raw_chat: false
+  return_full_prompt: false
+  shuffle: true
+  dataloader_num_workers: 8
+  validation_shuffle: false
+  filter_overlong_prompts: false
+  filter_overlong_prompts_workers: 1
+  truncation: error
+  image_key: images
+  video_key: videos
+  trust_remote_code: false
+  custom_cls:
+    path: null
+    name: null
+  return_multi_modal_inputs: true
+  sampler:
+    class_path: null
+    class_name: null
+  datagen:
+    path: null
+    name: null
+  apply_chat_template_kwargs: {}
+critic:
+  optim:
+    _target_: verl.workers.config.FSDPOptimizerConfig
+    lr: 1.0e-05
+    lr_warmup_steps_ratio: 0.0
+    total_training_steps: -1
+    weight_decay: 0.01
+    lr_warmup_steps: -1
+    betas:
+    - 0.9
+    - 0.999
+    clip_grad: 1.0
+    min_lr_ratio: 0.0
+    num_cycles: 0.5
+    warmup_style: constant
+  model:
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    path: ${model_path}
+    tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+    override_config: {}
+    external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+    trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+    _target_: verl.workers.config.FSDPCriticModelCfg
+    use_shm: false
+    enable_gradient_checkpointing: true
+    enable_activation_offload: false
+    use_remove_padding: false
+    lora_rank: ${lora.rank}
+    lora_alpha: ${lora.alpha}
+    target_modules: ${lora.target_modules}
+  _target_: verl.workers.config.FSDPCriticConfig
+  rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+  strategy: fsdp
+  enable: null
+  ppo_mini_batch_size: ${ppo_mini_batch_size}
+  ppo_micro_batch_size: null
+  ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+  use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+  ppo_max_token_len_per_gpu: 32768
+  forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+  ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+  shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+  cliprange_value: 0.5
+  loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+  checkpoint:
+    _target_: verl.trainer.config.CheckpointConfig
+    save_contents:
+    - model
+    - optimizer
+    - extra
+    load_contents: ${.save_contents}
+    async_save: false
+  profiler:
+    _target_: verl.utils.profiler.ProfilerConfig
+    tool: ${oc.select:global_profiler.tool,null}
+    enable: false
+    all_ranks: false
+    ranks: []
+    save_path: ${oc.select:global_profiler.save_path,null}
+    tool_config:
+      nsys:
+        _target_: verl.utils.profiler.config.NsightToolConfig
+        discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+      npu:
+        _target_: verl.utils.profiler.config.NPUToolConfig
+        contents: []
+        level: level1
+        analysis: true
+        discrete: false
+      torch:
+        _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+        step_start: 0
+        step_end: null
+      torch_memory:
+        _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+        trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+        stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+  forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+  forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+  ulysses_sequence_parallel_size: 1
+  grad_clip: 1.0
+reward_model:
+  enable: false
+  enable_resource_pool: false
+  n_gpus_per_node: 0
+  nnodes: 0
+  strategy: fsdp
+  model:
+    input_tokenizer: ${actor_rollout_ref.model.path}
+    path: ~/models/FsfairX-LLaMA3-RM-v0.1
+    external_lib: ${actor_rollout_ref.model.external_lib}
+    trust_remote_code: false
+    use_shm: false
+    use_remove_padding: false
+    use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+  micro_batch_size: null
+  micro_batch_size_per_gpu: null
+  max_length: null
+  use_dynamic_bsz: ${critic.use_dynamic_bsz}
+  forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+  reward_manager: naive
+  launch_reward_fn_async: false
+  sandbox_fusion:
+    url: null
+    max_concurrent: 64
+    memory_limit_mb: 1024
+  profiler:
+    _target_: verl.utils.profiler.ProfilerConfig
+    tool: ${oc.select:global_profiler.tool,null}
+    enable: false
+    all_ranks: false
+    ranks: []
+    save_path: ${oc.select:global_profiler.save_path,null}
+    tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+  ulysses_sequence_parallel_size: 1
+custom_reward_function:
+  path: null
+  name: compute_score
+algorithm:
+  _target_: verl.trainer.config.AlgoConfig
+  gamma: 1.0
+  lam: 1.0
+  adv_estimator: gae
+  norm_adv_by_std_in_grpo: true
+  use_kl_in_reward: false
+  kl_penalty: kl
+  kl_ctrl:
+    _target_: verl.trainer.config.KLControlConfig
+    type: fixed
+    kl_coef: 0.0
+    horizon: 10000
+    target_kl: 0.1
+  use_pf_ppo: false
+  pf_ppo:
+    reweight_method: pow
+    weight_pow: 2.0
+  high_level_gamma: 0.95
+  bi_level_gae: false
+  zero_task_advantage: false
+  soft_advantage_reweight: false
+trainer:
+  balance_batch: true
+  total_epochs: 30
+  total_training_steps: 200
+  project_name: ragen
+  experiment_name: sudoku_3b_action1_abstraction
+  logger:
+  - console
+  - wandb
+  log_val_generations: 0
+  rollout_data_dir: null
+  validation_data_dir: null
+  nnodes: 1
+  n_gpus_per_node: 8
+  save_freq: -1
+  esi_redundant_time: 0
+  resume_mode: auto
+  resume_from_path: null
+  val_before_train: true
+  val_only: false
+  test_freq: 10
+  critic_warmup: 0
+  default_hdfs_dir: null
+  del_local_ckpt_after_load: false
+  default_local_dir: checkpoints/${trainer.project_name}/${trainer.experiment_name}
+  max_actor_ckpt_to_keep: 1
+  max_critic_ckpt_to_keep: 1
+  ray_wait_register_center_timeout: 300
+  device: cuda
+  use_legacy_worker_impl: auto
+  local_log_dir: results/
+  validation_steps: 1
+  generations_to_log_to_wandb:
+    val: 20
+  log_group_rv_table: false
+  gradient_analysis_mode: false
+  gradient_analysis_every: 50
+  gradient_analysis_env_groups: null
+  gradient_analysis_group_size: null
+  gradient_analysis_log_prefilter: false
+  gradient_analysis_only: false
+  exit_after_gradient_analysis: false
+global_profiler:
+  _target_: verl.utils.profiler.ProfilerConfig
+  tool: null
+  steps: null
+  profile_continuous_steps: false
+  save_path: outputs/profile
+  global_tool_config:
+    nsys:
+      _target_: verl.utils.profiler.config.NsightToolConfig
+      discrete: false
+      controller_nsight_options:
+        trace: cuda,nvtx,cublas,ucx
+        cuda-memory-usage: 'true'
+        cuda-graph-trace: graph
+      worker_nsight_options:
+        trace: cuda,nvtx,cublas,ucx
+        cuda-memory-usage: 'true'
+        cuda-graph-trace: graph
+        capture-range: cudaProfilerApi
+        capture-range-end: null
+        kill: none
+    torch_memory:
+      trace_alloc_max_entries: 100000
+      stack_depth: 32
+      context: all
+      stacks: all
+      kw_args: {}
+ray_kwargs:
+  ray_init:
+    num_cpus: null
+  timeline_json_file: null
+custom_envs:
+  SimpleSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 20
+    env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+      \ when reasoning:\n1. First compare the box position with the target position;\
+      \ the useful push directions are usually the directions that reduce their row/column\
+      \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+      \ push direction. A move that only repositions the player can be useful if it\
+      \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+      \ dead end unless that square is the target or clearly on the only path to the\
+      \ target.\n4. Prefer short plans that move the single box steadily toward the\
+      \ target; avoid wandering moves that do not improve player position or box position.\n\
+      5. If the box and target are aligned in the same row or column, try to keep\
+      \ the box on that line and push along it.\n6. If they are not aligned, first\
+      \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+      7. Check that after each push, the player can still reach the next required\
+      \ pushing side of the box.\n8. Output only the required XML-like format and\
+      \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+      \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+      \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+      \ pull a box. \nThe answer should be a sequence of actions, like <answer>Right\
+      \ || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 2
+      max_steps: 100
+  LargerSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+      \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+      \ you can push it by moving in the same direction. \nYou cannot push a box through\
+      \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+      \ like <answer>Right || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 8
+      dim_y: 8
+      num_boxes: 2
+      max_steps: 100
+      search_depth: 10
+  SokobanDifferentGridVocab:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+      \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+      \ you can push it by moving in the same direction. \nYou cannot push a box through\
+      \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+      \ like <answer>Right || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      search_depth: 30
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      grid_lookup:
+        0: W
+        1: .
+        2: G
+        3: C
+        4: B
+        5: A
+        6: '@'
+      grid_vocab:
+        W: wall
+        .: empty
+        G: target
+        C: box on target
+        B: box
+        A: player
+        '@': player on target
+  CoordSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 20
+    env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+      \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+      \ the zero-indexed coordinates of the player, each box, and each target. \n\
+      Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+      \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+      \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+      \ pull a box.\nThe answer should be a sequence of actions, like <answer>Right\
+      \ || Right || Up</answer>.\n"
+    max_tokens: 120
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 2
+      max_steps: 100
+      observation_format: grid_coord
+  VisualSimpleSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: You are solving the Sokoban puzzle. You are the player and you
+      need to push all boxes to targets. When you are right next to a box, you can
+      push it by moving in the same direction. You cannot push a box through a wall,
+      and you cannot pull a box. The answer should be a sequence of actions, like
+      <answer>Right || Right || Up</answer>
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      render_mode: rgb_array
+  Alfworld:
+    env_type: alfworld
+    max_actions_per_traj: 50
+    parallel_friendly: false
+    max_workers: 1
+    env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+      Complete household tasks by navigating and interacting with objects.
+
+
+      You should first reason step-by-step about the current situation. This reasoning
+      process MUST be enclosed within <think> </think> tags.
+
+      Once you''ve finished your reasoning, you should choose an admissible action
+      for current step and present it within <answer>...</answer> tags.
+
+      '
+    max_tokens: 512
+    env_config:
+      eval_dataset: eval_in_distribution
+  AlfworldOOD:
+    env_type: alfworld
+    max_actions_per_traj: 50
+    parallel_friendly: false
+    max_workers: 1
+    env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+      Complete household tasks by navigating and interacting with objects.
+
+
+      You should first reason step-by-step about the current situation. This reasoning
+      process MUST be enclosed within <think> </think> tags.
+
+      Once you''ve finished your reasoning, you should choose an admissible action
+      for current step and present it within <answer>...</answer> tags.
+
+      '
+    max_tokens: 512
+    env_config:
+      eval_dataset: eval_out_of_distribution
+  Countdown:
+    env_type: countdown
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving the Countdown puzzle. You should use the num
+      list to create an equation that equals the target. Example answer format: <think>
+      To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+      = 4. So the answer is 2 + 5 - 3 = 4. </think><answer>2 + 5 - 3</answer>'
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config: null
+  Bandit:
+    env_type: bandit
+    max_actions_per_traj: 1
+    env_instruction: ''
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      split: train
+  BanditTest:
+    env_type: bandit
+    max_actions_per_traj: 1
+    env_instruction: ''
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      split: test
+  DeepCoder:
+    env_type: deepcoder
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving a coding task. Provide a complete Python function
+      solution only. Format: <answer>...</answer>'
+    max_tokens: 8000
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 1
+  FrozenLake:
+    env_type: frozen_lake
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+      go to the target. You may move to the unintended direction due to the slippery
+      ice. Example answer format: <think>To forbid the hole and go to the target,
+      I should go left then go up.</think><answer>Left || Up</answer>'
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      success_rate: 0.8
+  CoordFrozenLake:
+    env_type: frozen_lake
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+      both a symbol grid and zero-indexed coordinates for the start, goal, player,
+      and any holes.
+
+      Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+      (5, 5).
+
+      Beware that the ice is slippery, so the agent might slide and end up in an unintended
+      tile.
+
+      Respond with a sequence of actions such as <answer>Left || Up || Up</answer>.
+
+      '
+    max_tokens: 120
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      observation_format: grid_coord
+      success_rate: 0.8
+  MetamathQA:
+    env_type: metamathqa
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving Math problems. '
+    max_tokens: 100
+    env_config: null
+  WebShopFull:
+    env_type: webshop
+    max_actions_per_traj: 15
+    env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+      environment.
+    max_tokens: 200
+    env_config:
+      dataset: full
+  WebShop:
+    env_type: webshop
+    max_actions_per_traj: 9
+    env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+      a product that close to the production description. You need to search, read
+      the search results, pick a product, choose the size and color and buy. You should
+      only choose action from the available actions list provided later.  Example
+      process: I need a gingko light and 20x20 pillow cover that is hand painted.
+      First search[gingko light 20x20 pillow cover hand painted], answer format: <answer>search[blanket
+      with fleece throw]</answer>. Valid answer is search[<keywords>] or click[<clickable>].'
+    max_tokens: 200
+    env_config:
+      dataset: small
+  Lean:
+    env_type: lean
+    max_actions_per_traj: 30
+    env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+      propose a sequence of tactics that completes the proof. Think step by step about
+      which tactics to apply next. Provide tactics separated by '||', for example
+      <answer>intro || simp || rfl</answer>.
+    max_tokens: 512
+    parallel_friendly: true
+    max_workers: 32
+    env_config: null
+  SimpleSudoku:
+    env_type: sudoku
+    max_actions_per_traj: 20
+    env_instruction: 'You are a careful 4x4 Sudoku solver. Use these reusable abstractions
+      when reasoning:
+
+      1. In <think>, explain the constraint logic behind the move, not just the final
+      placement. Mention which row, column, or 2x2 box makes the move safe or forced.
+
+      2. Treat each move as a constraint-preserving placement: place a number only
+      if it does not already appear in the same row, column, or 2x2 box.
+
+      3. First look for highly forced cells. If an empty cell has only one legal candidate
+      after checking its row, column, and box, fill it immediately and explain why
+      other numbers are excluded.
+
+      4. If no cell is obviously forced, scan each row, column, and 2x2 box for missing
+      numbers. If a missing number can go in only one empty position within that unit,
+      place it there and state that unit-level reason.
+
+      5. Prefer moves that reduce uncertainty and create new forced cells for the
+      next turn. A good move should make the remaining puzzle more constrained, not
+      more ambiguous.
+
+      6. Solve incrementally: choose exactly one placement, explain it briefly in
+      <think>, then output that one move in <answer>.
+
+      7. Never modify bracketed initial cells or already-filled cells. Only place
+      numbers into dots.
+
+      8. Avoid exploratory guesses when a forced move exists. In this environment,
+      reliable progress usually comes from constraint propagation rather than trial-and-error.
+
+      9. If a previous move was invalid or the board did not change, do not repeat
+      the same placement. Recompute legal candidates and explain the corrected constraint-consistent
+      choice.
+
+      10. Use row, column, and box agreement as confidence: the strongest placements
+      are those supported by multiple constraints at once.
+
+      11. Keep <think> concise but meaningful: identify the target cell, list or compare
+      its legal candidates, and give the decisive constraint.
+
+      12. Output only the required XML-like format and choose valid Sudoku placements.
+
+
+      You are solving a Sudoku puzzle. Fill in the grid so that every row, column,
+      and 2x2 box contains the numbers 1-4 without repetition.
+
+      Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+      shown as dots (.).
+
+      Place numbers one at a time using the format: <answer>place 1 at row 2 col 3</answer>
+
+      Always output: <think> [brief constraint-based reasoning] </think> <answer>
+      [one placement] </answer>
+
+      The environment will provide feedback on valid/invalid moves and show conflicts
+      if any occur.
+
+      '
+    max_tokens: 150
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      grid_size: 4
+      difficulty: easy
+      render_format: with_feedback
+      show_conflicts: false
+      show_valid_numbers: false
+      max_steps: 20
+  MediumSudoku:
+    env_type: sudoku
+    max_actions_per_traj: 30
+    env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+      row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+      Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+      shown as dots (.).
+
+      Place numbers one at a time using the format: <answer>place 5 at row 2 col 3</answer>
+      or <answer>2,3,5</answer>
+
+      The environment will provide feedback on valid/invalid moves and show conflicts
+      if any occur.
+
+      '
+    max_tokens: 150
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      grid_size: 9
+      difficulty: medium
+      render_format: with_feedback
+      show_conflicts: true
+      show_valid_numbers: true
+      max_steps: 81
+  SearchQA:
+    env_type: search
+    max_actions_per_traj: 10
+    env_instruction: "You are a search agent answering questions by searching for\
+      \ information.\nUse search[your query] to find relevant documents, and finish[your\
+      \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+      \ about the current situation. This reasoning process MUST be enclosed within\
+      \ <think> </think> tags.\nThen provide your action within <answer>...</answer>\
+      \ tags.\n\nExamples:\n  <think>I need to find information about Ben Platt's\
+      \ father.</think><answer>search[Ben Platt father parent]</answer>\n  <think>Based\
+      \ on the search results, Ben Platt's father is Henry Platt.</think><answer>finish[Henry\
+      \ Platt]</answer>\n"
+    max_tokens: 300
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 10
+      max_search_results: 5
+  SearchQAMock:
+    env_type: search
+    max_actions_per_traj: 10
+    env_instruction: "You are a search agent answering questions by searching for\
+      \ information.\nUse search[your query] to find relevant documents, and finish[your\
+      \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+      \ about the current situation. This reasoning process MUST be enclosed within\
+      \ <think> </think> tags.\nThen provide your action within <answer>...</answer>\
+      \ tags.\n\nExamples:\n  <think>I need to find information about Ben Platt's\
+      \ father.</think><answer>search[Ben Platt father parent]</answer>\n  <think>Based\
+      \ on the search results, Ben Platt's father is Henry Platt.</think><answer>finish[Henry\
+      \ Platt]</answer>\n"
+    max_tokens: 300
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 10
+      max_search_results: 5
+      mock_mode: true
+  game_2048:
+    env_type: game_2048
+    max_actions_per_traj: 700
+    env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+      by sliding Up, Right, Down, or Left.
+
+      If a move is invalid (no tiles move), a small penalty is applied. Respond with
+      a single action.
+
+      Example: <answer>Up</answer>
+
+      '
+    max_tokens: 8192
+    env_config: null
+  rubikscube:
+    env_type: rubikscube
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+      is to restore the cube so that each of the faces consists of a single, unique
+      color.
+
+      Available actions use standard Singmaster notation for face rotations: U, U'',
+      D, D'', L, L'', R, R'', F, F'', B, B''.
+
+      - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+      - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+      prime ('') means 90° counter-clockwise (e.g., "R''").
+
+      Respond with a sequence of actions separated by "||".
+
+      Example: <answer>U</answer>
+
+      '
+    max_tokens: 96
+    env_config:
+      scramble_depth: 1
+      max_steps: 7
+      render_mode: text
+system:
+  CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+  train: 10000
+  val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/share/model/Qwen/Qwen2.5-3B-Instruct
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+  rank: 0
+  alpha: 64
+  target_modules: all-linear
+agent_proxy:
+  context_window_mode: full
+  max_context_window: -1
+  batch_adjust_mode: copy
+  max_turn: 20
+  action_sep: '||'
+  max_actions_per_turn: 1
+  use_turn_scores: false
+  enable_think: true
+  reward_normalization:
+    grouping: state
+    method: identity
+collapse_detection:
+  compute_freq: 5
+  micro_batch_size: 128
+  first_turn_enabled: true
+  multi_turn_enabled: true
+  num_samples: 64
+es_manager:
+  format_penalty: -0.1
+  train:
+    env_groups: 8
+    group_size: 16
+    env_configs:
+      tags:
+      - SimpleSudoku
+      n_groups:
+      - 8
+  val:
+    env_groups: 32
+    group_size: 16
+    env_configs:
+      tags:
+      - SimpleSudoku
+      n_groups:
+      - 32
+ctx_manager:
+  generation:
+    gen_config:
+      response_length: ${actor_rollout_ref.rollout.response_length}
+      temperature: ${actor_rollout_ref.rollout.temperature}
+      top_p: ${actor_rollout_ref.rollout.top_p}
+      top_k: ${actor_rollout_ref.rollout.top_k}
+      kwargs: null

outputs/2026-06-09/16-05-29/.hydra/hydra.yaml

@@ -0,0 +1,178 @@
+hydra:
+  run:
+    dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+  sweep:
+    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath:
+  - pkg://verl.trainer.config
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task:
+    - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+    - actor_rollout_ref.rollout.rollout_filter_value=0.9
+    - trainer.total_training_steps=200
+    - model_path=/mnt/general/share/model/Qwen/Qwen2.5-3B-Instruct
+    - trainer.experiment_name=sudoku_3b_action1_abstraction
+  job:
+    name: train
+    chdir: null
+    override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,model_path=/mnt/general/share/model/Qwen/Qwen2.5-3B-Instruct,trainer.experiment_name=sudoku_3b_action1_abstraction,trainer.total_training_steps=200
+    id: ???
+    num: ???
+    config_name: _8_sudoku
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /mnt/general/wanghy/RAGEN_v2
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /mnt/general/wanghy/RAGEN_v2/config
+      schema: file
+      provider: main
+    - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+      schema: file
+      provider: command-line
+    - path: verl.trainer.config
+      schema: pkg
+      provider: hydra.searchpath in main
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-09/16-05-29
+    choices:
+      reward_model: dp_reward_model
+      critic: dp_critic
+      critic/../engine@critic.model.fsdp_config: fsdp
+      critic/../optim@critic.optim: fsdp
+      model@actor_rollout_ref.model: hf_model
+      rollout@actor_rollout_ref.rollout: rollout
+      ref@actor_rollout_ref.ref: dp_ref
+      ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+      data: legacy_data
+      actor@actor_rollout_ref.actor: dp_actor
+      actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+      actor/../optim@actor_rollout_ref.actor.optim: fsdp
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

outputs/2026-06-09/16-05-29/.hydra/overrides.yaml

@@ -0,0 +1,5 @@
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- model_path=/mnt/general/share/model/Qwen/Qwen2.5-3B-Instruct
+- trainer.experiment_name=sudoku_3b_action1_abstraction

outputs/2026-06-09/17-01-43/.hydra/config.yaml

@@ -0,0 +1,1048 @@
+actor_rollout_ref:
+  actor:
+    optim:
+      _target_: verl.workers.config.FSDPOptimizerConfig
+      lr: 1.0e-06
+      lr_warmup_steps_ratio: 0.0
+      total_training_steps: -1
+      weight_decay: 0.01
+      lr_warmup_steps: -1
+      betas:
+      - 0.9
+      - 0.999
+      clip_grad: 1.0
+      min_lr_ratio: 0.0
+      num_cycles: 0.5
+      warmup_style: constant
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    _target_: verl.workers.config.FSDPActorConfig
+    strategy: fsdp
+    ppo_mini_batch_size: ${ppo_mini_batch_size}
+    ppo_micro_batch_size: null
+    ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+    use_dynamic_bsz: false
+    ppo_max_token_len_per_gpu: 16384
+    clip_ratio: 0.2
+    clip_ratio_low: 0.2
+    clip_ratio_high: 0.28
+    freeze_vision_tower: false
+    policy_loss:
+      _target_: verl.workers.config.PolicyLossConfig
+      loss_mode: vanilla
+      clip_cov_ratio: 0.0002
+      clip_cov_lb: 1.0
+      clip_cov_ub: 5.0
+      kl_cov_ratio: 0.0002
+      ppo_kl_coef: 0.1
+    clip_ratio_c: 3.0
+    loss_agg_mode: token-mean
+    entropy_coeff: 0.001
+    tis_imp_ratio_cap: -1
+    use_kl_loss: false
+    use_torch_compile: true
+    kl_loss_coef: 0.0
+    kl_loss_type: kl
+    ppo_epochs: 1
+    shuffle: false
+    checkpoint:
+      _target_: verl.trainer.config.CheckpointConfig
+      save_contents:
+      - model
+      - optimizer
+      - extra
+      load_contents: ${.save_contents}
+      async_save: false
+    use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: false
+      all_ranks: false
+      ranks: []
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config:
+        nsys:
+          _target_: verl.utils.profiler.config.NsightToolConfig
+          discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+        npu:
+          _target_: verl.utils.profiler.config.NPUToolConfig
+          contents: []
+          level: level1
+          analysis: true
+          discrete: false
+        torch:
+          _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+          step_start: 0
+          step_end: null
+        torch_memory:
+          _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+          trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+          stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+    grad_clip: 1.0
+    ulysses_sequence_parallel_size: 1
+    entropy_from_logits_with_chunking: false
+    entropy_checkpointing: false
+    use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+    use_ref: true
+    grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+    filter_loss_scaling: none
+  ref:
+    strategy: ${actor_rollout_ref.actor.strategy}
+    use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+    log_prob_micro_batch_size: null
+    log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+    log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+    log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: false
+      all_ranks: false
+      ranks: []
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config:
+        nsys:
+          _target_: verl.utils.profiler.config.NsightToolConfig
+          discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+        npu:
+          _target_: verl.utils.profiler.config.NPUToolConfig
+          contents: []
+          level: level1
+          analysis: true
+          discrete: false
+        torch:
+          _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+          step_start: 0
+          step_end: null
+        torch_memory:
+          _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+          trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+          stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    model: null
+    ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+    entropy_from_logits_with_chunking: false
+    entropy_checkpointing: false
+  rollout:
+    _target_: verl.workers.config.RolloutConfig
+    name: vllm
+    mode: sync
+    temperature: 1
+    top_k: -1
+    top_p: 1
+    prompt_length: 1
+    response_length: 400
+    dtype: bfloat16
+    gpu_memory_utilization: 0.7
+    ignore_eos: false
+    enforce_eager: true
+    cudagraph_capture_sizes: null
+    free_cache_engine: true
+    tensor_model_parallel_size: 1
+    data_parallel_size: 1
+    expert_parallel_size: 1
+    max_num_batched_tokens: 16384
+    max_model_len: 16384
+    max_num_seqs: 1024
+    enable_chunked_prefill: true
+    enable_prefix_caching: true
+    load_format: auto
+    log_prob_micro_batch_size: null
+    log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+    log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+    log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+    disable_log_stats: true
+    do_sample: true
+    'n': 1
+    over_sample_rate: 0
+    multi_stage_wake_up: false
+    engine_kwargs:
+      vllm: {}
+      sglang: {}
+    val_kwargs:
+      _target_: verl.workers.config.SamplingConfig
+      top_k: -1
+      top_p: 1.0
+      temperature: 0.5
+      'n': 1
+      do_sample: true
+    multi_turn:
+      _target_: verl.workers.config.MultiTurnConfig
+      enable: false
+      max_assistant_turns: null
+      tool_config_path: null
+      max_user_turns: null
+      max_parallel_calls: 1
+      max_tool_response_length: 256
+      tool_response_truncate_side: middle
+      interaction_config_path: null
+      use_inference_chat_template: false
+      tokenization_sanity_check_mode: strict
+      format: hermes
+      num_repeat_rollouts: null
+    calculate_log_probs: false
+    agent:
+      _target_: verl.workers.config.AgentLoopConfig
+      num_workers: 8
+      agent_loop_config_path: null
+      custom_async_server:
+        _target_: verl.workers.config.CustomAsyncServerConfig
+        path: null
+        name: null
+    update_weights_bucket_megabytes: 512
+    trace:
+      _target_: verl.workers.config.TraceConfig
+      backend: null
+      token2text: false
+    skip_rollout: false
+    skip_dump_dir: /tmp/rollout_dump
+    skip_tokenizer_init: true
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+      all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+      ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+    layered_summon: false
+    rollout_filter_value: 0.9
+    rollout_filter_strategy: top_p
+    rollout_filter_type: largest
+    rollout_filter_include_zero: true
+    rollout_filter_top_p_prob_mode: linear
+    rollout_filter_selection_eps: 0.01
+    rollout_filter_empty_stop_steps: 5
+    rollout_filter_metric: reward_variance
+    gradient_analysis_num_buckets: 6
+    gradient_analysis_bucket_mode: quantile
+  model:
+    _target_: verl.workers.config.HFModelConfig
+    path: ${model_path}
+    hf_config_path: null
+    tokenizer_path: null
+    use_shm: false
+    trust_remote_code: false
+    custom_chat_template: null
+    external_lib: null
+    override_config: {}
+    enable_gradient_checkpointing: true
+    enable_activation_offload: false
+    use_remove_padding: false
+    lora_rank: ${lora.rank}
+    lora_alpha: ${lora.alpha}
+    target_modules: ${lora.target_modules}
+    exclude_modules: null
+    use_liger: false
+    use_fused_kernels: false
+    fused_kernel_options:
+      impl_backend: torch
+  hybrid_engine: true
+  nccl_timeout: 600
+data:
+  tokenizer: null
+  use_shm: false
+  train_files: ~/data/rlhf/gsm8k/train.parquet
+  val_files: ~/data/rlhf/gsm8k/test.parquet
+  prompt_key: prompt
+  reward_fn_key: data_source
+  max_prompt_length: null
+  max_response_length: null
+  train_batch_size: null
+  val_batch_size: null
+  return_raw_input_ids: false
+  return_raw_chat: false
+  return_full_prompt: false
+  shuffle: true
+  dataloader_num_workers: 8
+  validation_shuffle: false
+  filter_overlong_prompts: false
+  filter_overlong_prompts_workers: 1
+  truncation: error
+  image_key: images
+  video_key: videos
+  trust_remote_code: false
+  custom_cls:
+    path: null
+    name: null
+  return_multi_modal_inputs: true
+  sampler:
+    class_path: null
+    class_name: null
+  datagen:
+    path: null
+    name: null
+  apply_chat_template_kwargs: {}
+critic:
+  optim:
+    _target_: verl.workers.config.FSDPOptimizerConfig
+    lr: 1.0e-05
+    lr_warmup_steps_ratio: 0.0
+    total_training_steps: -1
+    weight_decay: 0.01
+    lr_warmup_steps: -1
+    betas:
+    - 0.9
+    - 0.999
+    clip_grad: 1.0
+    min_lr_ratio: 0.0
+    num_cycles: 0.5
+    warmup_style: constant
+  model:
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    path: ${model_path}
+    tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+    override_config: {}
+    external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+    trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+    _target_: verl.workers.config.FSDPCriticModelCfg
+    use_shm: false
+    enable_gradient_checkpointing: true
+    enable_activation_offload: false
+    use_remove_padding: false
+    lora_rank: ${lora.rank}
+    lora_alpha: ${lora.alpha}
+    target_modules: ${lora.target_modules}
+  _target_: verl.workers.config.FSDPCriticConfig
+  rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+  strategy: fsdp
+  enable: null
+  ppo_mini_batch_size: ${ppo_mini_batch_size}
+  ppo_micro_batch_size: null
+  ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+  use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+  ppo_max_token_len_per_gpu: 32768
+  forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+  ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+  shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+  cliprange_value: 0.5
+  loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+  checkpoint:
+    _target_: verl.trainer.config.CheckpointConfig
+    save_contents:
+    - model
+    - optimizer
+    - extra
+    load_contents: ${.save_contents}
+    async_save: false
+  profiler:
+    _target_: verl.utils.profiler.ProfilerConfig
+    tool: ${oc.select:global_profiler.tool,null}
+    enable: false
+    all_ranks: false
+    ranks: []
+    save_path: ${oc.select:global_profiler.save_path,null}
+    tool_config:
+      nsys:
+        _target_: verl.utils.profiler.config.NsightToolConfig
+        discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+      npu:
+        _target_: verl.utils.profiler.config.NPUToolConfig
+        contents: []
+        level: level1
+        analysis: true
+        discrete: false
+      torch:
+        _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+        step_start: 0
+        step_end: null
+      torch_memory:
+        _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+        trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+        stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+  forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+  forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+  ulysses_sequence_parallel_size: 1
+  grad_clip: 1.0
+reward_model:
+  enable: false
+  enable_resource_pool: false
+  n_gpus_per_node: 0
+  nnodes: 0
+  strategy: fsdp
+  model:
+    input_tokenizer: ${actor_rollout_ref.model.path}
+    path: ~/models/FsfairX-LLaMA3-RM-v0.1
+    external_lib: ${actor_rollout_ref.model.external_lib}
+    trust_remote_code: false
+    use_shm: false
+    use_remove_padding: false
+    use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+  micro_batch_size: null
+  micro_batch_size_per_gpu: null
+  max_length: null
+  use_dynamic_bsz: ${critic.use_dynamic_bsz}
+  forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+  reward_manager: naive
+  launch_reward_fn_async: false
+  sandbox_fusion:
+    url: null
+    max_concurrent: 64
+    memory_limit_mb: 1024
+  profiler:
+    _target_: verl.utils.profiler.ProfilerConfig
+    tool: ${oc.select:global_profiler.tool,null}
+    enable: false
+    all_ranks: false
+    ranks: []
+    save_path: ${oc.select:global_profiler.save_path,null}
+    tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+  ulysses_sequence_parallel_size: 1
+custom_reward_function:
+  path: null
+  name: compute_score
+algorithm:
+  _target_: verl.trainer.config.AlgoConfig
+  gamma: 1.0
+  lam: 1.0
+  adv_estimator: gae
+  norm_adv_by_std_in_grpo: true
+  use_kl_in_reward: false
+  kl_penalty: kl
+  kl_ctrl:
+    _target_: verl.trainer.config.KLControlConfig
+    type: fixed
+    kl_coef: 0.0
+    horizon: 10000
+    target_kl: 0.1
+  use_pf_ppo: false
+  pf_ppo:
+    reweight_method: pow
+    weight_pow: 2.0
+  high_level_gamma: 0.95
+  bi_level_gae: false
+  zero_task_advantage: false
+  soft_advantage_reweight: false
+trainer:
+  balance_batch: true
+  total_epochs: 30
+  total_training_steps: 200
+  project_name: ragen
+  experiment_name: sokoban_3b_box1_withthink_sa
+  logger:
+  - console
+  - wandb
+  log_val_generations: 0
+  rollout_data_dir: null
+  validation_data_dir: null
+  nnodes: 1
+  n_gpus_per_node: 8
+  save_freq: -1
+  esi_redundant_time: 0
+  resume_mode: auto
+  resume_from_path: null
+  val_before_train: true
+  val_only: false
+  test_freq: 10
+  critic_warmup: 0
+  default_hdfs_dir: null
+  del_local_ckpt_after_load: false
+  default_local_dir: checkpoints/${trainer.project_name}/${trainer.experiment_name}
+  max_actor_ckpt_to_keep: 1
+  max_critic_ckpt_to_keep: 1
+  ray_wait_register_center_timeout: 300
+  device: cuda
+  use_legacy_worker_impl: auto
+  local_log_dir: results/
+  validation_steps: 1
+  generations_to_log_to_wandb:
+    val: 20
+  log_group_rv_table: false
+  gradient_analysis_mode: false
+  gradient_analysis_every: 50
+  gradient_analysis_env_groups: null
+  gradient_analysis_group_size: null
+  gradient_analysis_log_prefilter: false
+  gradient_analysis_only: false
+  exit_after_gradient_analysis: false
+global_profiler:
+  _target_: verl.utils.profiler.ProfilerConfig
+  tool: null
+  steps: null
+  profile_continuous_steps: false
+  save_path: outputs/profile
+  global_tool_config:
+    nsys:
+      _target_: verl.utils.profiler.config.NsightToolConfig
+      discrete: false
+      controller_nsight_options:
+        trace: cuda,nvtx,cublas,ucx
+        cuda-memory-usage: 'true'
+        cuda-graph-trace: graph
+      worker_nsight_options:
+        trace: cuda,nvtx,cublas,ucx
+        cuda-memory-usage: 'true'
+        cuda-graph-trace: graph
+        capture-range: cudaProfilerApi
+        capture-range-end: null
+        kill: none
+    torch_memory:
+      trace_alloc_max_entries: 100000
+      stack_depth: 32
+      context: all
+      stacks: all
+      kw_args: {}
+ray_kwargs:
+  ray_init:
+    num_cpus: null
+  timeline_json_file: null
+custom_envs:
+  SimpleSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 20
+    env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+      \ when reasoning:\n1. First compare the box position with the target position;\
+      \ the useful push directions are usually the directions that reduce their row/column\
+      \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+      \ push direction. A move that only repositions the player can be useful if it\
+      \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+      \ dead end unless that square is the target or clearly on the only path to the\
+      \ target.\n4. Prefer short plans that move the single box steadily toward the\
+      \ target; avoid wandering moves that do not improve player position or box position.\n\
+      5. If the box and target are aligned in the same row or column, try to keep\
+      \ the box on that line and push along it.\n6. If they are not aligned, first\
+      \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+      7. Check that after each push, the player can still reach the next required\
+      \ pushing side of the box.\n8. Output only the required XML-like format and\
+      \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+      \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+      \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+      \ pull a box. \nThe answer should be a sequence of actions, like <answer>Right\
+      \ || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 2
+      max_steps: 100
+  LargerSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+      \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+      \ you can push it by moving in the same direction. \nYou cannot push a box through\
+      \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+      \ like <answer>Right || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 8
+      dim_y: 8
+      num_boxes: 2
+      max_steps: 100
+      search_depth: 10
+  SokobanDifferentGridVocab:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+      \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+      \ you can push it by moving in the same direction. \nYou cannot push a box through\
+      \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+      \ like <answer>Right || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      search_depth: 30
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      grid_lookup:
+        0: W
+        1: .
+        2: G
+        3: C
+        4: B
+        5: A
+        6: '@'
+      grid_vocab:
+        W: wall
+        .: empty
+        G: target
+        C: box on target
+        B: box
+        A: player
+        '@': player on target
+  CoordSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 20
+    env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+      \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+      \ the zero-indexed coordinates of the player, each box, and each target. \n\
+      Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+      \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+      \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+      \ pull a box.\nThe answer should be a sequence of actions, like <answer>Right\
+      \ || Right || Up</answer>.\n"
+    max_tokens: 120
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      observation_format: grid_coord
+  VisualSimpleSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: You are solving the Sokoban puzzle. You are the player and you
+      need to push all boxes to targets. When you are right next to a box, you can
+      push it by moving in the same direction. You cannot push a box through a wall,
+      and you cannot pull a box. The answer should be a sequence of actions, like
+      <answer>Right || Right || Up</answer>
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      render_mode: rgb_array
+  Alfworld:
+    env_type: alfworld
+    max_actions_per_traj: 50
+    parallel_friendly: false
+    max_workers: 1
+    env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+      Complete household tasks by navigating and interacting with objects.
+
+
+      You should first reason step-by-step about the current situation. This reasoning
+      process MUST be enclosed within <think> </think> tags.
+
+      Once you''ve finished your reasoning, you should choose an admissible action
+      for current step and present it within <answer>...</answer> tags.
+
+      '
+    max_tokens: 512
+    env_config:
+      eval_dataset: eval_in_distribution
+  AlfworldOOD:
+    env_type: alfworld
+    max_actions_per_traj: 50
+    parallel_friendly: false
+    max_workers: 1
+    env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+      Complete household tasks by navigating and interacting with objects.
+
+
+      You should first reason step-by-step about the current situation. This reasoning
+      process MUST be enclosed within <think> </think> tags.
+
+      Once you''ve finished your reasoning, you should choose an admissible action
+      for current step and present it within <answer>...</answer> tags.
+
+      '
+    max_tokens: 512
+    env_config:
+      eval_dataset: eval_out_of_distribution
+  Countdown:
+    env_type: countdown
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving the Countdown puzzle. You should use the num
+      list to create an equation that equals the target. Example answer format: <think>
+      To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+      = 4. So the answer is 2 + 5 - 3 = 4. </think><answer>2 + 5 - 3</answer>'
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config: null
+  Bandit:
+    env_type: bandit
+    max_actions_per_traj: 1
+    env_instruction: ''
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      split: train
+  BanditTest:
+    env_type: bandit
+    max_actions_per_traj: 1
+    env_instruction: ''
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      split: test
+  DeepCoder:
+    env_type: deepcoder
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving a coding task. Provide a complete Python function
+      solution only. Format: <answer>...</answer>'
+    max_tokens: 8000
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 1
+  FrozenLake:
+    env_type: frozen_lake
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+      go to the target. You may move to the unintended direction due to the slippery
+      ice. Example answer format: <think>To forbid the hole and go to the target,
+      I should go left then go up.</think><answer>Left || Up</answer>'
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      success_rate: 0.8
+  CoordFrozenLake:
+    env_type: frozen_lake
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+      both a symbol grid and zero-indexed coordinates for the start, goal, player,
+      and any holes.
+
+      Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+      (5, 5).
+
+      Beware that the ice is slippery, so the agent might slide and end up in an unintended
+      tile.
+
+      Respond with a sequence of actions such as <answer>Left || Up || Up</answer>.
+
+      '
+    max_tokens: 120
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      observation_format: grid_coord
+      success_rate: 0.8
+  MetamathQA:
+    env_type: metamathqa
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving Math problems. '
+    max_tokens: 100
+    env_config: null
+  WebShopFull:
+    env_type: webshop
+    max_actions_per_traj: 15
+    env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+      environment.
+    max_tokens: 200
+    env_config:
+      dataset: full
+  WebShop:
+    env_type: webshop
+    max_actions_per_traj: 9
+    env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+      a product that close to the production description. You need to search, read
+      the search results, pick a product, choose the size and color and buy. You should
+      only choose action from the available actions list provided later.  Example
+      process: I need a gingko light and 20x20 pillow cover that is hand painted.
+      First search[gingko light 20x20 pillow cover hand painted], answer format: <answer>search[blanket
+      with fleece throw]</answer>. Valid answer is search[<keywords>] or click[<clickable>].'
+    max_tokens: 200
+    env_config:
+      dataset: small
+  Lean:
+    env_type: lean
+    max_actions_per_traj: 30
+    env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+      propose a sequence of tactics that completes the proof. Think step by step about
+      which tactics to apply next. Provide tactics separated by '||', for example
+      <answer>intro || simp || rfl</answer>.
+    max_tokens: 512
+    parallel_friendly: true
+    max_workers: 32
+    env_config: null
+  SimpleSudoku:
+    env_type: sudoku
+    max_actions_per_traj: 20
+    env_instruction: 'You are a careful 4x4 Sudoku solver. Use these reusable abstractions
+      when reasoning:
+
+      1. In <think>, explain the constraint logic behind the move, not just the final
+      placement. Mention which row, column, or 2x2 box makes the move safe or forced.
+
+      2. Treat each move as a constraint-preserving placement: place a number only
+      if it does not already appear in the same row, column, or 2x2 box.
+
+      3. First look for highly forced cells. If an empty cell has only one legal candidate
+      after checking its row, column, and box, fill it immediately and explain why
+      other numbers are excluded.
+
+      4. If no cell is obviously forced, scan each row, column, and 2x2 box for missing
+      numbers. If a missing number can go in only one empty position within that unit,
+      place it there and state that unit-level reason.
+
+      5. Prefer moves that reduce uncertainty and create new forced cells for the
+      next turn. A good move should make the remaining puzzle more constrained, not
+      more ambiguous.
+
+      6. Solve incrementally: choose exactly one placement, explain it briefly in
+      <think>, then output that one move in <answer>.
+
+      7. Never modify bracketed initial cells or already-filled cells. Only place
+      numbers into dots.
+
+      8. Avoid exploratory guesses when a forced move exists. In this environment,
+      reliable progress usually comes from constraint propagation rather than trial-and-error.
+
+      9. If a previous move was invalid or the board did not change, do not repeat
+      the same placement. Recompute legal candidates and explain the corrected constraint-consistent
+      choice.
+
+      10. Use row, column, and box agreement as confidence: the strongest placements
+      are those supported by multiple constraints at once.
+
+      11. Keep <think> concise but meaningful: identify the target cell, list or compare
+      its legal candidates, and give the decisive constraint.
+
+      12. Output only the required XML-like format and choose valid Sudoku placements.
+
+
+      You are solving a Sudoku puzzle. Fill in the grid so that every row, column,
+      and 2x2 box contains the numbers 1-4 without repetition.
+
+      Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+      shown as dots (.).
+
+      Place numbers one at a time using the format: <answer>place 1 at row 2 col 3</answer>
+
+      Always output: <think> [brief constraint-based reasoning] </think> <answer>
+      [one placement] </answer>
+
+      The environment will provide feedback on valid/invalid moves and show conflicts
+      if any occur.
+
+      '
+    max_tokens: 150
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      grid_size: 4
+      difficulty: easy
+      render_format: with_feedback
+      show_conflicts: false
+      show_valid_numbers: false
+      max_steps: 20
+  MediumSudoku:
+    env_type: sudoku
+    max_actions_per_traj: 30
+    env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+      row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+      Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+      shown as dots (.).
+
+      Place numbers one at a time using the format: <answer>place 5 at row 2 col 3</answer>
+      or <answer>2,3,5</answer>
+
+      The environment will provide feedback on valid/invalid moves and show conflicts
+      if any occur.
+
+      '
+    max_tokens: 150
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      grid_size: 9
+      difficulty: medium
+      render_format: with_feedback
+      show_conflicts: true
+      show_valid_numbers: true
+      max_steps: 81
+  SearchQA:
+    env_type: search
+    max_actions_per_traj: 10
+    env_instruction: "You are a search agent answering questions by searching for\
+      \ information.\nUse search[your query] to find relevant documents, and finish[your\
+      \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+      \ about the current situation. This reasoning process MUST be enclosed within\
+      \ <think> </think> tags.\nThen provide your action within <answer>...</answer>\
+      \ tags.\n\nExamples:\n  <think>I need to find information about Ben Platt's\
+      \ father.</think><answer>search[Ben Platt father parent]</answer>\n  <think>Based\
+      \ on the search results, Ben Platt's father is Henry Platt.</think><answer>finish[Henry\
+      \ Platt]</answer>\n"
+    max_tokens: 300
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 10
+      max_search_results: 5
+  SearchQAMock:
+    env_type: search
+    max_actions_per_traj: 10
+    env_instruction: "You are a search agent answering questions by searching for\
+      \ information.\nUse search[your query] to find relevant documents, and finish[your\
+      \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+      \ about the current situation. This reasoning process MUST be enclosed within\
+      \ <think> </think> tags.\nThen provide your action within <answer>...</answer>\
+      \ tags.\n\nExamples:\n  <think>I need to find information about Ben Platt's\
+      \ father.</think><answer>search[Ben Platt father parent]</answer>\n  <think>Based\
+      \ on the search results, Ben Platt's father is Henry Platt.</think><answer>finish[Henry\
+      \ Platt]</answer>\n"
+    max_tokens: 300
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 10
+      max_search_results: 5
+      mock_mode: true
+  game_2048:
+    env_type: game_2048
+    max_actions_per_traj: 700
+    env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+      by sliding Up, Right, Down, or Left.
+
+      If a move is invalid (no tiles move), a small penalty is applied. Respond with
+      a single action.
+
+      Example: <answer>Up</answer>
+
+      '
+    max_tokens: 8192
+    env_config: null
+  rubikscube:
+    env_type: rubikscube
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+      is to restore the cube so that each of the faces consists of a single, unique
+      color.
+
+      Available actions use standard Singmaster notation for face rotations: U, U'',
+      D, D'', L, L'', R, R'', F, F'', B, B''.
+
+      - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+      - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+      prime ('') means 90° counter-clockwise (e.g., "R''").
+
+      Respond with a sequence of actions separated by "||".
+
+      Example: <answer>U</answer>
+
+      '
+    max_tokens: 96
+    env_config:
+      scramble_depth: 1
+      max_steps: 7
+      render_mode: text
+system:
+  CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+  train: 10000
+  val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_sokoban_box2_withthink_sa
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+  rank: 0
+  alpha: 64
+  target_modules: all-linear
+agent_proxy:
+  context_window_mode: full
+  max_context_window: -1
+  batch_adjust_mode: copy
+  max_turn: 20
+  action_sep: '||'
+  max_actions_per_turn: 1
+  use_turn_scores: false
+  enable_think: true
+  reward_normalization:
+    grouping: state
+    method: identity
+collapse_detection:
+  compute_freq: 5
+  micro_batch_size: 128
+  first_turn_enabled: true
+  multi_turn_enabled: true
+  num_samples: 64
+es_manager:
+  format_penalty: -0.1
+  train:
+    env_groups: 8
+    group_size: 16
+    env_configs:
+      tags:
+      - CoordSokoban
+      n_groups:
+      - 8
+  val:
+    env_groups: 512
+    group_size: 1
+    env_configs:
+      tags:
+      - CoordSokoban
+      n_groups:
+      - 512
+ctx_manager:
+  generation:
+    gen_config:
+      response_length: ${actor_rollout_ref.rollout.response_length}
+      temperature: ${actor_rollout_ref.rollout.temperature}
+      top_p: ${actor_rollout_ref.rollout.top_p}
+      top_k: ${actor_rollout_ref.rollout.top_k}
+      kwargs: null

outputs/2026-06-09/17-01-43/.hydra/overrides.yaml

@@ -0,0 +1,5 @@
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_sokoban_box2_withthink_sa
+- trainer.experiment_name=sokoban_3b_box1_withthink_sa

outputs/2026-06-09/20-37-55/.hydra/hydra.yaml

@@ -0,0 +1,178 @@
+hydra:
+  run:
+    dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+  sweep:
+    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath:
+  - pkg://verl.trainer.config
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task:
+    - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+    - actor_rollout_ref.rollout.rollout_filter_value=0.9
+    - trainer.total_training_steps=200
+    - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_sokoban_box2_withthink_sas
+    - trainer.experiment_name=sokoban_3b_box1_withthink_sas
+  job:
+    name: train
+    chdir: null
+    override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_sokoban_box2_withthink_sas,trainer.experiment_name=sokoban_3b_box1_withthink_sas,trainer.total_training_steps=200
+    id: ???
+    num: ???
+    config_name: _2_sokoban
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /mnt/general/wanghy/RAGEN_v2
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /mnt/general/wanghy/RAGEN_v2/config
+      schema: file
+      provider: main
+    - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+      schema: file
+      provider: command-line
+    - path: verl.trainer.config
+      schema: pkg
+      provider: hydra.searchpath in main
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-09/20-37-55
+    choices:
+      reward_model: dp_reward_model
+      critic: dp_critic
+      critic/../engine@critic.model.fsdp_config: fsdp
+      critic/../optim@critic.optim: fsdp
+      model@actor_rollout_ref.model: hf_model
+      rollout@actor_rollout_ref.rollout: rollout
+      ref@actor_rollout_ref.ref: dp_ref
+      ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+      data: legacy_data
+      actor@actor_rollout_ref.actor: dp_actor
+      actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+      actor/../optim@actor_rollout_ref.actor.optim: fsdp
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

outputs/2026-06-09/20-37-55/.hydra/overrides.yaml

@@ -0,0 +1,5 @@
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_sokoban_box2_withthink_sas
+- trainer.experiment_name=sokoban_3b_box1_withthink_sas

outputs/2026-06-12/14-59-00/.hydra/config.yaml

@@ -0,0 +1,1048 @@
+actor_rollout_ref:
+  actor:
+    optim:
+      _target_: verl.workers.config.FSDPOptimizerConfig
+      lr: 1.0e-06
+      lr_warmup_steps_ratio: 0.0
+      total_training_steps: -1
+      weight_decay: 0.01
+      lr_warmup_steps: -1
+      betas:
+      - 0.9
+      - 0.999
+      clip_grad: 1.0
+      min_lr_ratio: 0.0
+      num_cycles: 0.5
+      warmup_style: constant
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    _target_: verl.workers.config.FSDPActorConfig
+    strategy: fsdp
+    ppo_mini_batch_size: ${ppo_mini_batch_size}
+    ppo_micro_batch_size: null
+    ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+    use_dynamic_bsz: false
+    ppo_max_token_len_per_gpu: 16384
+    clip_ratio: 0.2
+    clip_ratio_low: 0.2
+    clip_ratio_high: 0.28
+    freeze_vision_tower: false
+    policy_loss:
+      _target_: verl.workers.config.PolicyLossConfig
+      loss_mode: vanilla
+      clip_cov_ratio: 0.0002
+      clip_cov_lb: 1.0
+      clip_cov_ub: 5.0
+      kl_cov_ratio: 0.0002
+      ppo_kl_coef: 0.1
+    clip_ratio_c: 3.0
+    loss_agg_mode: token-mean
+    entropy_coeff: 0.001
+    tis_imp_ratio_cap: -1
+    use_kl_loss: false
+    use_torch_compile: true
+    kl_loss_coef: 0.0
+    kl_loss_type: kl
+    ppo_epochs: 1
+    shuffle: false
+    checkpoint:
+      _target_: verl.trainer.config.CheckpointConfig
+      save_contents:
+      - model
+      - optimizer
+      - extra
+      load_contents: ${.save_contents}
+      async_save: false
+    use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: false
+      all_ranks: false
+      ranks: []
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config:
+        nsys:
+          _target_: verl.utils.profiler.config.NsightToolConfig
+          discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+        npu:
+          _target_: verl.utils.profiler.config.NPUToolConfig
+          contents: []
+          level: level1
+          analysis: true
+          discrete: false
+        torch:
+          _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+          step_start: 0
+          step_end: null
+        torch_memory:
+          _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+          trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+          stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+    grad_clip: 1.0
+    ulysses_sequence_parallel_size: 1
+    entropy_from_logits_with_chunking: false
+    entropy_checkpointing: false
+    use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+    use_ref: true
+    grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+    filter_loss_scaling: none
+  ref:
+    strategy: ${actor_rollout_ref.actor.strategy}
+    use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+    log_prob_micro_batch_size: null
+    log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+    log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+    log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: false
+      all_ranks: false
+      ranks: []
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config:
+        nsys:
+          _target_: verl.utils.profiler.config.NsightToolConfig
+          discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+        npu:
+          _target_: verl.utils.profiler.config.NPUToolConfig
+          contents: []
+          level: level1
+          analysis: true
+          discrete: false
+        torch:
+          _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+          step_start: 0
+          step_end: null
+        torch_memory:
+          _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+          trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+          stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    model: null
+    ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+    entropy_from_logits_with_chunking: false
+    entropy_checkpointing: false
+  rollout:
+    _target_: verl.workers.config.RolloutConfig
+    name: vllm
+    mode: sync
+    temperature: 1
+    top_k: -1
+    top_p: 1
+    prompt_length: 1
+    response_length: 500
+    dtype: bfloat16
+    gpu_memory_utilization: 0.7
+    ignore_eos: false
+    enforce_eager: true
+    cudagraph_capture_sizes: null
+    free_cache_engine: true
+    tensor_model_parallel_size: 1
+    data_parallel_size: 1
+    expert_parallel_size: 1
+    max_num_batched_tokens: 16384
+    max_model_len: 16384
+    max_num_seqs: 1024
+    enable_chunked_prefill: true
+    enable_prefix_caching: true
+    load_format: auto
+    log_prob_micro_batch_size: null
+    log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+    log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+    log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+    disable_log_stats: true
+    do_sample: true
+    'n': 1
+    over_sample_rate: 0
+    multi_stage_wake_up: false
+    engine_kwargs:
+      vllm: {}
+      sglang: {}
+    val_kwargs:
+      _target_: verl.workers.config.SamplingConfig
+      top_k: -1
+      top_p: 1.0
+      temperature: 0.5
+      'n': 1
+      do_sample: true
+    multi_turn:
+      _target_: verl.workers.config.MultiTurnConfig
+      enable: false
+      max_assistant_turns: null
+      tool_config_path: null
+      max_user_turns: null
+      max_parallel_calls: 1
+      max_tool_response_length: 256
+      tool_response_truncate_side: middle
+      interaction_config_path: null
+      use_inference_chat_template: false
+      tokenization_sanity_check_mode: strict
+      format: hermes
+      num_repeat_rollouts: null
+    calculate_log_probs: false
+    agent:
+      _target_: verl.workers.config.AgentLoopConfig
+      num_workers: 8
+      agent_loop_config_path: null
+      custom_async_server:
+        _target_: verl.workers.config.CustomAsyncServerConfig
+        path: null
+        name: null
+    update_weights_bucket_megabytes: 512
+    trace:
+      _target_: verl.workers.config.TraceConfig
+      backend: null
+      token2text: false
+    skip_rollout: false
+    skip_dump_dir: /tmp/rollout_dump
+    skip_tokenizer_init: true
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+      all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+      ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+    layered_summon: false
+    rollout_filter_value: 0.9
+    rollout_filter_strategy: top_p
+    rollout_filter_type: largest
+    rollout_filter_include_zero: true
+    rollout_filter_top_p_prob_mode: linear
+    rollout_filter_selection_eps: 0.01
+    rollout_filter_empty_stop_steps: 5
+    rollout_filter_metric: reward_variance
+    gradient_analysis_num_buckets: 6
+    gradient_analysis_bucket_mode: quantile
+  model:
+    _target_: verl.workers.config.HFModelConfig
+    path: ${model_path}
+    hf_config_path: null
+    tokenizer_path: null
+    use_shm: false
+    trust_remote_code: false
+    custom_chat_template: null
+    external_lib: null
+    override_config: {}
+    enable_gradient_checkpointing: true
+    enable_activation_offload: false
+    use_remove_padding: false
+    lora_rank: ${lora.rank}
+    lora_alpha: ${lora.alpha}
+    target_modules: ${lora.target_modules}
+    exclude_modules: null
+    use_liger: false
+    use_fused_kernels: false
+    fused_kernel_options:
+      impl_backend: torch
+  hybrid_engine: true
+  nccl_timeout: 600
+data:
+  tokenizer: null
+  use_shm: false
+  train_files: ~/data/rlhf/gsm8k/train.parquet
+  val_files: ~/data/rlhf/gsm8k/test.parquet
+  prompt_key: prompt
+  reward_fn_key: data_source
+  max_prompt_length: null
+  max_response_length: null
+  train_batch_size: null
+  val_batch_size: null
+  return_raw_input_ids: false
+  return_raw_chat: false
+  return_full_prompt: false
+  shuffle: true
+  dataloader_num_workers: 8
+  validation_shuffle: false
+  filter_overlong_prompts: false
+  filter_overlong_prompts_workers: 1
+  truncation: error
+  image_key: images
+  video_key: videos
+  trust_remote_code: false
+  custom_cls:
+    path: null
+    name: null
+  return_multi_modal_inputs: true
+  sampler:
+    class_path: null
+    class_name: null
+  datagen:
+    path: null
+    name: null
+  apply_chat_template_kwargs: {}
+critic:
+  optim:
+    _target_: verl.workers.config.FSDPOptimizerConfig
+    lr: 1.0e-05
+    lr_warmup_steps_ratio: 0.0
+    total_training_steps: -1
+    weight_decay: 0.01
+    lr_warmup_steps: -1
+    betas:
+    - 0.9
+    - 0.999
+    clip_grad: 1.0
+    min_lr_ratio: 0.0
+    num_cycles: 0.5
+    warmup_style: constant
+  model:
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    path: ${model_path}
+    tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+    override_config: {}
+    external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+    trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+    _target_: verl.workers.config.FSDPCriticModelCfg
+    use_shm: false
+    enable_gradient_checkpointing: true
+    enable_activation_offload: false
+    use_remove_padding: false
+    lora_rank: ${lora.rank}
+    lora_alpha: ${lora.alpha}
+    target_modules: ${lora.target_modules}
+  _target_: verl.workers.config.FSDPCriticConfig
+  rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+  strategy: fsdp
+  enable: null
+  ppo_mini_batch_size: ${ppo_mini_batch_size}
+  ppo_micro_batch_size: null
+  ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+  use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+  ppo_max_token_len_per_gpu: 32768
+  forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+  ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+  shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+  cliprange_value: 0.5
+  loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+  checkpoint:
+    _target_: verl.trainer.config.CheckpointConfig
+    save_contents:
+    - model
+    - optimizer
+    - extra
+    load_contents: ${.save_contents}
+    async_save: false
+  profiler:
+    _target_: verl.utils.profiler.ProfilerConfig
+    tool: ${oc.select:global_profiler.tool,null}
+    enable: false
+    all_ranks: false
+    ranks: []
+    save_path: ${oc.select:global_profiler.save_path,null}
+    tool_config:
+      nsys:
+        _target_: verl.utils.profiler.config.NsightToolConfig
+        discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+      npu:
+        _target_: verl.utils.profiler.config.NPUToolConfig
+        contents: []
+        level: level1
+        analysis: true
+        discrete: false
+      torch:
+        _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+        step_start: 0
+        step_end: null
+      torch_memory:
+        _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+        trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+        stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+  forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+  forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+  ulysses_sequence_parallel_size: 1
+  grad_clip: 1.0
+reward_model:
+  enable: false
+  enable_resource_pool: false
+  n_gpus_per_node: 0
+  nnodes: 0
+  strategy: fsdp
+  model:
+    input_tokenizer: ${actor_rollout_ref.model.path}
+    path: ~/models/FsfairX-LLaMA3-RM-v0.1
+    external_lib: ${actor_rollout_ref.model.external_lib}
+    trust_remote_code: false
+    use_shm: false
+    use_remove_padding: false
+    use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+  micro_batch_size: null
+  micro_batch_size_per_gpu: null
+  max_length: null
+  use_dynamic_bsz: ${critic.use_dynamic_bsz}
+  forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+  reward_manager: naive
+  launch_reward_fn_async: false
+  sandbox_fusion:
+    url: null
+    max_concurrent: 64
+    memory_limit_mb: 1024
+  profiler:
+    _target_: verl.utils.profiler.ProfilerConfig
+    tool: ${oc.select:global_profiler.tool,null}
+    enable: false
+    all_ranks: false
+    ranks: []
+    save_path: ${oc.select:global_profiler.save_path,null}
+    tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+  ulysses_sequence_parallel_size: 1
+custom_reward_function:
+  path: null
+  name: compute_score
+algorithm:
+  _target_: verl.trainer.config.AlgoConfig
+  gamma: 1.0
+  lam: 1.0
+  adv_estimator: gae
+  norm_adv_by_std_in_grpo: true
+  use_kl_in_reward: false
+  kl_penalty: kl
+  kl_ctrl:
+    _target_: verl.trainer.config.KLControlConfig
+    type: fixed
+    kl_coef: 0.0
+    horizon: 10000
+    target_kl: 0.1
+  use_pf_ppo: false
+  pf_ppo:
+    reweight_method: pow
+    weight_pow: 2.0
+  high_level_gamma: 0.95
+  bi_level_gae: false
+  zero_task_advantage: false
+  soft_advantage_reweight: false
+trainer:
+  balance_batch: true
+  total_epochs: 30
+  total_training_steps: 200
+  project_name: ragen
+  experiment_name: rubikscube2_withthink_fulltrajc_sa
+  logger:
+  - console
+  - wandb
+  log_val_generations: 0
+  rollout_data_dir: null
+  validation_data_dir: null
+  nnodes: 1
+  n_gpus_per_node: 8
+  save_freq: -1
+  esi_redundant_time: 0
+  resume_mode: auto
+  resume_from_path: null
+  val_before_train: true
+  val_only: false
+  test_freq: 10
+  critic_warmup: 0
+  default_hdfs_dir: null
+  del_local_ckpt_after_load: false
+  default_local_dir: checkpoints/${trainer.project_name}/${trainer.experiment_name}
+  max_actor_ckpt_to_keep: 1
+  max_critic_ckpt_to_keep: 1
+  ray_wait_register_center_timeout: 300
+  device: cuda
+  use_legacy_worker_impl: auto
+  local_log_dir: results/
+  validation_steps: 1
+  generations_to_log_to_wandb:
+    val: 20
+  log_group_rv_table: false
+  gradient_analysis_mode: false
+  gradient_analysis_every: 50
+  gradient_analysis_env_groups: null
+  gradient_analysis_group_size: null
+  gradient_analysis_log_prefilter: false
+  gradient_analysis_only: false
+  exit_after_gradient_analysis: false
+global_profiler:
+  _target_: verl.utils.profiler.ProfilerConfig
+  tool: null
+  steps: null
+  profile_continuous_steps: false
+  save_path: outputs/profile
+  global_tool_config:
+    nsys:
+      _target_: verl.utils.profiler.config.NsightToolConfig
+      discrete: false
+      controller_nsight_options:
+        trace: cuda,nvtx,cublas,ucx
+        cuda-memory-usage: 'true'
+        cuda-graph-trace: graph
+      worker_nsight_options:
+        trace: cuda,nvtx,cublas,ucx
+        cuda-memory-usage: 'true'
+        cuda-graph-trace: graph
+        capture-range: cudaProfilerApi
+        capture-range-end: null
+        kill: none
+    torch_memory:
+      trace_alloc_max_entries: 100000
+      stack_depth: 32
+      context: all
+      stacks: all
+      kw_args: {}
+ray_kwargs:
+  ray_init:
+    num_cpus: null
+  timeline_json_file: null
+custom_envs:
+  SimpleSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 20
+    env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+      \ when reasoning:\n1. First compare the box position with the target position;\
+      \ the useful push directions are usually the directions that reduce their row/column\
+      \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+      \ push direction. A move that only repositions the player can be useful if it\
+      \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+      \ dead end unless that square is the target or clearly on the only path to the\
+      \ target.\n4. Prefer short plans that move the single box steadily toward the\
+      \ target; avoid wandering moves that do not improve player position or box position.\n\
+      5. If the box and target are aligned in the same row or column, try to keep\
+      \ the box on that line and push along it.\n6. If they are not aligned, first\
+      \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+      7. Check that after each push, the player can still reach the next required\
+      \ pushing side of the box.\n8. Output only the required XML-like format and\
+      \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+      \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+      \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+      \ pull a box. \nThe answer should be a sequence of actions, like <answer>Right\
+      \ || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 2
+      max_steps: 100
+  LargerSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+      \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+      \ you can push it by moving in the same direction. \nYou cannot push a box through\
+      \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+      \ like <answer>Right || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 8
+      dim_y: 8
+      num_boxes: 2
+      max_steps: 100
+      search_depth: 10
+  SokobanDifferentGridVocab:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+      \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+      \ you can push it by moving in the same direction. \nYou cannot push a box through\
+      \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+      \ like <answer>Right || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      search_depth: 30
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      grid_lookup:
+        0: W
+        1: .
+        2: G
+        3: C
+        4: B
+        5: A
+        6: '@'
+      grid_vocab:
+        W: wall
+        .: empty
+        G: target
+        C: box on target
+        B: box
+        A: player
+        '@': player on target
+  CoordSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 20
+    env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+      \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+      \ the zero-indexed coordinates of the player, each box, and each target. \n\
+      Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+      \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+      \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+      \ pull a box.\nThe answer should be a sequence of actions, like <answer>Right\
+      \ || Right || Up</answer>.\n"
+    max_tokens: 120
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      observation_format: grid_coord
+  VisualSimpleSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: You are solving the Sokoban puzzle. You are the player and you
+      need to push all boxes to targets. When you are right next to a box, you can
+      push it by moving in the same direction. You cannot push a box through a wall,
+      and you cannot pull a box. The answer should be a sequence of actions, like
+      <answer>Right || Right || Up</answer>
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      render_mode: rgb_array
+  Alfworld:
+    env_type: alfworld
+    max_actions_per_traj: 50
+    parallel_friendly: false
+    max_workers: 1
+    env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+      Complete household tasks by navigating and interacting with objects.
+
+
+      You should first reason step-by-step about the current situation. This reasoning
+      process MUST be enclosed within <think> </think> tags.
+
+      Once you''ve finished your reasoning, you should choose an admissible action
+      for current step and present it within <answer>...</answer> tags.
+
+      '
+    max_tokens: 512
+    env_config:
+      eval_dataset: eval_in_distribution
+  AlfworldOOD:
+    env_type: alfworld
+    max_actions_per_traj: 50
+    parallel_friendly: false
+    max_workers: 1
+    env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+      Complete household tasks by navigating and interacting with objects.
+
+
+      You should first reason step-by-step about the current situation. This reasoning
+      process MUST be enclosed within <think> </think> tags.
+
+      Once you''ve finished your reasoning, you should choose an admissible action
+      for current step and present it within <answer>...</answer> tags.
+
+      '
+    max_tokens: 512
+    env_config:
+      eval_dataset: eval_out_of_distribution
+  Countdown:
+    env_type: countdown
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving the Countdown puzzle. You should use the num
+      list to create an equation that equals the target. Example answer format: <think>
+      To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+      = 4. So the answer is 2 + 5 - 3 = 4. </think><answer>2 + 5 - 3</answer>'
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config: null
+  Bandit:
+    env_type: bandit
+    max_actions_per_traj: 1
+    env_instruction: ''
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      split: train
+  BanditTest:
+    env_type: bandit
+    max_actions_per_traj: 1
+    env_instruction: ''
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      split: test
+  DeepCoder:
+    env_type: deepcoder
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving a coding task. Provide a complete Python function
+      solution only. Format: <answer>...</answer>'
+    max_tokens: 8000
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 1
+  FrozenLake:
+    env_type: frozen_lake
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+      go to the target. You may move to the unintended direction due to the slippery
+      ice. Example answer format: <think>To forbid the hole and go to the target,
+      I should go left then go up.</think><answer>Left || Up</answer>'
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      success_rate: 0.8
+  CoordFrozenLake:
+    env_type: frozen_lake
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+      both a symbol grid and zero-indexed coordinates for the start, goal, player,
+      and any holes.
+
+      Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+      (5, 5).
+
+      Beware that the ice is slippery, so the agent might slide and end up in an unintended
+      tile.
+
+      Respond with a sequence of actions such as <answer>Left || Up || Up</answer>.
+
+      '
+    max_tokens: 120
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      observation_format: grid_coord
+      success_rate: 0.8
+  MetamathQA:
+    env_type: metamathqa
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving Math problems. '
+    max_tokens: 100
+    env_config: null
+  WebShopFull:
+    env_type: webshop
+    max_actions_per_traj: 15
+    env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+      environment.
+    max_tokens: 200
+    env_config:
+      dataset: full
+  WebShop:
+    env_type: webshop
+    max_actions_per_traj: 9
+    env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+      a product that close to the production description. You need to search, read
+      the search results, pick a product, choose the size and color and buy. You should
+      only choose action from the available actions list provided later.  Example
+      process: I need a gingko light and 20x20 pillow cover that is hand painted.
+      First search[gingko light 20x20 pillow cover hand painted], answer format: <answer>search[blanket
+      with fleece throw]</answer>. Valid answer is search[<keywords>] or click[<clickable>].'
+    max_tokens: 200
+    env_config:
+      dataset: small
+  Lean:
+    env_type: lean
+    max_actions_per_traj: 30
+    env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+      propose a sequence of tactics that completes the proof. Think step by step about
+      which tactics to apply next. Provide tactics separated by '||', for example
+      <answer>intro || simp || rfl</answer>.
+    max_tokens: 512
+    parallel_friendly: true
+    max_workers: 32
+    env_config: null
+  SimpleSudoku:
+    env_type: sudoku
+    max_actions_per_traj: 20
+    env_instruction: 'You are a careful 4x4 Sudoku solver. Use these reusable abstractions
+      when reasoning:
+
+      1. In <think>, explain the constraint logic behind the move, not just the final
+      placement. Mention which row, column, or 2x2 box makes the move safe or forced.
+
+      2. Treat each move as a constraint-preserving placement: place a number only
+      if it does not already appear in the same row, column, or 2x2 box.
+
+      3. First look for highly forced cells. If an empty cell has only one legal candidate
+      after checking its row, column, and box, fill it immediately and explain why
+      other numbers are excluded.
+
+      4. If no cell is obviously forced, scan each row, column, and 2x2 box for missing
+      numbers. If a missing number can go in only one empty position within that unit,
+      place it there and state that unit-level reason.
+
+      5. Prefer moves that reduce uncertainty and create new forced cells for the
+      next turn. A good move should make the remaining puzzle more constrained, not
+      more ambiguous.
+
+      6. Solve incrementally: choose exactly one placement, explain it briefly in
+      <think>, then output that one move in <answer>.
+
+      7. Never modify bracketed initial cells or already-filled cells. Only place
+      numbers into dots.
+
+      8. Avoid exploratory guesses when a forced move exists. In this environment,
+      reliable progress usually comes from constraint propagation rather than trial-and-error.
+
+      9. If a previous move was invalid or the board did not change, do not repeat
+      the same placement. Recompute legal candidates and explain the corrected constraint-consistent
+      choice.
+
+      10. Use row, column, and box agreement as confidence: the strongest placements
+      are those supported by multiple constraints at once.
+
+      11. Keep <think> concise but meaningful: identify the target cell, list or compare
+      its legal candidates, and give the decisive constraint.
+
+      12. Output only the required XML-like format and choose valid Sudoku placements.
+
+
+      You are solving a Sudoku puzzle. Fill in the grid so that every row, column,
+      and 2x2 box contains the numbers 1-4 without repetition.
+
+      Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+      shown as dots (.).
+
+      Place numbers one at a time using the format: <answer>place 1 at row 2 col 3</answer>
+
+      Always output: <think> [brief constraint-based reasoning] </think> <answer>
+      [one placement] </answer>
+
+      The environment will provide feedback on valid/invalid moves and show conflicts
+      if any occur.
+
+      '
+    max_tokens: 150
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      grid_size: 4
+      difficulty: easy
+      render_format: with_feedback
+      show_conflicts: false
+      show_valid_numbers: false
+      max_steps: 20
+  MediumSudoku:
+    env_type: sudoku
+    max_actions_per_traj: 30
+    env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+      row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+      Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+      shown as dots (.).
+
+      Place numbers one at a time using the format: <answer>place 5 at row 2 col 3</answer>
+      or <answer>2,3,5</answer>
+
+      The environment will provide feedback on valid/invalid moves and show conflicts
+      if any occur.
+
+      '
+    max_tokens: 150
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      grid_size: 9
+      difficulty: medium
+      render_format: with_feedback
+      show_conflicts: true
+      show_valid_numbers: true
+      max_steps: 81
+  SearchQA:
+    env_type: search
+    max_actions_per_traj: 10
+    env_instruction: "You are a search agent answering questions by searching for\
+      \ information.\nUse search[your query] to find relevant documents, and finish[your\
+      \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+      \ about the current situation. This reasoning process MUST be enclosed within\
+      \ <think> </think> tags.\nThen provide your action within <answer>...</answer>\
+      \ tags.\n\nExamples:\n  <think>I need to find information about Ben Platt's\
+      \ father.</think><answer>search[Ben Platt father parent]</answer>\n  <think>Based\
+      \ on the search results, Ben Platt's father is Henry Platt.</think><answer>finish[Henry\
+      \ Platt]</answer>\n"
+    max_tokens: 300
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 10
+      max_search_results: 5
+  SearchQAMock:
+    env_type: search
+    max_actions_per_traj: 10
+    env_instruction: "You are a search agent answering questions by searching for\
+      \ information.\nUse search[your query] to find relevant documents, and finish[your\
+      \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+      \ about the current situation. This reasoning process MUST be enclosed within\
+      \ <think> </think> tags.\nThen provide your action within <answer>...</answer>\
+      \ tags.\n\nExamples:\n  <think>I need to find information about Ben Platt's\
+      \ father.</think><answer>search[Ben Platt father parent]</answer>\n  <think>Based\
+      \ on the search results, Ben Platt's father is Henry Platt.</think><answer>finish[Henry\
+      \ Platt]</answer>\n"
+    max_tokens: 300
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 10
+      max_search_results: 5
+      mock_mode: true
+  game_2048:
+    env_type: game_2048
+    max_actions_per_traj: 700
+    env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+      by sliding Up, Right, Down, or Left.
+
+      If a move is invalid (no tiles move), a small penalty is applied. Respond with
+      a single action.
+
+      Example: <answer>Up</answer>
+
+      '
+    max_tokens: 8192
+    env_config: null
+  rubikscube:
+    env_type: rubikscube
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+      is to restore the cube so that each of the faces consists of a single, unique
+      color.
+
+      Available actions use standard Singmaster notation for face rotations: U, U'',
+      D, D'', L, L'', R, R'', F, F'', B, B''.
+
+      - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+      - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+      prime ('') means 90° counter-clockwise (e.g., "R''").
+
+      Respond with a sequence of actions separated by "||".
+
+      Example: <answer>U</answer>
+
+      '
+    max_tokens: 96
+    env_config:
+      scramble_depth: 2
+      max_steps: 7
+      render_mode: text
+system:
+  CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+  train: 10000
+  val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sa
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+  rank: 0
+  alpha: 64
+  target_modules: all-linear
+agent_proxy:
+  context_window_mode: full
+  max_context_window: 5
+  batch_adjust_mode: copy
+  max_turn: 25
+  action_sep: '||'
+  max_actions_per_turn: 4
+  use_turn_scores: false
+  enable_think: true
+  reward_normalization:
+    grouping: state
+    method: identity
+collapse_detection:
+  compute_freq: 5
+  micro_batch_size: 128
+  first_turn_enabled: true
+  multi_turn_enabled: true
+  num_samples: 64
+es_manager:
+  format_penalty: -0.1
+  train:
+    env_groups: 8
+    group_size: 16
+    env_configs:
+      tags:
+      - rubikscube
+      n_groups:
+      - 8
+  val:
+    env_groups: 512
+    group_size: 1
+    env_configs:
+      tags:
+      - rubikscube
+      n_groups:
+      - 512
+ctx_manager:
+  generation:
+    gen_config:
+      response_length: ${actor_rollout_ref.rollout.response_length}
+      temperature: ${actor_rollout_ref.rollout.temperature}
+      top_p: ${actor_rollout_ref.rollout.top_p}
+      top_k: ${actor_rollout_ref.rollout.top_k}
+      kwargs: null

outputs/2026-06-12/14-59-00/.hydra/hydra.yaml

@@ -0,0 +1,177 @@
+hydra:
+  run:
+    dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+  sweep:
+    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task:
+    - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+    - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+    - actor_rollout_ref.rollout.rollout_filter_value=0.9
+    - trainer.total_training_steps=200
+    - trainer.n_gpus_per_node=8
+    - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sa
+    - custom_envs.rubikscube.env_config.scramble_depth=2
+    - trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa
+  job:
+    name: train
+    chdir: null
+    override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=2,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sa,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa,trainer.n_gpus_per_node=8,trainer.total_training_steps=200
+    id: ???
+    num: ???
+    config_name: _10_rubikscube
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /mnt/general/wanghy/RAGEN_v2
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /mnt/general/wanghy/RAGEN_v2/config
+      schema: file
+      provider: main
+    - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-12/14-59-00
+    choices:
+      reward_model: dp_reward_model
+      critic: dp_critic
+      critic/../engine@critic.model.fsdp_config: fsdp
+      critic/../optim@critic.optim: fsdp
+      model@actor_rollout_ref.model: hf_model
+      rollout@actor_rollout_ref.rollout: rollout
+      ref@actor_rollout_ref.ref: dp_ref
+      ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+      data: legacy_data
+      actor@actor_rollout_ref.actor: dp_actor
+      actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+      actor/../optim@actor_rollout_ref.actor.optim: fsdp
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

outputs/2026-06-15/10-55-43/.hydra/config.yaml

@@ -0,0 +1,1048 @@
+actor_rollout_ref:
+  actor:
+    optim:
+      _target_: verl.workers.config.FSDPOptimizerConfig
+      lr: 1.0e-06
+      lr_warmup_steps_ratio: 0.0
+      total_training_steps: -1
+      weight_decay: 0.01
+      lr_warmup_steps: -1
+      betas:
+      - 0.9
+      - 0.999
+      clip_grad: 1.0
+      min_lr_ratio: 0.0
+      num_cycles: 0.5
+      warmup_style: constant
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    _target_: verl.workers.config.FSDPActorConfig
+    strategy: fsdp
+    ppo_mini_batch_size: ${ppo_mini_batch_size}
+    ppo_micro_batch_size: null
+    ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+    use_dynamic_bsz: false
+    ppo_max_token_len_per_gpu: 16384
+    clip_ratio: 0.2
+    clip_ratio_low: 0.2
+    clip_ratio_high: 0.28
+    freeze_vision_tower: false
+    policy_loss:
+      _target_: verl.workers.config.PolicyLossConfig
+      loss_mode: vanilla
+      clip_cov_ratio: 0.0002
+      clip_cov_lb: 1.0
+      clip_cov_ub: 5.0
+      kl_cov_ratio: 0.0002
+      ppo_kl_coef: 0.1
+    clip_ratio_c: 3.0
+    loss_agg_mode: token-mean
+    entropy_coeff: 0.001
+    tis_imp_ratio_cap: -1
+    use_kl_loss: false
+    use_torch_compile: true
+    kl_loss_coef: 0.0
+    kl_loss_type: kl
+    ppo_epochs: 1
+    shuffle: false
+    checkpoint:
+      _target_: verl.trainer.config.CheckpointConfig
+      save_contents:
+      - model
+      - optimizer
+      - extra
+      load_contents: ${.save_contents}
+      async_save: false
+    use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: false
+      all_ranks: false
+      ranks: []
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config:
+        nsys:
+          _target_: verl.utils.profiler.config.NsightToolConfig
+          discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+        npu:
+          _target_: verl.utils.profiler.config.NPUToolConfig
+          contents: []
+          level: level1
+          analysis: true
+          discrete: false
+        torch:
+          _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+          step_start: 0
+          step_end: null
+        torch_memory:
+          _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+          trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+          stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+    grad_clip: 1.0
+    ulysses_sequence_parallel_size: 1
+    entropy_from_logits_with_chunking: false
+    entropy_checkpointing: false
+    use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+    use_ref: true
+    grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+    filter_loss_scaling: none
+  ref:
+    strategy: ${actor_rollout_ref.actor.strategy}
+    use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+    log_prob_micro_batch_size: null
+    log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+    log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+    log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: false
+      all_ranks: false
+      ranks: []
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config:
+        nsys:
+          _target_: verl.utils.profiler.config.NsightToolConfig
+          discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+        npu:
+          _target_: verl.utils.profiler.config.NPUToolConfig
+          contents: []
+          level: level1
+          analysis: true
+          discrete: false
+        torch:
+          _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+          step_start: 0
+          step_end: null
+        torch_memory:
+          _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+          trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+          stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    model: null
+    ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+    entropy_from_logits_with_chunking: false
+    entropy_checkpointing: false
+  rollout:
+    _target_: verl.workers.config.RolloutConfig
+    name: vllm
+    mode: sync
+    temperature: 1
+    top_k: -1
+    top_p: 1
+    prompt_length: 1
+    response_length: 500
+    dtype: bfloat16
+    gpu_memory_utilization: 0.7
+    ignore_eos: false
+    enforce_eager: true
+    cudagraph_capture_sizes: null
+    free_cache_engine: true
+    tensor_model_parallel_size: 1
+    data_parallel_size: 1
+    expert_parallel_size: 1
+    max_num_batched_tokens: 16384
+    max_model_len: 16384
+    max_num_seqs: 1024
+    enable_chunked_prefill: true
+    enable_prefix_caching: true
+    load_format: auto
+    log_prob_micro_batch_size: null
+    log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+    log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+    log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+    disable_log_stats: true
+    do_sample: true
+    'n': 1
+    over_sample_rate: 0
+    multi_stage_wake_up: false
+    engine_kwargs:
+      vllm: {}
+      sglang: {}
+    val_kwargs:
+      _target_: verl.workers.config.SamplingConfig
+      top_k: -1
+      top_p: 1.0
+      temperature: 0.5
+      'n': 1
+      do_sample: true
+    multi_turn:
+      _target_: verl.workers.config.MultiTurnConfig
+      enable: false
+      max_assistant_turns: null
+      tool_config_path: null
+      max_user_turns: null
+      max_parallel_calls: 1
+      max_tool_response_length: 256
+      tool_response_truncate_side: middle
+      interaction_config_path: null
+      use_inference_chat_template: false
+      tokenization_sanity_check_mode: strict
+      format: hermes
+      num_repeat_rollouts: null
+    calculate_log_probs: false
+    agent:
+      _target_: verl.workers.config.AgentLoopConfig
+      num_workers: 8
+      agent_loop_config_path: null
+      custom_async_server:
+        _target_: verl.workers.config.CustomAsyncServerConfig
+        path: null
+        name: null
+    update_weights_bucket_megabytes: 512
+    trace:
+      _target_: verl.workers.config.TraceConfig
+      backend: null
+      token2text: false
+    skip_rollout: false
+    skip_dump_dir: /tmp/rollout_dump
+    skip_tokenizer_init: true
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+      all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+      ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+    layered_summon: false
+    rollout_filter_value: 0.9
+    rollout_filter_strategy: top_p
+    rollout_filter_type: largest
+    rollout_filter_include_zero: true
+    rollout_filter_top_p_prob_mode: linear
+    rollout_filter_selection_eps: 0.01
+    rollout_filter_empty_stop_steps: 5
+    rollout_filter_metric: reward_variance
+    gradient_analysis_num_buckets: 6
+    gradient_analysis_bucket_mode: quantile
+  model:
+    _target_: verl.workers.config.HFModelConfig
+    path: ${model_path}
+    hf_config_path: null
+    tokenizer_path: null
+    use_shm: false
+    trust_remote_code: false
+    custom_chat_template: null
+    external_lib: null
+    override_config: {}
+    enable_gradient_checkpointing: true
+    enable_activation_offload: false
+    use_remove_padding: false
+    lora_rank: ${lora.rank}
+    lora_alpha: ${lora.alpha}
+    target_modules: ${lora.target_modules}
+    exclude_modules: null
+    use_liger: false
+    use_fused_kernels: false
+    fused_kernel_options:
+      impl_backend: torch
+  hybrid_engine: true
+  nccl_timeout: 600
+data:
+  tokenizer: null
+  use_shm: false
+  train_files: ~/data/rlhf/gsm8k/train.parquet
+  val_files: ~/data/rlhf/gsm8k/test.parquet
+  prompt_key: prompt
+  reward_fn_key: data_source
+  max_prompt_length: null
+  max_response_length: null
+  train_batch_size: null
+  val_batch_size: null
+  return_raw_input_ids: false
+  return_raw_chat: false
+  return_full_prompt: false
+  shuffle: true
+  dataloader_num_workers: 8
+  validation_shuffle: false
+  filter_overlong_prompts: false
+  filter_overlong_prompts_workers: 1
+  truncation: error
+  image_key: images
+  video_key: videos
+  trust_remote_code: false
+  custom_cls:
+    path: null
+    name: null
+  return_multi_modal_inputs: true
+  sampler:
+    class_path: null
+    class_name: null
+  datagen:
+    path: null
+    name: null
+  apply_chat_template_kwargs: {}
+critic:
+  optim:
+    _target_: verl.workers.config.FSDPOptimizerConfig
+    lr: 1.0e-05
+    lr_warmup_steps_ratio: 0.0
+    total_training_steps: -1
+    weight_decay: 0.01
+    lr_warmup_steps: -1
+    betas:
+    - 0.9
+    - 0.999
+    clip_grad: 1.0
+    min_lr_ratio: 0.0
+    num_cycles: 0.5
+    warmup_style: constant
+  model:
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    path: ${model_path}
+    tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+    override_config: {}
+    external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+    trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+    _target_: verl.workers.config.FSDPCriticModelCfg
+    use_shm: false
+    enable_gradient_checkpointing: true
+    enable_activation_offload: false
+    use_remove_padding: false
+    lora_rank: ${lora.rank}
+    lora_alpha: ${lora.alpha}
+    target_modules: ${lora.target_modules}
+  _target_: verl.workers.config.FSDPCriticConfig
+  rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+  strategy: fsdp
+  enable: null
+  ppo_mini_batch_size: ${ppo_mini_batch_size}
+  ppo_micro_batch_size: null
+  ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+  use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+  ppo_max_token_len_per_gpu: 32768
+  forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+  ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+  shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+  cliprange_value: 0.5
+  loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+  checkpoint:
+    _target_: verl.trainer.config.CheckpointConfig
+    save_contents:
+    - model
+    - optimizer
+    - extra
+    load_contents: ${.save_contents}
+    async_save: false
+  profiler:
+    _target_: verl.utils.profiler.ProfilerConfig
+    tool: ${oc.select:global_profiler.tool,null}
+    enable: false
+    all_ranks: false
+    ranks: []
+    save_path: ${oc.select:global_profiler.save_path,null}
+    tool_config:
+      nsys:
+        _target_: verl.utils.profiler.config.NsightToolConfig
+        discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+      npu:
+        _target_: verl.utils.profiler.config.NPUToolConfig
+        contents: []
+        level: level1
+        analysis: true
+        discrete: false
+      torch:
+        _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+        step_start: 0
+        step_end: null
+      torch_memory:
+        _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+        trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+        stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+  forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+  forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+  ulysses_sequence_parallel_size: 1
+  grad_clip: 1.0
+reward_model:
+  enable: false
+  enable_resource_pool: false
+  n_gpus_per_node: 0
+  nnodes: 0
+  strategy: fsdp
+  model:
+    input_tokenizer: ${actor_rollout_ref.model.path}
+    path: ~/models/FsfairX-LLaMA3-RM-v0.1
+    external_lib: ${actor_rollout_ref.model.external_lib}
+    trust_remote_code: false
+    use_shm: false
+    use_remove_padding: false
+    use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+  micro_batch_size: null
+  micro_batch_size_per_gpu: null
+  max_length: null
+  use_dynamic_bsz: ${critic.use_dynamic_bsz}
+  forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+  reward_manager: naive
+  launch_reward_fn_async: false
+  sandbox_fusion:
+    url: null
+    max_concurrent: 64
+    memory_limit_mb: 1024
+  profiler:
+    _target_: verl.utils.profiler.ProfilerConfig
+    tool: ${oc.select:global_profiler.tool,null}
+    enable: false
+    all_ranks: false
+    ranks: []
+    save_path: ${oc.select:global_profiler.save_path,null}
+    tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+  ulysses_sequence_parallel_size: 1
+custom_reward_function:
+  path: null
+  name: compute_score
+algorithm:
+  _target_: verl.trainer.config.AlgoConfig
+  gamma: 1.0
+  lam: 1.0
+  adv_estimator: gae
+  norm_adv_by_std_in_grpo: true
+  use_kl_in_reward: false
+  kl_penalty: kl
+  kl_ctrl:
+    _target_: verl.trainer.config.KLControlConfig
+    type: fixed
+    kl_coef: 0.0
+    horizon: 10000
+    target_kl: 0.1
+  use_pf_ppo: false
+  pf_ppo:
+    reweight_method: pow
+    weight_pow: 2.0
+  high_level_gamma: 0.95
+  bi_level_gae: false
+  zero_task_advantage: false
+  soft_advantage_reweight: false
+trainer:
+  balance_batch: true
+  total_epochs: 30
+  total_training_steps: 200
+  project_name: ragen
+  experiment_name: rubikscube2_withthink_fulltrajc_sa
+  logger:
+  - console
+  - wandb
+  log_val_generations: 0
+  rollout_data_dir: null
+  validation_data_dir: null
+  nnodes: 1
+  n_gpus_per_node: 8
+  save_freq: -1
+  esi_redundant_time: 0
+  resume_mode: auto
+  resume_from_path: null
+  val_before_train: true
+  val_only: false
+  test_freq: 10
+  critic_warmup: 0
+  default_hdfs_dir: null
+  del_local_ckpt_after_load: false
+  default_local_dir: checkpoints/${trainer.project_name}/${trainer.experiment_name}
+  max_actor_ckpt_to_keep: 1
+  max_critic_ckpt_to_keep: 1
+  ray_wait_register_center_timeout: 300
+  device: cuda
+  use_legacy_worker_impl: auto
+  local_log_dir: results/
+  validation_steps: 1
+  generations_to_log_to_wandb:
+    val: 20
+  log_group_rv_table: false
+  gradient_analysis_mode: false
+  gradient_analysis_every: 50
+  gradient_analysis_env_groups: null
+  gradient_analysis_group_size: null
+  gradient_analysis_log_prefilter: false
+  gradient_analysis_only: false
+  exit_after_gradient_analysis: false
+global_profiler:
+  _target_: verl.utils.profiler.ProfilerConfig
+  tool: null
+  steps: null
+  profile_continuous_steps: false
+  save_path: outputs/profile
+  global_tool_config:
+    nsys:
+      _target_: verl.utils.profiler.config.NsightToolConfig
+      discrete: false
+      controller_nsight_options:
+        trace: cuda,nvtx,cublas,ucx
+        cuda-memory-usage: 'true'
+        cuda-graph-trace: graph
+      worker_nsight_options:
+        trace: cuda,nvtx,cublas,ucx
+        cuda-memory-usage: 'true'
+        cuda-graph-trace: graph
+        capture-range: cudaProfilerApi
+        capture-range-end: null
+        kill: none
+    torch_memory:
+      trace_alloc_max_entries: 100000
+      stack_depth: 32
+      context: all
+      stacks: all
+      kw_args: {}
+ray_kwargs:
+  ray_init:
+    num_cpus: null
+  timeline_json_file: null
+custom_envs:
+  SimpleSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 20
+    env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+      \ when reasoning:\n1. First compare the box position with the target position;\
+      \ the useful push directions are usually the directions that reduce their row/column\
+      \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+      \ push direction. A move that only repositions the player can be useful if it\
+      \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+      \ dead end unless that square is the target or clearly on the only path to the\
+      \ target.\n4. Prefer short plans that move the single box steadily toward the\
+      \ target; avoid wandering moves that do not improve player position or box position.\n\
+      5. If the box and target are aligned in the same row or column, try to keep\
+      \ the box on that line and push along it.\n6. If they are not aligned, first\
+      \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+      7. Check that after each push, the player can still reach the next required\
+      \ pushing side of the box.\n8. Output only the required XML-like format and\
+      \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+      \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+      \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+      \ pull a box. \nThe answer should be a sequence of actions, like <answer>Right\
+      \ || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 2
+      max_steps: 100
+  LargerSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+      \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+      \ you can push it by moving in the same direction. \nYou cannot push a box through\
+      \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+      \ like <answer>Right || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 8
+      dim_y: 8
+      num_boxes: 2
+      max_steps: 100
+      search_depth: 10
+  SokobanDifferentGridVocab:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+      \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+      \ you can push it by moving in the same direction. \nYou cannot push a box through\
+      \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+      \ like <answer>Right || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      search_depth: 30
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      grid_lookup:
+        0: W
+        1: .
+        2: G
+        3: C
+        4: B
+        5: A
+        6: '@'
+      grid_vocab:
+        W: wall
+        .: empty
+        G: target
+        C: box on target
+        B: box
+        A: player
+        '@': player on target
+  CoordSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 20
+    env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+      \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+      \ the zero-indexed coordinates of the player, each box, and each target. \n\
+      Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+      \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+      \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+      \ pull a box.\nThe answer should be a sequence of actions, like <answer>Right\
+      \ || Right || Up</answer>.\n"
+    max_tokens: 120
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      observation_format: grid_coord
+  VisualSimpleSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: You are solving the Sokoban puzzle. You are the player and you
+      need to push all boxes to targets. When you are right next to a box, you can
+      push it by moving in the same direction. You cannot push a box through a wall,
+      and you cannot pull a box. The answer should be a sequence of actions, like
+      <answer>Right || Right || Up</answer>
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      render_mode: rgb_array
+  Alfworld:
+    env_type: alfworld
+    max_actions_per_traj: 50
+    parallel_friendly: false
+    max_workers: 1
+    env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+      Complete household tasks by navigating and interacting with objects.
+
+
+      You should first reason step-by-step about the current situation. This reasoning
+      process MUST be enclosed within <think> </think> tags.
+
+      Once you''ve finished your reasoning, you should choose an admissible action
+      for current step and present it within <answer>...</answer> tags.
+
+      '
+    max_tokens: 512
+    env_config:
+      eval_dataset: eval_in_distribution
+  AlfworldOOD:
+    env_type: alfworld
+    max_actions_per_traj: 50
+    parallel_friendly: false
+    max_workers: 1
+    env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+      Complete household tasks by navigating and interacting with objects.
+
+
+      You should first reason step-by-step about the current situation. This reasoning
+      process MUST be enclosed within <think> </think> tags.
+
+      Once you''ve finished your reasoning, you should choose an admissible action
+      for current step and present it within <answer>...</answer> tags.
+
+      '
+    max_tokens: 512
+    env_config:
+      eval_dataset: eval_out_of_distribution
+  Countdown:
+    env_type: countdown
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving the Countdown puzzle. You should use the num
+      list to create an equation that equals the target. Example answer format: <think>
+      To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+      = 4. So the answer is 2 + 5 - 3 = 4. </think><answer>2 + 5 - 3</answer>'
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config: null
+  Bandit:
+    env_type: bandit
+    max_actions_per_traj: 1
+    env_instruction: ''
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      split: train
+  BanditTest:
+    env_type: bandit
+    max_actions_per_traj: 1
+    env_instruction: ''
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      split: test
+  DeepCoder:
+    env_type: deepcoder
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving a coding task. Provide a complete Python function
+      solution only. Format: <answer>...</answer>'
+    max_tokens: 8000
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 1
+  FrozenLake:
+    env_type: frozen_lake
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+      go to the target. You may move to the unintended direction due to the slippery
+      ice. Example answer format: <think>To forbid the hole and go to the target,
+      I should go left then go up.</think><answer>Left || Up</answer>'
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      success_rate: 0.8
+  CoordFrozenLake:
+    env_type: frozen_lake
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+      both a symbol grid and zero-indexed coordinates for the start, goal, player,
+      and any holes.
+
+      Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+      (5, 5).
+
+      Beware that the ice is slippery, so the agent might slide and end up in an unintended
+      tile.
+
+      Respond with a sequence of actions such as <answer>Left || Up || Up</answer>.
+
+      '
+    max_tokens: 120
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      observation_format: grid_coord
+      success_rate: 0.8
+  MetamathQA:
+    env_type: metamathqa
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving Math problems. '
+    max_tokens: 100
+    env_config: null
+  WebShopFull:
+    env_type: webshop
+    max_actions_per_traj: 15
+    env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+      environment.
+    max_tokens: 200
+    env_config:
+      dataset: full
+  WebShop:
+    env_type: webshop
+    max_actions_per_traj: 9
+    env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+      a product that close to the production description. You need to search, read
+      the search results, pick a product, choose the size and color and buy. You should
+      only choose action from the available actions list provided later.  Example
+      process: I need a gingko light and 20x20 pillow cover that is hand painted.
+      First search[gingko light 20x20 pillow cover hand painted], answer format: <answer>search[blanket
+      with fleece throw]</answer>. Valid answer is search[<keywords>] or click[<clickable>].'
+    max_tokens: 200
+    env_config:
+      dataset: small
+  Lean:
+    env_type: lean
+    max_actions_per_traj: 30
+    env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+      propose a sequence of tactics that completes the proof. Think step by step about
+      which tactics to apply next. Provide tactics separated by '||', for example
+      <answer>intro || simp || rfl</answer>.
+    max_tokens: 512
+    parallel_friendly: true
+    max_workers: 32
+    env_config: null
+  SimpleSudoku:
+    env_type: sudoku
+    max_actions_per_traj: 20
+    env_instruction: 'You are a careful 4x4 Sudoku solver. Use these reusable abstractions
+      when reasoning:
+
+      1. In <think>, explain the constraint logic behind the move, not just the final
+      placement. Mention which row, column, or 2x2 box makes the move safe or forced.
+
+      2. Treat each move as a constraint-preserving placement: place a number only
+      if it does not already appear in the same row, column, or 2x2 box.
+
+      3. First look for highly forced cells. If an empty cell has only one legal candidate
+      after checking its row, column, and box, fill it immediately and explain why
+      other numbers are excluded.
+
+      4. If no cell is obviously forced, scan each row, column, and 2x2 box for missing
+      numbers. If a missing number can go in only one empty position within that unit,
+      place it there and state that unit-level reason.
+
+      5. Prefer moves that reduce uncertainty and create new forced cells for the
+      next turn. A good move should make the remaining puzzle more constrained, not
+      more ambiguous.
+
+      6. Solve incrementally: choose exactly one placement, explain it briefly in
+      <think>, then output that one move in <answer>.
+
+      7. Never modify bracketed initial cells or already-filled cells. Only place
+      numbers into dots.
+
+      8. Avoid exploratory guesses when a forced move exists. In this environment,
+      reliable progress usually comes from constraint propagation rather than trial-and-error.
+
+      9. If a previous move was invalid or the board did not change, do not repeat
+      the same placement. Recompute legal candidates and explain the corrected constraint-consistent
+      choice.
+
+      10. Use row, column, and box agreement as confidence: the strongest placements
+      are those supported by multiple constraints at once.
+
+      11. Keep <think> concise but meaningful: identify the target cell, list or compare
+      its legal candidates, and give the decisive constraint.
+
+      12. Output only the required XML-like format and choose valid Sudoku placements.
+
+
+      You are solving a Sudoku puzzle. Fill in the grid so that every row, column,
+      and 2x2 box contains the numbers 1-4 without repetition.
+
+      Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+      shown as dots (.).
+
+      Place numbers one at a time using the format: <answer>place 1 at row 2 col 3</answer>
+
+      Always output: <think> [brief constraint-based reasoning] </think> <answer>
+      [one placement] </answer>
+
+      The environment will provide feedback on valid/invalid moves and show conflicts
+      if any occur.
+
+      '
+    max_tokens: 150
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      grid_size: 4
+      difficulty: easy
+      render_format: with_feedback
+      show_conflicts: false
+      show_valid_numbers: false
+      max_steps: 20
+  MediumSudoku:
+    env_type: sudoku
+    max_actions_per_traj: 30
+    env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+      row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+      Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+      shown as dots (.).
+
+      Place numbers one at a time using the format: <answer>place 5 at row 2 col 3</answer>
+      or <answer>2,3,5</answer>
+
+      The environment will provide feedback on valid/invalid moves and show conflicts
+      if any occur.
+
+      '
+    max_tokens: 150
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      grid_size: 9
+      difficulty: medium
+      render_format: with_feedback
+      show_conflicts: true
+      show_valid_numbers: true
+      max_steps: 81
+  SearchQA:
+    env_type: search
+    max_actions_per_traj: 10
+    env_instruction: "You are a search agent answering questions by searching for\
+      \ information.\nUse search[your query] to find relevant documents, and finish[your\
+      \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+      \ about the current situation. This reasoning process MUST be enclosed within\
+      \ <think> </think> tags.\nThen provide your action within <answer>...</answer>\
+      \ tags.\n\nExamples:\n  <think>I need to find information about Ben Platt's\
+      \ father.</think><answer>search[Ben Platt father parent]</answer>\n  <think>Based\
+      \ on the search results, Ben Platt's father is Henry Platt.</think><answer>finish[Henry\
+      \ Platt]</answer>\n"
+    max_tokens: 300
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 10
+      max_search_results: 5
+  SearchQAMock:
+    env_type: search
+    max_actions_per_traj: 10
+    env_instruction: "You are a search agent answering questions by searching for\
+      \ information.\nUse search[your query] to find relevant documents, and finish[your\
+      \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+      \ about the current situation. This reasoning process MUST be enclosed within\
+      \ <think> </think> tags.\nThen provide your action within <answer>...</answer>\
+      \ tags.\n\nExamples:\n  <think>I need to find information about Ben Platt's\
+      \ father.</think><answer>search[Ben Platt father parent]</answer>\n  <think>Based\
+      \ on the search results, Ben Platt's father is Henry Platt.</think><answer>finish[Henry\
+      \ Platt]</answer>\n"
+    max_tokens: 300
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 10
+      max_search_results: 5
+      mock_mode: true
+  game_2048:
+    env_type: game_2048
+    max_actions_per_traj: 700
+    env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+      by sliding Up, Right, Down, or Left.
+
+      If a move is invalid (no tiles move), a small penalty is applied. Respond with
+      a single action.
+
+      Example: <answer>Up</answer>
+
+      '
+    max_tokens: 8192
+    env_config: null
+  rubikscube:
+    env_type: rubikscube
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+      is to restore the cube so that each of the faces consists of a single, unique
+      color.
+
+      Available actions use standard Singmaster notation for face rotations: U, U'',
+      D, D'', L, L'', R, R'', F, F'', B, B''.
+
+      - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+      - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+      prime ('') means 90° counter-clockwise (e.g., "R''").
+
+      Respond with a sequence of actions separated by "||".
+
+      Example: <answer>U</answer>
+
+      '
+    max_tokens: 96
+    env_config:
+      scramble_depth: 2
+      max_steps: 7
+      render_mode: text
+system:
+  CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+  train: 10000
+  val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sa
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+  rank: 0
+  alpha: 64
+  target_modules: all-linear
+agent_proxy:
+  context_window_mode: full
+  max_context_window: 5
+  batch_adjust_mode: copy
+  max_turn: 25
+  action_sep: '||'
+  max_actions_per_turn: 4
+  use_turn_scores: false
+  enable_think: true
+  reward_normalization:
+    grouping: state
+    method: identity
+collapse_detection:
+  compute_freq: 5
+  micro_batch_size: 128
+  first_turn_enabled: true
+  multi_turn_enabled: true
+  num_samples: 64
+es_manager:
+  format_penalty: -0.1
+  train:
+    env_groups: 8
+    group_size: 16
+    env_configs:
+      tags:
+      - rubikscube
+      n_groups:
+      - 8
+  val:
+    env_groups: 512
+    group_size: 1
+    env_configs:
+      tags:
+      - rubikscube
+      n_groups:
+      - 512
+ctx_manager:
+  generation:
+    gen_config:
+      response_length: ${actor_rollout_ref.rollout.response_length}
+      temperature: ${actor_rollout_ref.rollout.temperature}
+      top_p: ${actor_rollout_ref.rollout.top_p}
+      top_k: ${actor_rollout_ref.rollout.top_k}
+      kwargs: null

outputs/2026-06-15/10-55-43/.hydra/hydra.yaml

@@ -0,0 +1,177 @@
+hydra:
+  run:
+    dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+  sweep:
+    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task:
+    - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+    - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+    - actor_rollout_ref.rollout.rollout_filter_value=0.9
+    - trainer.total_training_steps=200
+    - trainer.n_gpus_per_node=8
+    - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sa
+    - custom_envs.rubikscube.env_config.scramble_depth=2
+    - trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa
+  job:
+    name: train
+    chdir: null
+    override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=2,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sa,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa,trainer.n_gpus_per_node=8,trainer.total_training_steps=200
+    id: ???
+    num: ???
+    config_name: _10_rubikscube
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /mnt/general/wanghy/RAGEN_v2
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /mnt/general/wanghy/RAGEN_v2/config
+      schema: file
+      provider: main
+    - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-15/10-55-43
+    choices:
+      reward_model: dp_reward_model
+      critic: dp_critic
+      critic/../engine@critic.model.fsdp_config: fsdp
+      critic/../optim@critic.optim: fsdp
+      model@actor_rollout_ref.model: hf_model
+      rollout@actor_rollout_ref.rollout: rollout
+      ref@actor_rollout_ref.ref: dp_ref
+      ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+      data: legacy_data
+      actor@actor_rollout_ref.actor: dp_actor
+      actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+      actor/../optim@actor_rollout_ref.actor.optim: fsdp
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

outputs/2026-06-15/10-55-43/.hydra/overrides.yaml

@@ -0,0 +1,8 @@
+- system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- trainer.n_gpus_per_node=8
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sa
+- custom_envs.rubikscube.env_config.scramble_depth=2
+- trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa

outputs/2026-06-15/10-56-06/.hydra/config.yaml

@@ -0,0 +1,1048 @@
+actor_rollout_ref:
+  actor:
+    optim:
+      _target_: verl.workers.config.FSDPOptimizerConfig
+      lr: 1.0e-06
+      lr_warmup_steps_ratio: 0.0
+      total_training_steps: -1
+      weight_decay: 0.01
+      lr_warmup_steps: -1
+      betas:
+      - 0.9
+      - 0.999
+      clip_grad: 1.0
+      min_lr_ratio: 0.0
+      num_cycles: 0.5
+      warmup_style: constant
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    _target_: verl.workers.config.FSDPActorConfig
+    strategy: fsdp
+    ppo_mini_batch_size: ${ppo_mini_batch_size}
+    ppo_micro_batch_size: null
+    ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+    use_dynamic_bsz: false
+    ppo_max_token_len_per_gpu: 16384
+    clip_ratio: 0.2
+    clip_ratio_low: 0.2
+    clip_ratio_high: 0.28
+    freeze_vision_tower: false
+    policy_loss:
+      _target_: verl.workers.config.PolicyLossConfig
+      loss_mode: vanilla
+      clip_cov_ratio: 0.0002
+      clip_cov_lb: 1.0
+      clip_cov_ub: 5.0
+      kl_cov_ratio: 0.0002
+      ppo_kl_coef: 0.1
+    clip_ratio_c: 3.0
+    loss_agg_mode: token-mean
+    entropy_coeff: 0.001
+    tis_imp_ratio_cap: -1
+    use_kl_loss: false
+    use_torch_compile: true
+    kl_loss_coef: 0.0
+    kl_loss_type: kl
+    ppo_epochs: 1
+    shuffle: false
+    checkpoint:
+      _target_: verl.trainer.config.CheckpointConfig
+      save_contents:
+      - model
+      - optimizer
+      - extra
+      load_contents: ${.save_contents}
+      async_save: false
+    use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: false
+      all_ranks: false
+      ranks: []
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config:
+        nsys:
+          _target_: verl.utils.profiler.config.NsightToolConfig
+          discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+        npu:
+          _target_: verl.utils.profiler.config.NPUToolConfig
+          contents: []
+          level: level1
+          analysis: true
+          discrete: false
+        torch:
+          _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+          step_start: 0
+          step_end: null
+        torch_memory:
+          _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+          trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+          stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+    grad_clip: 1.0
+    ulysses_sequence_parallel_size: 1
+    entropy_from_logits_with_chunking: false
+    entropy_checkpointing: false
+    use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+    use_ref: true
+    grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+    filter_loss_scaling: none
+  ref:
+    strategy: ${actor_rollout_ref.actor.strategy}
+    use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+    log_prob_micro_batch_size: null
+    log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+    log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+    log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: false
+      all_ranks: false
+      ranks: []
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config:
+        nsys:
+          _target_: verl.utils.profiler.config.NsightToolConfig
+          discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+        npu:
+          _target_: verl.utils.profiler.config.NPUToolConfig
+          contents: []
+          level: level1
+          analysis: true
+          discrete: false
+        torch:
+          _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+          step_start: 0
+          step_end: null
+        torch_memory:
+          _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+          trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+          stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    model: null
+    ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+    entropy_from_logits_with_chunking: false
+    entropy_checkpointing: false
+  rollout:
+    _target_: verl.workers.config.RolloutConfig
+    name: vllm
+    mode: sync
+    temperature: 1
+    top_k: -1
+    top_p: 1
+    prompt_length: 1
+    response_length: 500
+    dtype: bfloat16
+    gpu_memory_utilization: 0.7
+    ignore_eos: false
+    enforce_eager: true
+    cudagraph_capture_sizes: null
+    free_cache_engine: true
+    tensor_model_parallel_size: 1
+    data_parallel_size: 1
+    expert_parallel_size: 1
+    max_num_batched_tokens: 16384
+    max_model_len: 16384
+    max_num_seqs: 1024
+    enable_chunked_prefill: true
+    enable_prefix_caching: true
+    load_format: auto
+    log_prob_micro_batch_size: null
+    log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+    log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+    log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+    disable_log_stats: true
+    do_sample: true
+    'n': 1
+    over_sample_rate: 0
+    multi_stage_wake_up: false
+    engine_kwargs:
+      vllm: {}
+      sglang: {}
+    val_kwargs:
+      _target_: verl.workers.config.SamplingConfig
+      top_k: -1
+      top_p: 1.0
+      temperature: 0.5
+      'n': 1
+      do_sample: true
+    multi_turn:
+      _target_: verl.workers.config.MultiTurnConfig
+      enable: false
+      max_assistant_turns: null
+      tool_config_path: null
+      max_user_turns: null
+      max_parallel_calls: 1
+      max_tool_response_length: 256
+      tool_response_truncate_side: middle
+      interaction_config_path: null
+      use_inference_chat_template: false
+      tokenization_sanity_check_mode: strict
+      format: hermes
+      num_repeat_rollouts: null
+    calculate_log_probs: false
+    agent:
+      _target_: verl.workers.config.AgentLoopConfig
+      num_workers: 8
+      agent_loop_config_path: null
+      custom_async_server:
+        _target_: verl.workers.config.CustomAsyncServerConfig
+        path: null
+        name: null
+    update_weights_bucket_megabytes: 512
+    trace:
+      _target_: verl.workers.config.TraceConfig
+      backend: null
+      token2text: false
+    skip_rollout: false
+    skip_dump_dir: /tmp/rollout_dump
+    skip_tokenizer_init: true
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+      all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+      ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+    layered_summon: false
+    rollout_filter_value: 0.9
+    rollout_filter_strategy: top_p
+    rollout_filter_type: largest
+    rollout_filter_include_zero: true
+    rollout_filter_top_p_prob_mode: linear
+    rollout_filter_selection_eps: 0.01
+    rollout_filter_empty_stop_steps: 5
+    rollout_filter_metric: reward_variance
+    gradient_analysis_num_buckets: 6
+    gradient_analysis_bucket_mode: quantile
+  model:
+    _target_: verl.workers.config.HFModelConfig
+    path: ${model_path}
+    hf_config_path: null
+    tokenizer_path: null
+    use_shm: false
+    trust_remote_code: false
+    custom_chat_template: null
+    external_lib: null
+    override_config: {}
+    enable_gradient_checkpointing: true
+    enable_activation_offload: false
+    use_remove_padding: false
+    lora_rank: ${lora.rank}
+    lora_alpha: ${lora.alpha}
+    target_modules: ${lora.target_modules}
+    exclude_modules: null
+    use_liger: false
+    use_fused_kernels: false
+    fused_kernel_options:
+      impl_backend: torch
+  hybrid_engine: true
+  nccl_timeout: 600
+data:
+  tokenizer: null
+  use_shm: false
+  train_files: ~/data/rlhf/gsm8k/train.parquet
+  val_files: ~/data/rlhf/gsm8k/test.parquet
+  prompt_key: prompt
+  reward_fn_key: data_source
+  max_prompt_length: null
+  max_response_length: null
+  train_batch_size: null
+  val_batch_size: null
+  return_raw_input_ids: false
+  return_raw_chat: false
+  return_full_prompt: false
+  shuffle: true
+  dataloader_num_workers: 8
+  validation_shuffle: false
+  filter_overlong_prompts: false
+  filter_overlong_prompts_workers: 1
+  truncation: error
+  image_key: images
+  video_key: videos
+  trust_remote_code: false
+  custom_cls:
+    path: null
+    name: null
+  return_multi_modal_inputs: true
+  sampler:
+    class_path: null
+    class_name: null
+  datagen:
+    path: null
+    name: null
+  apply_chat_template_kwargs: {}
+critic:
+  optim:
+    _target_: verl.workers.config.FSDPOptimizerConfig
+    lr: 1.0e-05
+    lr_warmup_steps_ratio: 0.0
+    total_training_steps: -1
+    weight_decay: 0.01
+    lr_warmup_steps: -1
+    betas:
+    - 0.9
+    - 0.999
+    clip_grad: 1.0
+    min_lr_ratio: 0.0
+    num_cycles: 0.5
+    warmup_style: constant
+  model:
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    path: ${model_path}
+    tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+    override_config: {}
+    external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+    trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+    _target_: verl.workers.config.FSDPCriticModelCfg
+    use_shm: false
+    enable_gradient_checkpointing: true
+    enable_activation_offload: false
+    use_remove_padding: false
+    lora_rank: ${lora.rank}
+    lora_alpha: ${lora.alpha}
+    target_modules: ${lora.target_modules}
+  _target_: verl.workers.config.FSDPCriticConfig
+  rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+  strategy: fsdp
+  enable: null
+  ppo_mini_batch_size: ${ppo_mini_batch_size}
+  ppo_micro_batch_size: null
+  ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+  use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+  ppo_max_token_len_per_gpu: 32768
+  forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+  ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+  shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+  cliprange_value: 0.5
+  loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+  checkpoint:
+    _target_: verl.trainer.config.CheckpointConfig
+    save_contents:
+    - model
+    - optimizer
+    - extra
+    load_contents: ${.save_contents}
+    async_save: false
+  profiler:
+    _target_: verl.utils.profiler.ProfilerConfig
+    tool: ${oc.select:global_profiler.tool,null}
+    enable: false
+    all_ranks: false
+    ranks: []
+    save_path: ${oc.select:global_profiler.save_path,null}
+    tool_config:
+      nsys:
+        _target_: verl.utils.profiler.config.NsightToolConfig
+        discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+      npu:
+        _target_: verl.utils.profiler.config.NPUToolConfig
+        contents: []
+        level: level1
+        analysis: true
+        discrete: false
+      torch:
+        _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+        step_start: 0
+        step_end: null
+      torch_memory:
+        _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+        trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+        stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+  forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+  forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+  ulysses_sequence_parallel_size: 1
+  grad_clip: 1.0
+reward_model:
+  enable: false
+  enable_resource_pool: false
+  n_gpus_per_node: 0
+  nnodes: 0
+  strategy: fsdp
+  model:
+    input_tokenizer: ${actor_rollout_ref.model.path}
+    path: ~/models/FsfairX-LLaMA3-RM-v0.1
+    external_lib: ${actor_rollout_ref.model.external_lib}
+    trust_remote_code: false
+    use_shm: false
+    use_remove_padding: false
+    use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+  micro_batch_size: null
+  micro_batch_size_per_gpu: null
+  max_length: null
+  use_dynamic_bsz: ${critic.use_dynamic_bsz}
+  forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+  reward_manager: naive
+  launch_reward_fn_async: false
+  sandbox_fusion:
+    url: null
+    max_concurrent: 64
+    memory_limit_mb: 1024
+  profiler:
+    _target_: verl.utils.profiler.ProfilerConfig
+    tool: ${oc.select:global_profiler.tool,null}
+    enable: false
+    all_ranks: false
+    ranks: []
+    save_path: ${oc.select:global_profiler.save_path,null}
+    tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+  ulysses_sequence_parallel_size: 1
+custom_reward_function:
+  path: null
+  name: compute_score
+algorithm:
+  _target_: verl.trainer.config.AlgoConfig
+  gamma: 1.0
+  lam: 1.0
+  adv_estimator: gae
+  norm_adv_by_std_in_grpo: true
+  use_kl_in_reward: false
+  kl_penalty: kl
+  kl_ctrl:
+    _target_: verl.trainer.config.KLControlConfig
+    type: fixed
+    kl_coef: 0.0
+    horizon: 10000
+    target_kl: 0.1
+  use_pf_ppo: false
+  pf_ppo:
+    reweight_method: pow
+    weight_pow: 2.0
+  high_level_gamma: 0.95
+  bi_level_gae: false
+  zero_task_advantage: false
+  soft_advantage_reweight: false
+trainer:
+  balance_batch: true
+  total_epochs: 30
+  total_training_steps: 200
+  project_name: ragen
+  experiment_name: rubikscube3_withthink_fulltrajc_sa
+  logger:
+  - console
+  - wandb
+  log_val_generations: 0
+  rollout_data_dir: null
+  validation_data_dir: null
+  nnodes: 1
+  n_gpus_per_node: 8
+  save_freq: -1
+  esi_redundant_time: 0
+  resume_mode: auto
+  resume_from_path: null
+  val_before_train: true
+  val_only: false
+  test_freq: 10
+  critic_warmup: 0
+  default_hdfs_dir: null
+  del_local_ckpt_after_load: false
+  default_local_dir: checkpoints/${trainer.project_name}/${trainer.experiment_name}
+  max_actor_ckpt_to_keep: 1
+  max_critic_ckpt_to_keep: 1
+  ray_wait_register_center_timeout: 300
+  device: cuda
+  use_legacy_worker_impl: auto
+  local_log_dir: results/
+  validation_steps: 1
+  generations_to_log_to_wandb:
+    val: 20
+  log_group_rv_table: false
+  gradient_analysis_mode: false
+  gradient_analysis_every: 50
+  gradient_analysis_env_groups: null
+  gradient_analysis_group_size: null
+  gradient_analysis_log_prefilter: false
+  gradient_analysis_only: false
+  exit_after_gradient_analysis: false
+global_profiler:
+  _target_: verl.utils.profiler.ProfilerConfig
+  tool: null
+  steps: null
+  profile_continuous_steps: false
+  save_path: outputs/profile
+  global_tool_config:
+    nsys:
+      _target_: verl.utils.profiler.config.NsightToolConfig
+      discrete: false
+      controller_nsight_options:
+        trace: cuda,nvtx,cublas,ucx
+        cuda-memory-usage: 'true'
+        cuda-graph-trace: graph
+      worker_nsight_options:
+        trace: cuda,nvtx,cublas,ucx
+        cuda-memory-usage: 'true'
+        cuda-graph-trace: graph
+        capture-range: cudaProfilerApi
+        capture-range-end: null
+        kill: none
+    torch_memory:
+      trace_alloc_max_entries: 100000
+      stack_depth: 32
+      context: all
+      stacks: all
+      kw_args: {}
+ray_kwargs:
+  ray_init:
+    num_cpus: null
+  timeline_json_file: null
+custom_envs:
+  SimpleSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 20
+    env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+      \ when reasoning:\n1. First compare the box position with the target position;\
+      \ the useful push directions are usually the directions that reduce their row/column\
+      \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+      \ push direction. A move that only repositions the player can be useful if it\
+      \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+      \ dead end unless that square is the target or clearly on the only path to the\
+      \ target.\n4. Prefer short plans that move the single box steadily toward the\
+      \ target; avoid wandering moves that do not improve player position or box position.\n\
+      5. If the box and target are aligned in the same row or column, try to keep\
+      \ the box on that line and push along it.\n6. If they are not aligned, first\
+      \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+      7. Check that after each push, the player can still reach the next required\
+      \ pushing side of the box.\n8. Output only the required XML-like format and\
+      \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+      \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+      \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+      \ pull a box. \nThe answer should be a sequence of actions, like <answer>Right\
+      \ || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 2
+      max_steps: 100
+  LargerSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+      \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+      \ you can push it by moving in the same direction. \nYou cannot push a box through\
+      \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+      \ like <answer>Right || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 8
+      dim_y: 8
+      num_boxes: 2
+      max_steps: 100
+      search_depth: 10
+  SokobanDifferentGridVocab:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+      \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+      \ you can push it by moving in the same direction. \nYou cannot push a box through\
+      \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+      \ like <answer>Right || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      search_depth: 30
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      grid_lookup:
+        0: W
+        1: .
+        2: G
+        3: C
+        4: B
+        5: A
+        6: '@'
+      grid_vocab:
+        W: wall
+        .: empty
+        G: target
+        C: box on target
+        B: box
+        A: player
+        '@': player on target
+  CoordSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 20
+    env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+      \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+      \ the zero-indexed coordinates of the player, each box, and each target. \n\
+      Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+      \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+      \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+      \ pull a box.\nThe answer should be a sequence of actions, like <answer>Right\
+      \ || Right || Up</answer>.\n"
+    max_tokens: 120
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      observation_format: grid_coord
+  VisualSimpleSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: You are solving the Sokoban puzzle. You are the player and you
+      need to push all boxes to targets. When you are right next to a box, you can
+      push it by moving in the same direction. You cannot push a box through a wall,
+      and you cannot pull a box. The answer should be a sequence of actions, like
+      <answer>Right || Right || Up</answer>
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      render_mode: rgb_array
+  Alfworld:
+    env_type: alfworld
+    max_actions_per_traj: 50
+    parallel_friendly: false
+    max_workers: 1
+    env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+      Complete household tasks by navigating and interacting with objects.
+
+
+      You should first reason step-by-step about the current situation. This reasoning
+      process MUST be enclosed within <think> </think> tags.
+
+      Once you''ve finished your reasoning, you should choose an admissible action
+      for current step and present it within <answer>...</answer> tags.
+
+      '
+    max_tokens: 512
+    env_config:
+      eval_dataset: eval_in_distribution
+  AlfworldOOD:
+    env_type: alfworld
+    max_actions_per_traj: 50
+    parallel_friendly: false
+    max_workers: 1
+    env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+      Complete household tasks by navigating and interacting with objects.
+
+
+      You should first reason step-by-step about the current situation. This reasoning
+      process MUST be enclosed within <think> </think> tags.
+
+      Once you''ve finished your reasoning, you should choose an admissible action
+      for current step and present it within <answer>...</answer> tags.
+
+      '
+    max_tokens: 512
+    env_config:
+      eval_dataset: eval_out_of_distribution
+  Countdown:
+    env_type: countdown
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving the Countdown puzzle. You should use the num
+      list to create an equation that equals the target. Example answer format: <think>
+      To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+      = 4. So the answer is 2 + 5 - 3 = 4. </think><answer>2 + 5 - 3</answer>'
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config: null
+  Bandit:
+    env_type: bandit
+    max_actions_per_traj: 1
+    env_instruction: ''
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      split: train
+  BanditTest:
+    env_type: bandit
+    max_actions_per_traj: 1
+    env_instruction: ''
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      split: test
+  DeepCoder:
+    env_type: deepcoder
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving a coding task. Provide a complete Python function
+      solution only. Format: <answer>...</answer>'
+    max_tokens: 8000
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 1
+  FrozenLake:
+    env_type: frozen_lake
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+      go to the target. You may move to the unintended direction due to the slippery
+      ice. Example answer format: <think>To forbid the hole and go to the target,
+      I should go left then go up.</think><answer>Left || Up</answer>'
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      success_rate: 0.8
+  CoordFrozenLake:
+    env_type: frozen_lake
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+      both a symbol grid and zero-indexed coordinates for the start, goal, player,
+      and any holes.
+
+      Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+      (5, 5).
+
+      Beware that the ice is slippery, so the agent might slide and end up in an unintended
+      tile.
+
+      Respond with a sequence of actions such as <answer>Left || Up || Up</answer>.
+
+      '
+    max_tokens: 120
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      observation_format: grid_coord
+      success_rate: 0.8
+  MetamathQA:
+    env_type: metamathqa
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving Math problems. '
+    max_tokens: 100
+    env_config: null
+  WebShopFull:
+    env_type: webshop
+    max_actions_per_traj: 15
+    env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+      environment.
+    max_tokens: 200
+    env_config:
+      dataset: full
+  WebShop:
+    env_type: webshop
+    max_actions_per_traj: 9
+    env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+      a product that close to the production description. You need to search, read
+      the search results, pick a product, choose the size and color and buy. You should
+      only choose action from the available actions list provided later.  Example
+      process: I need a gingko light and 20x20 pillow cover that is hand painted.
+      First search[gingko light 20x20 pillow cover hand painted], answer format: <answer>search[blanket
+      with fleece throw]</answer>. Valid answer is search[<keywords>] or click[<clickable>].'
+    max_tokens: 200
+    env_config:
+      dataset: small
+  Lean:
+    env_type: lean
+    max_actions_per_traj: 30
+    env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+      propose a sequence of tactics that completes the proof. Think step by step about
+      which tactics to apply next. Provide tactics separated by '||', for example
+      <answer>intro || simp || rfl</answer>.
+    max_tokens: 512
+    parallel_friendly: true
+    max_workers: 32
+    env_config: null
+  SimpleSudoku:
+    env_type: sudoku
+    max_actions_per_traj: 20
+    env_instruction: 'You are a careful 4x4 Sudoku solver. Use these reusable abstractions
+      when reasoning:
+
+      1. In <think>, explain the constraint logic behind the move, not just the final
+      placement. Mention which row, column, or 2x2 box makes the move safe or forced.
+
+      2. Treat each move as a constraint-preserving placement: place a number only
+      if it does not already appear in the same row, column, or 2x2 box.
+
+      3. First look for highly forced cells. If an empty cell has only one legal candidate
+      after checking its row, column, and box, fill it immediately and explain why
+      other numbers are excluded.
+
+      4. If no cell is obviously forced, scan each row, column, and 2x2 box for missing
+      numbers. If a missing number can go in only one empty position within that unit,
+      place it there and state that unit-level reason.
+
+      5. Prefer moves that reduce uncertainty and create new forced cells for the
+      next turn. A good move should make the remaining puzzle more constrained, not
+      more ambiguous.
+
+      6. Solve incrementally: choose exactly one placement, explain it briefly in
+      <think>, then output that one move in <answer>.
+
+      7. Never modify bracketed initial cells or already-filled cells. Only place
+      numbers into dots.
+
+      8. Avoid exploratory guesses when a forced move exists. In this environment,
+      reliable progress usually comes from constraint propagation rather than trial-and-error.
+
+      9. If a previous move was invalid or the board did not change, do not repeat
+      the same placement. Recompute legal candidates and explain the corrected constraint-consistent
+      choice.
+
+      10. Use row, column, and box agreement as confidence: the strongest placements
+      are those supported by multiple constraints at once.
+
+      11. Keep <think> concise but meaningful: identify the target cell, list or compare
+      its legal candidates, and give the decisive constraint.
+
+      12. Output only the required XML-like format and choose valid Sudoku placements.
+
+
+      You are solving a Sudoku puzzle. Fill in the grid so that every row, column,
+      and 2x2 box contains the numbers 1-4 without repetition.
+
+      Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+      shown as dots (.).
+
+      Place numbers one at a time using the format: <answer>place 1 at row 2 col 3</answer>
+
+      Always output: <think> [brief constraint-based reasoning] </think> <answer>
+      [one placement] </answer>
+
+      The environment will provide feedback on valid/invalid moves and show conflicts
+      if any occur.
+
+      '
+    max_tokens: 150
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      grid_size: 4
+      difficulty: easy
+      render_format: with_feedback
+      show_conflicts: false
+      show_valid_numbers: false
+      max_steps: 20
+  MediumSudoku:
+    env_type: sudoku
+    max_actions_per_traj: 30
+    env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+      row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+      Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+      shown as dots (.).
+
+      Place numbers one at a time using the format: <answer>place 5 at row 2 col 3</answer>
+      or <answer>2,3,5</answer>
+
+      The environment will provide feedback on valid/invalid moves and show conflicts
+      if any occur.
+
+      '
+    max_tokens: 150
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      grid_size: 9
+      difficulty: medium
+      render_format: with_feedback
+      show_conflicts: true
+      show_valid_numbers: true
+      max_steps: 81
+  SearchQA:
+    env_type: search
+    max_actions_per_traj: 10
+    env_instruction: "You are a search agent answering questions by searching for\
+      \ information.\nUse search[your query] to find relevant documents, and finish[your\
+      \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+      \ about the current situation. This reasoning process MUST be enclosed within\
+      \ <think> </think> tags.\nThen provide your action within <answer>...</answer>\
+      \ tags.\n\nExamples:\n  <think>I need to find information about Ben Platt's\
+      \ father.</think><answer>search[Ben Platt father parent]</answer>\n  <think>Based\
+      \ on the search results, Ben Platt's father is Henry Platt.</think><answer>finish[Henry\
+      \ Platt]</answer>\n"
+    max_tokens: 300
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 10
+      max_search_results: 5
+  SearchQAMock:
+    env_type: search
+    max_actions_per_traj: 10
+    env_instruction: "You are a search agent answering questions by searching for\
+      \ information.\nUse search[your query] to find relevant documents, and finish[your\
+      \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+      \ about the current situation. This reasoning process MUST be enclosed within\
+      \ <think> </think> tags.\nThen provide your action within <answer>...</answer>\
+      \ tags.\n\nExamples:\n  <think>I need to find information about Ben Platt's\
+      \ father.</think><answer>search[Ben Platt father parent]</answer>\n  <think>Based\
+      \ on the search results, Ben Platt's father is Henry Platt.</think><answer>finish[Henry\
+      \ Platt]</answer>\n"
+    max_tokens: 300
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 10
+      max_search_results: 5
+      mock_mode: true
+  game_2048:
+    env_type: game_2048
+    max_actions_per_traj: 700
+    env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+      by sliding Up, Right, Down, or Left.
+
+      If a move is invalid (no tiles move), a small penalty is applied. Respond with
+      a single action.
+
+      Example: <answer>Up</answer>
+
+      '
+    max_tokens: 8192
+    env_config: null
+  rubikscube:
+    env_type: rubikscube
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+      is to restore the cube so that each of the faces consists of a single, unique
+      color.
+
+      Available actions use standard Singmaster notation for face rotations: U, U'',
+      D, D'', L, L'', R, R'', F, F'', B, B''.
+
+      - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+      - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+      prime ('') means 90° counter-clockwise (e.g., "R''").
+
+      Respond with a sequence of actions separated by "||".
+
+      Example: <answer>U</answer>
+
+      '
+    max_tokens: 96
+    env_config:
+      scramble_depth: 3
+      max_steps: 7
+      render_mode: text
+system:
+  CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+  train: 10000
+  val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube3_withthink_fulltraj_sa
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+  rank: 0
+  alpha: 64
+  target_modules: all-linear
+agent_proxy:
+  context_window_mode: full
+  max_context_window: 5
+  batch_adjust_mode: copy
+  max_turn: 25
+  action_sep: '||'
+  max_actions_per_turn: 4
+  use_turn_scores: false
+  enable_think: true
+  reward_normalization:
+    grouping: state
+    method: identity
+collapse_detection:
+  compute_freq: 5
+  micro_batch_size: 128
+  first_turn_enabled: true
+  multi_turn_enabled: true
+  num_samples: 64
+es_manager:
+  format_penalty: -0.1
+  train:
+    env_groups: 8
+    group_size: 16
+    env_configs:
+      tags:
+      - rubikscube
+      n_groups:
+      - 8
+  val:
+    env_groups: 512
+    group_size: 1
+    env_configs:
+      tags:
+      - rubikscube
+      n_groups:
+      - 512
+ctx_manager:
+  generation:
+    gen_config:
+      response_length: ${actor_rollout_ref.rollout.response_length}
+      temperature: ${actor_rollout_ref.rollout.temperature}
+      top_p: ${actor_rollout_ref.rollout.top_p}
+      top_k: ${actor_rollout_ref.rollout.top_k}
+      kwargs: null

outputs/2026-06-15/10-56-06/.hydra/hydra.yaml

@@ -0,0 +1,177 @@
+hydra:
+  run:
+    dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+  sweep:
+    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task:
+    - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+    - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+    - actor_rollout_ref.rollout.rollout_filter_value=0.9
+    - trainer.total_training_steps=200
+    - trainer.n_gpus_per_node=8
+    - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube3_withthink_fulltraj_sa
+    - custom_envs.rubikscube.env_config.scramble_depth=3
+    - trainer.experiment_name=rubikscube3_withthink_fulltrajc_sa
+  job:
+    name: train
+    chdir: null
+    override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=3,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube3_withthink_fulltraj_sa,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.experiment_name=rubikscube3_withthink_fulltrajc_sa,trainer.n_gpus_per_node=8,trainer.total_training_steps=200
+    id: ???
+    num: ???
+    config_name: _10_rubikscube
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /mnt/general/wanghy/RAGEN_v2
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /mnt/general/wanghy/RAGEN_v2/config
+      schema: file
+      provider: main
+    - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-15/10-56-06
+    choices:
+      reward_model: dp_reward_model
+      critic: dp_critic
+      critic/../engine@critic.model.fsdp_config: fsdp
+      critic/../optim@critic.optim: fsdp
+      model@actor_rollout_ref.model: hf_model
+      rollout@actor_rollout_ref.rollout: rollout
+      ref@actor_rollout_ref.ref: dp_ref
+      ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+      data: legacy_data
+      actor@actor_rollout_ref.actor: dp_actor
+      actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+      actor/../optim@actor_rollout_ref.actor.optim: fsdp
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

outputs/2026-06-15/10-56-06/.hydra/overrides.yaml

@@ -0,0 +1,8 @@
+- system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- trainer.n_gpus_per_node=8
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube3_withthink_fulltraj_sa
+- custom_envs.rubikscube.env_config.scramble_depth=3
+- trainer.experiment_name=rubikscube3_withthink_fulltrajc_sa

outputs/2026-06-15/17-29-15/.hydra/config.yaml

@@ -0,0 +1,1048 @@
+actor_rollout_ref:
+  actor:
+    optim:
+      _target_: verl.workers.config.FSDPOptimizerConfig
+      lr: 1.0e-06
+      lr_warmup_steps_ratio: 0.0
+      total_training_steps: -1
+      weight_decay: 0.01
+      lr_warmup_steps: -1
+      betas:
+      - 0.9
+      - 0.999
+      clip_grad: 1.0
+      min_lr_ratio: 0.0
+      num_cycles: 0.5
+      warmup_style: constant
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    _target_: verl.workers.config.FSDPActorConfig
+    strategy: fsdp
+    ppo_mini_batch_size: ${ppo_mini_batch_size}
+    ppo_micro_batch_size: null
+    ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+    use_dynamic_bsz: false
+    ppo_max_token_len_per_gpu: 16384
+    clip_ratio: 0.2
+    clip_ratio_low: 0.2
+    clip_ratio_high: 0.28
+    freeze_vision_tower: false
+    policy_loss:
+      _target_: verl.workers.config.PolicyLossConfig
+      loss_mode: vanilla
+      clip_cov_ratio: 0.0002
+      clip_cov_lb: 1.0
+      clip_cov_ub: 5.0
+      kl_cov_ratio: 0.0002
+      ppo_kl_coef: 0.1
+    clip_ratio_c: 3.0
+    loss_agg_mode: token-mean
+    entropy_coeff: 0.001
+    tis_imp_ratio_cap: -1
+    use_kl_loss: false
+    use_torch_compile: true
+    kl_loss_coef: 0.0
+    kl_loss_type: kl
+    ppo_epochs: 1
+    shuffle: false
+    checkpoint:
+      _target_: verl.trainer.config.CheckpointConfig
+      save_contents:
+      - model
+      - optimizer
+      - extra
+      load_contents: ${.save_contents}
+      async_save: false
+    use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: false
+      all_ranks: false
+      ranks: []
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config:
+        nsys:
+          _target_: verl.utils.profiler.config.NsightToolConfig
+          discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+        npu:
+          _target_: verl.utils.profiler.config.NPUToolConfig
+          contents: []
+          level: level1
+          analysis: true
+          discrete: false
+        torch:
+          _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+          step_start: 0
+          step_end: null
+        torch_memory:
+          _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+          trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+          stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+    grad_clip: 1.0
+    ulysses_sequence_parallel_size: 1
+    entropy_from_logits_with_chunking: false
+    entropy_checkpointing: false
+    use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+    use_ref: true
+    grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+    filter_loss_scaling: none
+  ref:
+    strategy: ${actor_rollout_ref.actor.strategy}
+    use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+    log_prob_micro_batch_size: null
+    log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+    log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+    log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: false
+      all_ranks: false
+      ranks: []
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config:
+        nsys:
+          _target_: verl.utils.profiler.config.NsightToolConfig
+          discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+        npu:
+          _target_: verl.utils.profiler.config.NPUToolConfig
+          contents: []
+          level: level1
+          analysis: true
+          discrete: false
+        torch:
+          _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+          step_start: 0
+          step_end: null
+        torch_memory:
+          _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+          trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+          stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    model: null
+    ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+    entropy_from_logits_with_chunking: false
+    entropy_checkpointing: false
+  rollout:
+    _target_: verl.workers.config.RolloutConfig
+    name: vllm
+    mode: sync
+    temperature: 1
+    top_k: -1
+    top_p: 1
+    prompt_length: 1
+    response_length: 500
+    dtype: bfloat16
+    gpu_memory_utilization: 0.7
+    ignore_eos: false
+    enforce_eager: true
+    cudagraph_capture_sizes: null
+    free_cache_engine: true
+    tensor_model_parallel_size: 1
+    data_parallel_size: 1
+    expert_parallel_size: 1
+    max_num_batched_tokens: 16384
+    max_model_len: 16384
+    max_num_seqs: 1024
+    enable_chunked_prefill: true
+    enable_prefix_caching: true
+    load_format: auto
+    log_prob_micro_batch_size: null
+    log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+    log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+    log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+    disable_log_stats: true
+    do_sample: true
+    'n': 1
+    over_sample_rate: 0
+    multi_stage_wake_up: false
+    engine_kwargs:
+      vllm: {}
+      sglang: {}
+    val_kwargs:
+      _target_: verl.workers.config.SamplingConfig
+      top_k: -1
+      top_p: 1.0
+      temperature: 0.5
+      'n': 1
+      do_sample: true
+    multi_turn:
+      _target_: verl.workers.config.MultiTurnConfig
+      enable: false
+      max_assistant_turns: null
+      tool_config_path: null
+      max_user_turns: null
+      max_parallel_calls: 1
+      max_tool_response_length: 256
+      tool_response_truncate_side: middle
+      interaction_config_path: null
+      use_inference_chat_template: false
+      tokenization_sanity_check_mode: strict
+      format: hermes
+      num_repeat_rollouts: null
+    calculate_log_probs: false
+    agent:
+      _target_: verl.workers.config.AgentLoopConfig
+      num_workers: 8
+      agent_loop_config_path: null
+      custom_async_server:
+        _target_: verl.workers.config.CustomAsyncServerConfig
+        path: null
+        name: null
+    update_weights_bucket_megabytes: 512
+    trace:
+      _target_: verl.workers.config.TraceConfig
+      backend: null
+      token2text: false
+    skip_rollout: false
+    skip_dump_dir: /tmp/rollout_dump
+    skip_tokenizer_init: true
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+      all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+      ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+    layered_summon: false
+    rollout_filter_value: 0.9
+    rollout_filter_strategy: top_p
+    rollout_filter_type: largest
+    rollout_filter_include_zero: true
+    rollout_filter_top_p_prob_mode: linear
+    rollout_filter_selection_eps: 0.01
+    rollout_filter_empty_stop_steps: 5
+    rollout_filter_metric: reward_variance
+    gradient_analysis_num_buckets: 6
+    gradient_analysis_bucket_mode: quantile
+  model:
+    _target_: verl.workers.config.HFModelConfig
+    path: ${model_path}
+    hf_config_path: null
+    tokenizer_path: null
+    use_shm: false
+    trust_remote_code: false
+    custom_chat_template: null
+    external_lib: null
+    override_config: {}
+    enable_gradient_checkpointing: true
+    enable_activation_offload: false
+    use_remove_padding: false
+    lora_rank: ${lora.rank}
+    lora_alpha: ${lora.alpha}
+    target_modules: ${lora.target_modules}
+    exclude_modules: null
+    use_liger: false
+    use_fused_kernels: false
+    fused_kernel_options:
+      impl_backend: torch
+  hybrid_engine: true
+  nccl_timeout: 600
+data:
+  tokenizer: null
+  use_shm: false
+  train_files: ~/data/rlhf/gsm8k/train.parquet
+  val_files: ~/data/rlhf/gsm8k/test.parquet
+  prompt_key: prompt
+  reward_fn_key: data_source
+  max_prompt_length: null
+  max_response_length: null
+  train_batch_size: null
+  val_batch_size: null
+  return_raw_input_ids: false
+  return_raw_chat: false
+  return_full_prompt: false
+  shuffle: true
+  dataloader_num_workers: 8
+  validation_shuffle: false
+  filter_overlong_prompts: false
+  filter_overlong_prompts_workers: 1
+  truncation: error
+  image_key: images
+  video_key: videos
+  trust_remote_code: false
+  custom_cls:
+    path: null
+    name: null
+  return_multi_modal_inputs: true
+  sampler:
+    class_path: null
+    class_name: null
+  datagen:
+    path: null
+    name: null
+  apply_chat_template_kwargs: {}
+critic:
+  optim:
+    _target_: verl.workers.config.FSDPOptimizerConfig
+    lr: 1.0e-05
+    lr_warmup_steps_ratio: 0.0
+    total_training_steps: -1
+    weight_decay: 0.01
+    lr_warmup_steps: -1
+    betas:
+    - 0.9
+    - 0.999
+    clip_grad: 1.0
+    min_lr_ratio: 0.0
+    num_cycles: 0.5
+    warmup_style: constant
+  model:
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    path: ${model_path}
+    tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+    override_config: {}
+    external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+    trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+    _target_: verl.workers.config.FSDPCriticModelCfg
+    use_shm: false
+    enable_gradient_checkpointing: true
+    enable_activation_offload: false
+    use_remove_padding: false
+    lora_rank: ${lora.rank}
+    lora_alpha: ${lora.alpha}
+    target_modules: ${lora.target_modules}
+  _target_: verl.workers.config.FSDPCriticConfig
+  rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+  strategy: fsdp
+  enable: null
+  ppo_mini_batch_size: ${ppo_mini_batch_size}
+  ppo_micro_batch_size: null
+  ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+  use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+  ppo_max_token_len_per_gpu: 32768
+  forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+  ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+  shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+  cliprange_value: 0.5
+  loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+  checkpoint:
+    _target_: verl.trainer.config.CheckpointConfig
+    save_contents:
+    - model
+    - optimizer
+    - extra
+    load_contents: ${.save_contents}
+    async_save: false
+  profiler:
+    _target_: verl.utils.profiler.ProfilerConfig
+    tool: ${oc.select:global_profiler.tool,null}
+    enable: false
+    all_ranks: false
+    ranks: []
+    save_path: ${oc.select:global_profiler.save_path,null}
+    tool_config:
+      nsys:
+        _target_: verl.utils.profiler.config.NsightToolConfig
+        discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+      npu:
+        _target_: verl.utils.profiler.config.NPUToolConfig
+        contents: []
+        level: level1
+        analysis: true
+        discrete: false
+      torch:
+        _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+        step_start: 0
+        step_end: null
+      torch_memory:
+        _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+        trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+        stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+  forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+  forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+  ulysses_sequence_parallel_size: 1
+  grad_clip: 1.0
+reward_model:
+  enable: false
+  enable_resource_pool: false
+  n_gpus_per_node: 0
+  nnodes: 0
+  strategy: fsdp
+  model:
+    input_tokenizer: ${actor_rollout_ref.model.path}
+    path: ~/models/FsfairX-LLaMA3-RM-v0.1
+    external_lib: ${actor_rollout_ref.model.external_lib}
+    trust_remote_code: false
+    use_shm: false
+    use_remove_padding: false
+    use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+  micro_batch_size: null
+  micro_batch_size_per_gpu: null
+  max_length: null
+  use_dynamic_bsz: ${critic.use_dynamic_bsz}
+  forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+  reward_manager: naive
+  launch_reward_fn_async: false
+  sandbox_fusion:
+    url: null
+    max_concurrent: 64
+    memory_limit_mb: 1024
+  profiler:
+    _target_: verl.utils.profiler.ProfilerConfig
+    tool: ${oc.select:global_profiler.tool,null}
+    enable: false
+    all_ranks: false
+    ranks: []
+    save_path: ${oc.select:global_profiler.save_path,null}
+    tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+  ulysses_sequence_parallel_size: 1
+custom_reward_function:
+  path: null
+  name: compute_score
+algorithm:
+  _target_: verl.trainer.config.AlgoConfig
+  gamma: 1.0
+  lam: 1.0
+  adv_estimator: gae
+  norm_adv_by_std_in_grpo: true
+  use_kl_in_reward: false
+  kl_penalty: kl
+  kl_ctrl:
+    _target_: verl.trainer.config.KLControlConfig
+    type: fixed
+    kl_coef: 0.0
+    horizon: 10000
+    target_kl: 0.1
+  use_pf_ppo: false
+  pf_ppo:
+    reweight_method: pow
+    weight_pow: 2.0
+  high_level_gamma: 0.95
+  bi_level_gae: false
+  zero_task_advantage: false
+  soft_advantage_reweight: false
+trainer:
+  balance_batch: true
+  total_epochs: 30
+  total_training_steps: 200
+  project_name: ragen
+  experiment_name: rubikscube2_withthink_fulltrajc_sa
+  logger:
+  - console
+  - wandb
+  log_val_generations: 0
+  rollout_data_dir: null
+  validation_data_dir: null
+  nnodes: 1
+  n_gpus_per_node: 8
+  save_freq: -1
+  esi_redundant_time: 0
+  resume_mode: auto
+  resume_from_path: null
+  val_before_train: true
+  val_only: false
+  test_freq: 10
+  critic_warmup: 0
+  default_hdfs_dir: null
+  del_local_ckpt_after_load: false
+  default_local_dir: checkpoints/${trainer.project_name}/${trainer.experiment_name}
+  max_actor_ckpt_to_keep: 1
+  max_critic_ckpt_to_keep: 1
+  ray_wait_register_center_timeout: 300
+  device: cuda
+  use_legacy_worker_impl: auto
+  local_log_dir: results/
+  validation_steps: 1
+  generations_to_log_to_wandb:
+    val: 20
+  log_group_rv_table: false
+  gradient_analysis_mode: false
+  gradient_analysis_every: 50
+  gradient_analysis_env_groups: null
+  gradient_analysis_group_size: null
+  gradient_analysis_log_prefilter: false
+  gradient_analysis_only: false
+  exit_after_gradient_analysis: false
+global_profiler:
+  _target_: verl.utils.profiler.ProfilerConfig
+  tool: null
+  steps: null
+  profile_continuous_steps: false
+  save_path: outputs/profile
+  global_tool_config:
+    nsys:
+      _target_: verl.utils.profiler.config.NsightToolConfig
+      discrete: false
+      controller_nsight_options:
+        trace: cuda,nvtx,cublas,ucx
+        cuda-memory-usage: 'true'
+        cuda-graph-trace: graph
+      worker_nsight_options:
+        trace: cuda,nvtx,cublas,ucx
+        cuda-memory-usage: 'true'
+        cuda-graph-trace: graph
+        capture-range: cudaProfilerApi
+        capture-range-end: null
+        kill: none
+    torch_memory:
+      trace_alloc_max_entries: 100000
+      stack_depth: 32
+      context: all
+      stacks: all
+      kw_args: {}
+ray_kwargs:
+  ray_init:
+    num_cpus: null
+  timeline_json_file: null
+custom_envs:
+  SimpleSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 20
+    env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+      \ when reasoning:\n1. First compare the box position with the target position;\
+      \ the useful push directions are usually the directions that reduce their row/column\
+      \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+      \ push direction. A move that only repositions the player can be useful if it\
+      \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+      \ dead end unless that square is the target or clearly on the only path to the\
+      \ target.\n4. Prefer short plans that move the single box steadily toward the\
+      \ target; avoid wandering moves that do not improve player position or box position.\n\
+      5. If the box and target are aligned in the same row or column, try to keep\
+      \ the box on that line and push along it.\n6. If they are not aligned, first\
+      \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+      7. Check that after each push, the player can still reach the next required\
+      \ pushing side of the box.\n8. Output only the required XML-like format and\
+      \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+      \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+      \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+      \ pull a box. \nThe answer should be a sequence of actions, like <answer>Right\
+      \ || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 2
+      max_steps: 100
+  LargerSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+      \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+      \ you can push it by moving in the same direction. \nYou cannot push a box through\
+      \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+      \ like <answer>Right || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 8
+      dim_y: 8
+      num_boxes: 2
+      max_steps: 100
+      search_depth: 10
+  SokobanDifferentGridVocab:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+      \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+      \ you can push it by moving in the same direction. \nYou cannot push a box through\
+      \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+      \ like <answer>Right || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      search_depth: 30
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      grid_lookup:
+        0: W
+        1: .
+        2: G
+        3: C
+        4: B
+        5: A
+        6: '@'
+      grid_vocab:
+        W: wall
+        .: empty
+        G: target
+        C: box on target
+        B: box
+        A: player
+        '@': player on target
+  CoordSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 20
+    env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+      \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+      \ the zero-indexed coordinates of the player, each box, and each target. \n\
+      Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+      \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+      \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+      \ pull a box.\nThe answer should be a sequence of actions, like <answer>Right\
+      \ || Right || Up</answer>.\n"
+    max_tokens: 120
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      observation_format: grid_coord
+  VisualSimpleSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: You are solving the Sokoban puzzle. You are the player and you
+      need to push all boxes to targets. When you are right next to a box, you can
+      push it by moving in the same direction. You cannot push a box through a wall,
+      and you cannot pull a box. The answer should be a sequence of actions, like
+      <answer>Right || Right || Up</answer>
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      render_mode: rgb_array
+  Alfworld:
+    env_type: alfworld
+    max_actions_per_traj: 50
+    parallel_friendly: false
+    max_workers: 1
+    env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+      Complete household tasks by navigating and interacting with objects.
+
+
+      You should first reason step-by-step about the current situation. This reasoning
+      process MUST be enclosed within <think> </think> tags.
+
+      Once you''ve finished your reasoning, you should choose an admissible action
+      for current step and present it within <answer>...</answer> tags.
+
+      '
+    max_tokens: 512
+    env_config:
+      eval_dataset: eval_in_distribution
+  AlfworldOOD:
+    env_type: alfworld
+    max_actions_per_traj: 50
+    parallel_friendly: false
+    max_workers: 1
+    env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+      Complete household tasks by navigating and interacting with objects.
+
+
+      You should first reason step-by-step about the current situation. This reasoning
+      process MUST be enclosed within <think> </think> tags.
+
+      Once you''ve finished your reasoning, you should choose an admissible action
+      for current step and present it within <answer>...</answer> tags.
+
+      '
+    max_tokens: 512
+    env_config:
+      eval_dataset: eval_out_of_distribution
+  Countdown:
+    env_type: countdown
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving the Countdown puzzle. You should use the num
+      list to create an equation that equals the target. Example answer format: <think>
+      To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+      = 4. So the answer is 2 + 5 - 3 = 4. </think><answer>2 + 5 - 3</answer>'
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config: null
+  Bandit:
+    env_type: bandit
+    max_actions_per_traj: 1
+    env_instruction: ''
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      split: train
+  BanditTest:
+    env_type: bandit
+    max_actions_per_traj: 1
+    env_instruction: ''
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      split: test
+  DeepCoder:
+    env_type: deepcoder
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving a coding task. Provide a complete Python function
+      solution only. Format: <answer>...</answer>'
+    max_tokens: 8000
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 1
+  FrozenLake:
+    env_type: frozen_lake
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+      go to the target. You may move to the unintended direction due to the slippery
+      ice. Example answer format: <think>To forbid the hole and go to the target,
+      I should go left then go up.</think><answer>Left || Up</answer>'
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      success_rate: 0.8
+  CoordFrozenLake:
+    env_type: frozen_lake
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+      both a symbol grid and zero-indexed coordinates for the start, goal, player,
+      and any holes.
+
+      Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+      (5, 5).
+
+      Beware that the ice is slippery, so the agent might slide and end up in an unintended
+      tile.
+
+      Respond with a sequence of actions such as <answer>Left || Up || Up</answer>.
+
+      '
+    max_tokens: 120
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      observation_format: grid_coord
+      success_rate: 0.8
+  MetamathQA:
+    env_type: metamathqa
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving Math problems. '
+    max_tokens: 100
+    env_config: null
+  WebShopFull:
+    env_type: webshop
+    max_actions_per_traj: 15
+    env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+      environment.
+    max_tokens: 200
+    env_config:
+      dataset: full
+  WebShop:
+    env_type: webshop
+    max_actions_per_traj: 9
+    env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+      a product that close to the production description. You need to search, read
+      the search results, pick a product, choose the size and color and buy. You should
+      only choose action from the available actions list provided later.  Example
+      process: I need a gingko light and 20x20 pillow cover that is hand painted.
+      First search[gingko light 20x20 pillow cover hand painted], answer format: <answer>search[blanket
+      with fleece throw]</answer>. Valid answer is search[<keywords>] or click[<clickable>].'
+    max_tokens: 200
+    env_config:
+      dataset: small
+  Lean:
+    env_type: lean
+    max_actions_per_traj: 30
+    env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+      propose a sequence of tactics that completes the proof. Think step by step about
+      which tactics to apply next. Provide tactics separated by '||', for example
+      <answer>intro || simp || rfl</answer>.
+    max_tokens: 512
+    parallel_friendly: true
+    max_workers: 32
+    env_config: null
+  SimpleSudoku:
+    env_type: sudoku
+    max_actions_per_traj: 20
+    env_instruction: 'You are a careful 4x4 Sudoku solver. Use these reusable abstractions
+      when reasoning:
+
+      1. In <think>, explain the constraint logic behind the move, not just the final
+      placement. Mention which row, column, or 2x2 box makes the move safe or forced.
+
+      2. Treat each move as a constraint-preserving placement: place a number only
+      if it does not already appear in the same row, column, or 2x2 box.
+
+      3. First look for highly forced cells. If an empty cell has only one legal candidate
+      after checking its row, column, and box, fill it immediately and explain why
+      other numbers are excluded.
+
+      4. If no cell is obviously forced, scan each row, column, and 2x2 box for missing
+      numbers. If a missing number can go in only one empty position within that unit,
+      place it there and state that unit-level reason.
+
+      5. Prefer moves that reduce uncertainty and create new forced cells for the
+      next turn. A good move should make the remaining puzzle more constrained, not
+      more ambiguous.
+
+      6. Solve incrementally: choose exactly one placement, explain it briefly in
+      <think>, then output that one move in <answer>.
+
+      7. Never modify bracketed initial cells or already-filled cells. Only place
+      numbers into dots.
+
+      8. Avoid exploratory guesses when a forced move exists. In this environment,
+      reliable progress usually comes from constraint propagation rather than trial-and-error.
+
+      9. If a previous move was invalid or the board did not change, do not repeat
+      the same placement. Recompute legal candidates and explain the corrected constraint-consistent
+      choice.
+
+      10. Use row, column, and box agreement as confidence: the strongest placements
+      are those supported by multiple constraints at once.
+
+      11. Keep <think> concise but meaningful: identify the target cell, list or compare
+      its legal candidates, and give the decisive constraint.
+
+      12. Output only the required XML-like format and choose valid Sudoku placements.
+
+
+      You are solving a Sudoku puzzle. Fill in the grid so that every row, column,
+      and 2x2 box contains the numbers 1-4 without repetition.
+
+      Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+      shown as dots (.).
+
+      Place numbers one at a time using the format: <answer>place 1 at row 2 col 3</answer>
+
+      Always output: <think> [brief constraint-based reasoning] </think> <answer>
+      [one placement] </answer>
+
+      The environment will provide feedback on valid/invalid moves and show conflicts
+      if any occur.
+
+      '
+    max_tokens: 150
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      grid_size: 4
+      difficulty: easy
+      render_format: with_feedback
+      show_conflicts: false
+      show_valid_numbers: false
+      max_steps: 20
+  MediumSudoku:
+    env_type: sudoku
+    max_actions_per_traj: 30
+    env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+      row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+      Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+      shown as dots (.).
+
+      Place numbers one at a time using the format: <answer>place 5 at row 2 col 3</answer>
+      or <answer>2,3,5</answer>
+
+      The environment will provide feedback on valid/invalid moves and show conflicts
+      if any occur.
+
+      '
+    max_tokens: 150
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      grid_size: 9
+      difficulty: medium
+      render_format: with_feedback
+      show_conflicts: true
+      show_valid_numbers: true
+      max_steps: 81
+  SearchQA:
+    env_type: search
+    max_actions_per_traj: 10
+    env_instruction: "You are a search agent answering questions by searching for\
+      \ information.\nUse search[your query] to find relevant documents, and finish[your\
+      \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+      \ about the current situation. This reasoning process MUST be enclosed within\
+      \ <think> </think> tags.\nThen provide your action within <answer>...</answer>\
+      \ tags.\n\nExamples:\n  <think>I need to find information about Ben Platt's\
+      \ father.</think><answer>search[Ben Platt father parent]</answer>\n  <think>Based\
+      \ on the search results, Ben Platt's father is Henry Platt.</think><answer>finish[Henry\
+      \ Platt]</answer>\n"
+    max_tokens: 300
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 10
+      max_search_results: 5
+  SearchQAMock:
+    env_type: search
+    max_actions_per_traj: 10
+    env_instruction: "You are a search agent answering questions by searching for\
+      \ information.\nUse search[your query] to find relevant documents, and finish[your\
+      \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+      \ about the current situation. This reasoning process MUST be enclosed within\
+      \ <think> </think> tags.\nThen provide your action within <answer>...</answer>\
+      \ tags.\n\nExamples:\n  <think>I need to find information about Ben Platt's\
+      \ father.</think><answer>search[Ben Platt father parent]</answer>\n  <think>Based\
+      \ on the search results, Ben Platt's father is Henry Platt.</think><answer>finish[Henry\
+      \ Platt]</answer>\n"
+    max_tokens: 300
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 10
+      max_search_results: 5
+      mock_mode: true
+  game_2048:
+    env_type: game_2048
+    max_actions_per_traj: 700
+    env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+      by sliding Up, Right, Down, or Left.
+
+      If a move is invalid (no tiles move), a small penalty is applied. Respond with
+      a single action.
+
+      Example: <answer>Up</answer>
+
+      '
+    max_tokens: 8192
+    env_config: null
+  rubikscube:
+    env_type: rubikscube
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+      is to restore the cube so that each of the faces consists of a single, unique
+      color.
+
+      Available actions use standard Singmaster notation for face rotations: U, U'',
+      D, D'', L, L'', R, R'', F, F'', B, B''.
+
+      - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+      - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+      prime ('') means 90° counter-clockwise (e.g., "R''").
+
+      Respond with a sequence of actions separated by "||".
+
+      Example: <answer>U</answer>
+
+      '
+    max_tokens: 96
+    env_config:
+      scramble_depth: 2
+      max_steps: 7
+      render_mode: text
+system:
+  CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+  train: 10000
+  val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_sokoban_box2_withthink_fulltracj_sa
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+  rank: 0
+  alpha: 64
+  target_modules: all-linear
+agent_proxy:
+  context_window_mode: full
+  max_context_window: 5
+  batch_adjust_mode: copy
+  max_turn: 25
+  action_sep: '||'
+  max_actions_per_turn: 4
+  use_turn_scores: false
+  enable_think: true
+  reward_normalization:
+    grouping: state
+    method: identity
+collapse_detection:
+  compute_freq: 5
+  micro_batch_size: 128
+  first_turn_enabled: true
+  multi_turn_enabled: true
+  num_samples: 64
+es_manager:
+  format_penalty: -0.1
+  train:
+    env_groups: 8
+    group_size: 16
+    env_configs:
+      tags:
+      - rubikscube
+      n_groups:
+      - 8
+  val:
+    env_groups: 512
+    group_size: 1
+    env_configs:
+      tags:
+      - rubikscube
+      n_groups:
+      - 512
+ctx_manager:
+  generation:
+    gen_config:
+      response_length: ${actor_rollout_ref.rollout.response_length}
+      temperature: ${actor_rollout_ref.rollout.temperature}
+      top_p: ${actor_rollout_ref.rollout.top_p}
+      top_k: ${actor_rollout_ref.rollout.top_k}
+      kwargs: null

outputs/2026-06-15/17-29-15/.hydra/hydra.yaml

@@ -0,0 +1,177 @@
+hydra:
+  run:
+    dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+  sweep:
+    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task:
+    - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+    - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+    - actor_rollout_ref.rollout.rollout_filter_value=0.9
+    - trainer.total_training_steps=200
+    - trainer.n_gpus_per_node=8
+    - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_sokoban_box2_withthink_fulltracj_sa
+    - custom_envs.rubikscube.env_config.scramble_depth=2
+    - trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa
+  job:
+    name: train
+    chdir: null
+    override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=2,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_sokoban_box2_withthink_fulltracj_sa,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa,trainer.n_gpus_per_node=8,trainer.total_training_steps=200
+    id: ???
+    num: ???
+    config_name: _10_rubikscube
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /mnt/general/wanghy/RAGEN_v2
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /mnt/general/wanghy/RAGEN_v2/config
+      schema: file
+      provider: main
+    - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-15/17-29-15
+    choices:
+      reward_model: dp_reward_model
+      critic: dp_critic
+      critic/../engine@critic.model.fsdp_config: fsdp
+      critic/../optim@critic.optim: fsdp
+      model@actor_rollout_ref.model: hf_model
+      rollout@actor_rollout_ref.rollout: rollout
+      ref@actor_rollout_ref.ref: dp_ref
+      ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+      data: legacy_data
+      actor@actor_rollout_ref.actor: dp_actor
+      actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+      actor/../optim@actor_rollout_ref.actor.optim: fsdp
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

outputs/2026-06-15/17-29-15/.hydra/overrides.yaml

@@ -0,0 +1,8 @@
+- system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- trainer.n_gpus_per_node=8
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_sokoban_box2_withthink_fulltracj_sa
+- custom_envs.rubikscube.env_config.scramble_depth=2
+- trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa

outputs/2026-06-16/13-25-02/.hydra/hydra.yaml

@@ -0,0 +1,177 @@
+hydra:
+  run:
+    dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+  sweep:
+    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task:
+    - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+    - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+    - actor_rollout_ref.rollout.rollout_filter_value=0.9
+    - trainer.total_training_steps=200
+    - trainer.n_gpus_per_node=8
+    - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_sokoban_box2_withthink_fulltracj_sa
+    - custom_envs.rubikscube.env_config.scramble_depth=2
+    - trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa
+  job:
+    name: train
+    chdir: null
+    override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=2,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_sokoban_box2_withthink_fulltracj_sa,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa,trainer.n_gpus_per_node=8,trainer.total_training_steps=200
+    id: ???
+    num: ???
+    config_name: _10_rubikscube
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /mnt/general/wanghy/RAGEN_v2
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /mnt/general/wanghy/RAGEN_v2/config
+      schema: file
+      provider: main
+    - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-16/13-25-02
+    choices:
+      reward_model: dp_reward_model
+      critic: dp_critic
+      critic/../engine@critic.model.fsdp_config: fsdp
+      critic/../optim@critic.optim: fsdp
+      model@actor_rollout_ref.model: hf_model
+      rollout@actor_rollout_ref.rollout: rollout
+      ref@actor_rollout_ref.ref: dp_ref
+      ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+      data: legacy_data
+      actor@actor_rollout_ref.actor: dp_actor
+      actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+      actor/../optim@actor_rollout_ref.actor.optim: fsdp
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

outputs/2026-06-16/13-25-02/.hydra/overrides.yaml

@@ -0,0 +1,8 @@
+- system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- trainer.n_gpus_per_node=8
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_sokoban_box2_withthink_fulltracj_sa
+- custom_envs.rubikscube.env_config.scramble_depth=2
+- trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa

outputs/2026-06-16/17-30-16/.hydra/config.yaml

@@ -0,0 +1,1048 @@
+actor_rollout_ref:
+  actor:
+    optim:
+      _target_: verl.workers.config.FSDPOptimizerConfig
+      lr: 1.0e-06
+      lr_warmup_steps_ratio: 0.0
+      total_training_steps: -1
+      weight_decay: 0.01
+      lr_warmup_steps: -1
+      betas:
+      - 0.9
+      - 0.999
+      clip_grad: 1.0
+      min_lr_ratio: 0.0
+      num_cycles: 0.5
+      warmup_style: constant
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    _target_: verl.workers.config.FSDPActorConfig
+    strategy: fsdp
+    ppo_mini_batch_size: ${ppo_mini_batch_size}
+    ppo_micro_batch_size: null
+    ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+    use_dynamic_bsz: false
+    ppo_max_token_len_per_gpu: 16384
+    clip_ratio: 0.2
+    clip_ratio_low: 0.2
+    clip_ratio_high: 0.28
+    freeze_vision_tower: false
+    policy_loss:
+      _target_: verl.workers.config.PolicyLossConfig
+      loss_mode: vanilla
+      clip_cov_ratio: 0.0002
+      clip_cov_lb: 1.0
+      clip_cov_ub: 5.0
+      kl_cov_ratio: 0.0002
+      ppo_kl_coef: 0.1
+    clip_ratio_c: 3.0
+    loss_agg_mode: token-mean
+    entropy_coeff: 0.001
+    tis_imp_ratio_cap: -1
+    use_kl_loss: false
+    use_torch_compile: true
+    kl_loss_coef: 0.0
+    kl_loss_type: kl
+    ppo_epochs: 1
+    shuffle: false
+    checkpoint:
+      _target_: verl.trainer.config.CheckpointConfig
+      save_contents:
+      - model
+      - optimizer
+      - extra
+      load_contents: ${.save_contents}
+      async_save: false
+    use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: false
+      all_ranks: false
+      ranks: []
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config:
+        nsys:
+          _target_: verl.utils.profiler.config.NsightToolConfig
+          discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+        npu:
+          _target_: verl.utils.profiler.config.NPUToolConfig
+          contents: []
+          level: level1
+          analysis: true
+          discrete: false
+        torch:
+          _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+          step_start: 0
+          step_end: null
+        torch_memory:
+          _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+          trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+          stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+    grad_clip: 1.0
+    ulysses_sequence_parallel_size: 1
+    entropy_from_logits_with_chunking: false
+    entropy_checkpointing: false
+    use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+    use_ref: true
+    grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+    filter_loss_scaling: none
+  ref:
+    strategy: ${actor_rollout_ref.actor.strategy}
+    use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+    log_prob_micro_batch_size: null
+    log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+    log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+    log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: false
+      all_ranks: false
+      ranks: []
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config:
+        nsys:
+          _target_: verl.utils.profiler.config.NsightToolConfig
+          discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+        npu:
+          _target_: verl.utils.profiler.config.NPUToolConfig
+          contents: []
+          level: level1
+          analysis: true
+          discrete: false
+        torch:
+          _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+          step_start: 0
+          step_end: null
+        torch_memory:
+          _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+          trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+          stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    model: null
+    ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+    entropy_from_logits_with_chunking: false
+    entropy_checkpointing: false
+  rollout:
+    _target_: verl.workers.config.RolloutConfig
+    name: vllm
+    mode: sync
+    temperature: 1
+    top_k: -1
+    top_p: 1
+    prompt_length: 1
+    response_length: 500
+    dtype: bfloat16
+    gpu_memory_utilization: 0.7
+    ignore_eos: false
+    enforce_eager: true
+    cudagraph_capture_sizes: null
+    free_cache_engine: true
+    tensor_model_parallel_size: 1
+    data_parallel_size: 1
+    expert_parallel_size: 1
+    max_num_batched_tokens: 16384
+    max_model_len: 16384
+    max_num_seqs: 1024
+    enable_chunked_prefill: true
+    enable_prefix_caching: true
+    load_format: auto
+    log_prob_micro_batch_size: null
+    log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+    log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+    log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+    disable_log_stats: true
+    do_sample: true
+    'n': 1
+    over_sample_rate: 0
+    multi_stage_wake_up: false
+    engine_kwargs:
+      vllm: {}
+      sglang: {}
+    val_kwargs:
+      _target_: verl.workers.config.SamplingConfig
+      top_k: -1
+      top_p: 1.0
+      temperature: 0.5
+      'n': 1
+      do_sample: true
+    multi_turn:
+      _target_: verl.workers.config.MultiTurnConfig
+      enable: false
+      max_assistant_turns: null
+      tool_config_path: null
+      max_user_turns: null
+      max_parallel_calls: 1
+      max_tool_response_length: 256
+      tool_response_truncate_side: middle
+      interaction_config_path: null
+      use_inference_chat_template: false
+      tokenization_sanity_check_mode: strict
+      format: hermes
+      num_repeat_rollouts: null
+    calculate_log_probs: false
+    agent:
+      _target_: verl.workers.config.AgentLoopConfig
+      num_workers: 8
+      agent_loop_config_path: null
+      custom_async_server:
+        _target_: verl.workers.config.CustomAsyncServerConfig
+        path: null
+        name: null
+    update_weights_bucket_megabytes: 512
+    trace:
+      _target_: verl.workers.config.TraceConfig
+      backend: null
+      token2text: false
+    skip_rollout: false
+    skip_dump_dir: /tmp/rollout_dump
+    skip_tokenizer_init: true
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+      all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+      ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+    layered_summon: false
+    rollout_filter_value: 0.9
+    rollout_filter_strategy: top_p
+    rollout_filter_type: largest
+    rollout_filter_include_zero: true
+    rollout_filter_top_p_prob_mode: linear
+    rollout_filter_selection_eps: 0.01
+    rollout_filter_empty_stop_steps: 5
+    rollout_filter_metric: reward_variance
+    gradient_analysis_num_buckets: 6
+    gradient_analysis_bucket_mode: quantile
+  model:
+    _target_: verl.workers.config.HFModelConfig
+    path: ${model_path}
+    hf_config_path: null
+    tokenizer_path: null
+    use_shm: false
+    trust_remote_code: false
+    custom_chat_template: null
+    external_lib: null
+    override_config: {}
+    enable_gradient_checkpointing: true
+    enable_activation_offload: false
+    use_remove_padding: false
+    lora_rank: ${lora.rank}
+    lora_alpha: ${lora.alpha}
+    target_modules: ${lora.target_modules}
+    exclude_modules: null
+    use_liger: false
+    use_fused_kernels: false
+    fused_kernel_options:
+      impl_backend: torch
+  hybrid_engine: true
+  nccl_timeout: 600
+data:
+  tokenizer: null
+  use_shm: false
+  train_files: ~/data/rlhf/gsm8k/train.parquet
+  val_files: ~/data/rlhf/gsm8k/test.parquet
+  prompt_key: prompt
+  reward_fn_key: data_source
+  max_prompt_length: null
+  max_response_length: null
+  train_batch_size: null
+  val_batch_size: null
+  return_raw_input_ids: false
+  return_raw_chat: false
+  return_full_prompt: false
+  shuffle: true
+  dataloader_num_workers: 8
+  validation_shuffle: false
+  filter_overlong_prompts: false
+  filter_overlong_prompts_workers: 1
+  truncation: error
+  image_key: images
+  video_key: videos
+  trust_remote_code: false
+  custom_cls:
+    path: null
+    name: null
+  return_multi_modal_inputs: true
+  sampler:
+    class_path: null
+    class_name: null
+  datagen:
+    path: null
+    name: null
+  apply_chat_template_kwargs: {}
+critic:
+  optim:
+    _target_: verl.workers.config.FSDPOptimizerConfig
+    lr: 1.0e-05
+    lr_warmup_steps_ratio: 0.0
+    total_training_steps: -1
+    weight_decay: 0.01
+    lr_warmup_steps: -1
+    betas:
+    - 0.9
+    - 0.999
+    clip_grad: 1.0
+    min_lr_ratio: 0.0
+    num_cycles: 0.5
+    warmup_style: constant
+  model:
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    path: ${model_path}
+    tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+    override_config: {}
+    external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+    trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+    _target_: verl.workers.config.FSDPCriticModelCfg
+    use_shm: false
+    enable_gradient_checkpointing: true
+    enable_activation_offload: false
+    use_remove_padding: false
+    lora_rank: ${lora.rank}
+    lora_alpha: ${lora.alpha}
+    target_modules: ${lora.target_modules}
+  _target_: verl.workers.config.FSDPCriticConfig
+  rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+  strategy: fsdp
+  enable: null
+  ppo_mini_batch_size: ${ppo_mini_batch_size}
+  ppo_micro_batch_size: null
+  ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+  use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+  ppo_max_token_len_per_gpu: 32768
+  forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+  ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+  shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+  cliprange_value: 0.5
+  loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+  checkpoint:
+    _target_: verl.trainer.config.CheckpointConfig
+    save_contents:
+    - model
+    - optimizer
+    - extra
+    load_contents: ${.save_contents}
+    async_save: false
+  profiler:
+    _target_: verl.utils.profiler.ProfilerConfig
+    tool: ${oc.select:global_profiler.tool,null}
+    enable: false
+    all_ranks: false
+    ranks: []
+    save_path: ${oc.select:global_profiler.save_path,null}
+    tool_config:
+      nsys:
+        _target_: verl.utils.profiler.config.NsightToolConfig
+        discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+      npu:
+        _target_: verl.utils.profiler.config.NPUToolConfig
+        contents: []
+        level: level1
+        analysis: true
+        discrete: false
+      torch:
+        _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+        step_start: 0
+        step_end: null
+      torch_memory:
+        _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+        trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+        stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+  forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+  forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+  ulysses_sequence_parallel_size: 1
+  grad_clip: 1.0
+reward_model:
+  enable: false
+  enable_resource_pool: false
+  n_gpus_per_node: 0
+  nnodes: 0
+  strategy: fsdp
+  model:
+    input_tokenizer: ${actor_rollout_ref.model.path}
+    path: ~/models/FsfairX-LLaMA3-RM-v0.1
+    external_lib: ${actor_rollout_ref.model.external_lib}
+    trust_remote_code: false
+    use_shm: false
+    use_remove_padding: false
+    use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+  micro_batch_size: null
+  micro_batch_size_per_gpu: null
+  max_length: null
+  use_dynamic_bsz: ${critic.use_dynamic_bsz}
+  forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+  reward_manager: naive
+  launch_reward_fn_async: false
+  sandbox_fusion:
+    url: null
+    max_concurrent: 64
+    memory_limit_mb: 1024
+  profiler:
+    _target_: verl.utils.profiler.ProfilerConfig
+    tool: ${oc.select:global_profiler.tool,null}
+    enable: false
+    all_ranks: false
+    ranks: []
+    save_path: ${oc.select:global_profiler.save_path,null}
+    tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+  ulysses_sequence_parallel_size: 1
+custom_reward_function:
+  path: null
+  name: compute_score
+algorithm:
+  _target_: verl.trainer.config.AlgoConfig
+  gamma: 1.0
+  lam: 1.0
+  adv_estimator: gae
+  norm_adv_by_std_in_grpo: true
+  use_kl_in_reward: false
+  kl_penalty: kl
+  kl_ctrl:
+    _target_: verl.trainer.config.KLControlConfig
+    type: fixed
+    kl_coef: 0.0
+    horizon: 10000
+    target_kl: 0.1
+  use_pf_ppo: false
+  pf_ppo:
+    reweight_method: pow
+    weight_pow: 2.0
+  high_level_gamma: 0.95
+  bi_level_gae: false
+  zero_task_advantage: false
+  soft_advantage_reweight: false
+trainer:
+  balance_batch: true
+  total_epochs: 30
+  total_training_steps: 200
+  project_name: ragen
+  experiment_name: rubikscube2_withthink_fulltrajc_sa
+  logger:
+  - console
+  - wandb
+  log_val_generations: 0
+  rollout_data_dir: null
+  validation_data_dir: null
+  nnodes: 1
+  n_gpus_per_node: 8
+  save_freq: -1
+  esi_redundant_time: 0
+  resume_mode: auto
+  resume_from_path: null
+  val_before_train: true
+  val_only: false
+  test_freq: 10
+  critic_warmup: 0
+  default_hdfs_dir: null
+  del_local_ckpt_after_load: false
+  default_local_dir: checkpoints/${trainer.project_name}/${trainer.experiment_name}
+  max_actor_ckpt_to_keep: 1
+  max_critic_ckpt_to_keep: 1
+  ray_wait_register_center_timeout: 300
+  device: cuda
+  use_legacy_worker_impl: auto
+  local_log_dir: results/
+  validation_steps: 1
+  generations_to_log_to_wandb:
+    val: 20
+  log_group_rv_table: false
+  gradient_analysis_mode: false
+  gradient_analysis_every: 50
+  gradient_analysis_env_groups: null
+  gradient_analysis_group_size: null
+  gradient_analysis_log_prefilter: false
+  gradient_analysis_only: false
+  exit_after_gradient_analysis: false
+global_profiler:
+  _target_: verl.utils.profiler.ProfilerConfig
+  tool: null
+  steps: null
+  profile_continuous_steps: false
+  save_path: outputs/profile
+  global_tool_config:
+    nsys:
+      _target_: verl.utils.profiler.config.NsightToolConfig
+      discrete: false
+      controller_nsight_options:
+        trace: cuda,nvtx,cublas,ucx
+        cuda-memory-usage: 'true'
+        cuda-graph-trace: graph
+      worker_nsight_options:
+        trace: cuda,nvtx,cublas,ucx
+        cuda-memory-usage: 'true'
+        cuda-graph-trace: graph
+        capture-range: cudaProfilerApi
+        capture-range-end: null
+        kill: none
+    torch_memory:
+      trace_alloc_max_entries: 100000
+      stack_depth: 32
+      context: all
+      stacks: all
+      kw_args: {}
+ray_kwargs:
+  ray_init:
+    num_cpus: null
+  timeline_json_file: null
+custom_envs:
+  SimpleSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 20
+    env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+      \ when reasoning:\n1. First compare the box position with the target position;\
+      \ the useful push directions are usually the directions that reduce their row/column\
+      \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+      \ push direction. A move that only repositions the player can be useful if it\
+      \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+      \ dead end unless that square is the target or clearly on the only path to the\
+      \ target.\n4. Prefer short plans that move the single box steadily toward the\
+      \ target; avoid wandering moves that do not improve player position or box position.\n\
+      5. If the box and target are aligned in the same row or column, try to keep\
+      \ the box on that line and push along it.\n6. If they are not aligned, first\
+      \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+      7. Check that after each push, the player can still reach the next required\
+      \ pushing side of the box.\n8. Output only the required XML-like format and\
+      \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+      \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+      \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+      \ pull a box. \nThe answer should be a sequence of actions, like <answer>Right\
+      \ || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 2
+      max_steps: 100
+  LargerSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+      \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+      \ you can push it by moving in the same direction. \nYou cannot push a box through\
+      \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+      \ like <answer>Right || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 8
+      dim_y: 8
+      num_boxes: 2
+      max_steps: 100
+      search_depth: 10
+  SokobanDifferentGridVocab:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+      \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+      \ you can push it by moving in the same direction. \nYou cannot push a box through\
+      \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+      \ like <answer>Right || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      search_depth: 30
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      grid_lookup:
+        0: W
+        1: .
+        2: G
+        3: C
+        4: B
+        5: A
+        6: '@'
+      grid_vocab:
+        W: wall
+        .: empty
+        G: target
+        C: box on target
+        B: box
+        A: player
+        '@': player on target
+  CoordSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 20
+    env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+      \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+      \ the zero-indexed coordinates of the player, each box, and each target. \n\
+      Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+      \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+      \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+      \ pull a box.\nThe answer should be a sequence of actions, like <answer>Right\
+      \ || Right || Up</answer>.\n"
+    max_tokens: 120
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      observation_format: grid_coord
+  VisualSimpleSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: You are solving the Sokoban puzzle. You are the player and you
+      need to push all boxes to targets. When you are right next to a box, you can
+      push it by moving in the same direction. You cannot push a box through a wall,
+      and you cannot pull a box. The answer should be a sequence of actions, like
+      <answer>Right || Right || Up</answer>
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      render_mode: rgb_array
+  Alfworld:
+    env_type: alfworld
+    max_actions_per_traj: 50
+    parallel_friendly: false
+    max_workers: 1
+    env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+      Complete household tasks by navigating and interacting with objects.
+
+
+      You should first reason step-by-step about the current situation. This reasoning
+      process MUST be enclosed within <think> </think> tags.
+
+      Once you''ve finished your reasoning, you should choose an admissible action
+      for current step and present it within <answer>...</answer> tags.
+
+      '
+    max_tokens: 512
+    env_config:
+      eval_dataset: eval_in_distribution
+  AlfworldOOD:
+    env_type: alfworld
+    max_actions_per_traj: 50
+    parallel_friendly: false
+    max_workers: 1
+    env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+      Complete household tasks by navigating and interacting with objects.
+
+
+      You should first reason step-by-step about the current situation. This reasoning
+      process MUST be enclosed within <think> </think> tags.
+
+      Once you''ve finished your reasoning, you should choose an admissible action
+      for current step and present it within <answer>...</answer> tags.
+
+      '
+    max_tokens: 512
+    env_config:
+      eval_dataset: eval_out_of_distribution
+  Countdown:
+    env_type: countdown
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving the Countdown puzzle. You should use the num
+      list to create an equation that equals the target. Example answer format: <think>
+      To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+      = 4. So the answer is 2 + 5 - 3 = 4. </think><answer>2 + 5 - 3</answer>'
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config: null
+  Bandit:
+    env_type: bandit
+    max_actions_per_traj: 1
+    env_instruction: ''
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      split: train
+  BanditTest:
+    env_type: bandit
+    max_actions_per_traj: 1
+    env_instruction: ''
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      split: test
+  DeepCoder:
+    env_type: deepcoder
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving a coding task. Provide a complete Python function
+      solution only. Format: <answer>...</answer>'
+    max_tokens: 8000
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 1
+  FrozenLake:
+    env_type: frozen_lake
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+      go to the target. You may move to the unintended direction due to the slippery
+      ice. Example answer format: <think>To forbid the hole and go to the target,
+      I should go left then go up.</think><answer>Left || Up</answer>'
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      success_rate: 0.8
+  CoordFrozenLake:
+    env_type: frozen_lake
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+      both a symbol grid and zero-indexed coordinates for the start, goal, player,
+      and any holes.
+
+      Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+      (5, 5).
+
+      Beware that the ice is slippery, so the agent might slide and end up in an unintended
+      tile.
+
+      Respond with a sequence of actions such as <answer>Left || Up || Up</answer>.
+
+      '
+    max_tokens: 120
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      observation_format: grid_coord
+      success_rate: 0.8
+  MetamathQA:
+    env_type: metamathqa
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving Math problems. '
+    max_tokens: 100
+    env_config: null
+  WebShopFull:
+    env_type: webshop
+    max_actions_per_traj: 15
+    env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+      environment.
+    max_tokens: 200
+    env_config:
+      dataset: full
+  WebShop:
+    env_type: webshop
+    max_actions_per_traj: 9
+    env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+      a product that close to the production description. You need to search, read
+      the search results, pick a product, choose the size and color and buy. You should
+      only choose action from the available actions list provided later.  Example
+      process: I need a gingko light and 20x20 pillow cover that is hand painted.
+      First search[gingko light 20x20 pillow cover hand painted], answer format: <answer>search[blanket
+      with fleece throw]</answer>. Valid answer is search[<keywords>] or click[<clickable>].'
+    max_tokens: 200
+    env_config:
+      dataset: small
+  Lean:
+    env_type: lean
+    max_actions_per_traj: 30
+    env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+      propose a sequence of tactics that completes the proof. Think step by step about
+      which tactics to apply next. Provide tactics separated by '||', for example
+      <answer>intro || simp || rfl</answer>.
+    max_tokens: 512
+    parallel_friendly: true
+    max_workers: 32
+    env_config: null
+  SimpleSudoku:
+    env_type: sudoku
+    max_actions_per_traj: 20
+    env_instruction: 'You are a careful 4x4 Sudoku solver. Use these reusable abstractions
+      when reasoning:
+
+      1. In <think>, explain the constraint logic behind the move, not just the final
+      placement. Mention which row, column, or 2x2 box makes the move safe or forced.
+
+      2. Treat each move as a constraint-preserving placement: place a number only
+      if it does not already appear in the same row, column, or 2x2 box.
+
+      3. First look for highly forced cells. If an empty cell has only one legal candidate
+      after checking its row, column, and box, fill it immediately and explain why
+      other numbers are excluded.
+
+      4. If no cell is obviously forced, scan each row, column, and 2x2 box for missing
+      numbers. If a missing number can go in only one empty position within that unit,
+      place it there and state that unit-level reason.
+
+      5. Prefer moves that reduce uncertainty and create new forced cells for the
+      next turn. A good move should make the remaining puzzle more constrained, not
+      more ambiguous.
+
+      6. Solve incrementally: choose exactly one placement, explain it briefly in
+      <think>, then output that one move in <answer>.
+
+      7. Never modify bracketed initial cells or already-filled cells. Only place
+      numbers into dots.
+
+      8. Avoid exploratory guesses when a forced move exists. In this environment,
+      reliable progress usually comes from constraint propagation rather than trial-and-error.
+
+      9. If a previous move was invalid or the board did not change, do not repeat
+      the same placement. Recompute legal candidates and explain the corrected constraint-consistent
+      choice.
+
+      10. Use row, column, and box agreement as confidence: the strongest placements
+      are those supported by multiple constraints at once.
+
+      11. Keep <think> concise but meaningful: identify the target cell, list or compare
+      its legal candidates, and give the decisive constraint.
+
+      12. Output only the required XML-like format and choose valid Sudoku placements.
+
+
+      You are solving a Sudoku puzzle. Fill in the grid so that every row, column,
+      and 2x2 box contains the numbers 1-4 without repetition.
+
+      Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+      shown as dots (.).
+
+      Place numbers one at a time using the format: <answer>place 1 at row 2 col 3</answer>
+
+      Always output: <think> [brief constraint-based reasoning] </think> <answer>
+      [one placement] </answer>
+
+      The environment will provide feedback on valid/invalid moves and show conflicts
+      if any occur.
+
+      '
+    max_tokens: 150
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      grid_size: 4
+      difficulty: easy
+      render_format: with_feedback
+      show_conflicts: false
+      show_valid_numbers: false
+      max_steps: 20
+  MediumSudoku:
+    env_type: sudoku
+    max_actions_per_traj: 30
+    env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+      row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+      Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+      shown as dots (.).
+
+      Place numbers one at a time using the format: <answer>place 5 at row 2 col 3</answer>
+      or <answer>2,3,5</answer>
+
+      The environment will provide feedback on valid/invalid moves and show conflicts
+      if any occur.
+
+      '
+    max_tokens: 150
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      grid_size: 9
+      difficulty: medium
+      render_format: with_feedback
+      show_conflicts: true
+      show_valid_numbers: true
+      max_steps: 81
+  SearchQA:
+    env_type: search
+    max_actions_per_traj: 10
+    env_instruction: "You are a search agent answering questions by searching for\
+      \ information.\nUse search[your query] to find relevant documents, and finish[your\
+      \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+      \ about the current situation. This reasoning process MUST be enclosed within\
+      \ <think> </think> tags.\nThen provide your action within <answer>...</answer>\
+      \ tags.\n\nExamples:\n  <think>I need to find information about Ben Platt's\
+      \ father.</think><answer>search[Ben Platt father parent]</answer>\n  <think>Based\
+      \ on the search results, Ben Platt's father is Henry Platt.</think><answer>finish[Henry\
+      \ Platt]</answer>\n"
+    max_tokens: 300
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 10
+      max_search_results: 5
+  SearchQAMock:
+    env_type: search
+    max_actions_per_traj: 10
+    env_instruction: "You are a search agent answering questions by searching for\
+      \ information.\nUse search[your query] to find relevant documents, and finish[your\
+      \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+      \ about the current situation. This reasoning process MUST be enclosed within\
+      \ <think> </think> tags.\nThen provide your action within <answer>...</answer>\
+      \ tags.\n\nExamples:\n  <think>I need to find information about Ben Platt's\
+      \ father.</think><answer>search[Ben Platt father parent]</answer>\n  <think>Based\
+      \ on the search results, Ben Platt's father is Henry Platt.</think><answer>finish[Henry\
+      \ Platt]</answer>\n"
+    max_tokens: 300
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 10
+      max_search_results: 5
+      mock_mode: true
+  game_2048:
+    env_type: game_2048
+    max_actions_per_traj: 700
+    env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+      by sliding Up, Right, Down, or Left.
+
+      If a move is invalid (no tiles move), a small penalty is applied. Respond with
+      a single action.
+
+      Example: <answer>Up</answer>
+
+      '
+    max_tokens: 8192
+    env_config: null
+  rubikscube:
+    env_type: rubikscube
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+      is to restore the cube so that each of the faces consists of a single, unique
+      color.
+
+      Available actions use standard Singmaster notation for face rotations: U, U'',
+      D, D'', L, L'', R, R'', F, F'', B, B''.
+
+      - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+      - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+      prime ('') means 90° counter-clockwise (e.g., "R''").
+
+      Respond with a sequence of actions separated by "||".
+
+      Example: <answer>U</answer>
+
+      '
+    max_tokens: 96
+    env_config:
+      scramble_depth: 2
+      max_steps: 7
+      render_mode: text
+system:
+  CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+  train: 10000
+  val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sas
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+  rank: 0
+  alpha: 64
+  target_modules: all-linear
+agent_proxy:
+  context_window_mode: full
+  max_context_window: 5
+  batch_adjust_mode: copy
+  max_turn: 10
+  action_sep: '||'
+  max_actions_per_turn: 4
+  use_turn_scores: false
+  enable_think: true
+  reward_normalization:
+    grouping: state
+    method: identity
+collapse_detection:
+  compute_freq: 5
+  micro_batch_size: 128
+  first_turn_enabled: true
+  multi_turn_enabled: true
+  num_samples: 64
+es_manager:
+  format_penalty: -0.1
+  train:
+    env_groups: 8
+    group_size: 16
+    env_configs:
+      tags:
+      - rubikscube
+      n_groups:
+      - 8
+  val:
+    env_groups: 512
+    group_size: 1
+    env_configs:
+      tags:
+      - rubikscube
+      n_groups:
+      - 512
+ctx_manager:
+  generation:
+    gen_config:
+      response_length: ${actor_rollout_ref.rollout.response_length}
+      temperature: ${actor_rollout_ref.rollout.temperature}
+      top_p: ${actor_rollout_ref.rollout.top_p}
+      top_k: ${actor_rollout_ref.rollout.top_k}
+      kwargs: null

outputs/2026-06-16/17-30-16/.hydra/hydra.yaml

@@ -0,0 +1,177 @@
+hydra:
+  run:
+    dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+  sweep:
+    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task:
+    - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+    - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+    - actor_rollout_ref.rollout.rollout_filter_value=0.9
+    - trainer.total_training_steps=200
+    - trainer.n_gpus_per_node=8
+    - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sas
+    - custom_envs.rubikscube.env_config.scramble_depth=2
+    - trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa
+  job:
+    name: train
+    chdir: null
+    override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=2,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sas,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa,trainer.n_gpus_per_node=8,trainer.total_training_steps=200
+    id: ???
+    num: ???
+    config_name: _10_rubikscube
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /mnt/general/wanghy/RAGEN_v2
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /mnt/general/wanghy/RAGEN_v2/config
+      schema: file
+      provider: main
+    - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-16/17-30-16
+    choices:
+      reward_model: dp_reward_model
+      critic: dp_critic
+      critic/../engine@critic.model.fsdp_config: fsdp
+      critic/../optim@critic.optim: fsdp
+      model@actor_rollout_ref.model: hf_model
+      rollout@actor_rollout_ref.rollout: rollout
+      ref@actor_rollout_ref.ref: dp_ref
+      ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+      data: legacy_data
+      actor@actor_rollout_ref.actor: dp_actor
+      actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+      actor/../optim@actor_rollout_ref.actor.optim: fsdp
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

outputs/2026-06-16/17-30-16/.hydra/overrides.yaml

@@ -0,0 +1,8 @@
+- system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- trainer.n_gpus_per_node=8
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sas
+- custom_envs.rubikscube.env_config.scramble_depth=2
+- trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa

outputs/2026-06-16/18-42-33/.hydra/config.yaml

@@ -0,0 +1,1048 @@
+actor_rollout_ref:
+  actor:
+    optim:
+      _target_: verl.workers.config.FSDPOptimizerConfig
+      lr: 1.0e-06
+      lr_warmup_steps_ratio: 0.0
+      total_training_steps: -1
+      weight_decay: 0.01
+      lr_warmup_steps: -1
+      betas:
+      - 0.9
+      - 0.999
+      clip_grad: 1.0
+      min_lr_ratio: 0.0
+      num_cycles: 0.5
+      warmup_style: constant
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    _target_: verl.workers.config.FSDPActorConfig
+    strategy: fsdp
+    ppo_mini_batch_size: ${ppo_mini_batch_size}
+    ppo_micro_batch_size: null
+    ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+    use_dynamic_bsz: false
+    ppo_max_token_len_per_gpu: 16384
+    clip_ratio: 0.2
+    clip_ratio_low: 0.2
+    clip_ratio_high: 0.28
+    freeze_vision_tower: false
+    policy_loss:
+      _target_: verl.workers.config.PolicyLossConfig
+      loss_mode: vanilla
+      clip_cov_ratio: 0.0002
+      clip_cov_lb: 1.0
+      clip_cov_ub: 5.0
+      kl_cov_ratio: 0.0002
+      ppo_kl_coef: 0.1
+    clip_ratio_c: 3.0
+    loss_agg_mode: token-mean
+    entropy_coeff: 0.001
+    tis_imp_ratio_cap: -1
+    use_kl_loss: false
+    use_torch_compile: true
+    kl_loss_coef: 0.0
+    kl_loss_type: kl
+    ppo_epochs: 1
+    shuffle: false
+    checkpoint:
+      _target_: verl.trainer.config.CheckpointConfig
+      save_contents:
+      - model
+      - optimizer
+      - extra
+      load_contents: ${.save_contents}
+      async_save: false
+    use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: false
+      all_ranks: false
+      ranks: []
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config:
+        nsys:
+          _target_: verl.utils.profiler.config.NsightToolConfig
+          discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+        npu:
+          _target_: verl.utils.profiler.config.NPUToolConfig
+          contents: []
+          level: level1
+          analysis: true
+          discrete: false
+        torch:
+          _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+          step_start: 0
+          step_end: null
+        torch_memory:
+          _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+          trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+          stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+    grad_clip: 1.0
+    ulysses_sequence_parallel_size: 1
+    entropy_from_logits_with_chunking: false
+    entropy_checkpointing: false
+    use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+    use_ref: true
+    grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+    filter_loss_scaling: none
+  ref:
+    strategy: ${actor_rollout_ref.actor.strategy}
+    use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+    log_prob_micro_batch_size: null
+    log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+    log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+    log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: false
+      all_ranks: false
+      ranks: []
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config:
+        nsys:
+          _target_: verl.utils.profiler.config.NsightToolConfig
+          discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+        npu:
+          _target_: verl.utils.profiler.config.NPUToolConfig
+          contents: []
+          level: level1
+          analysis: true
+          discrete: false
+        torch:
+          _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+          step_start: 0
+          step_end: null
+        torch_memory:
+          _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+          trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+          stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    model: null
+    ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+    entropy_from_logits_with_chunking: false
+    entropy_checkpointing: false
+  rollout:
+    _target_: verl.workers.config.RolloutConfig
+    name: vllm
+    mode: sync
+    temperature: 1
+    top_k: -1
+    top_p: 1
+    prompt_length: 1
+    response_length: 500
+    dtype: bfloat16
+    gpu_memory_utilization: 0.7
+    ignore_eos: false
+    enforce_eager: true
+    cudagraph_capture_sizes: null
+    free_cache_engine: true
+    tensor_model_parallel_size: 1
+    data_parallel_size: 1
+    expert_parallel_size: 1
+    max_num_batched_tokens: 16384
+    max_model_len: 16384
+    max_num_seqs: 1024
+    enable_chunked_prefill: true
+    enable_prefix_caching: true
+    load_format: auto
+    log_prob_micro_batch_size: null
+    log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+    log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+    log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+    disable_log_stats: true
+    do_sample: true
+    'n': 1
+    over_sample_rate: 0
+    multi_stage_wake_up: false
+    engine_kwargs:
+      vllm: {}
+      sglang: {}
+    val_kwargs:
+      _target_: verl.workers.config.SamplingConfig
+      top_k: -1
+      top_p: 1.0
+      temperature: 0.5
+      'n': 1
+      do_sample: true
+    multi_turn:
+      _target_: verl.workers.config.MultiTurnConfig
+      enable: false
+      max_assistant_turns: null
+      tool_config_path: null
+      max_user_turns: null
+      max_parallel_calls: 1
+      max_tool_response_length: 256
+      tool_response_truncate_side: middle
+      interaction_config_path: null
+      use_inference_chat_template: false
+      tokenization_sanity_check_mode: strict
+      format: hermes
+      num_repeat_rollouts: null
+    calculate_log_probs: false
+    agent:
+      _target_: verl.workers.config.AgentLoopConfig
+      num_workers: 8
+      agent_loop_config_path: null
+      custom_async_server:
+        _target_: verl.workers.config.CustomAsyncServerConfig
+        path: null
+        name: null
+    update_weights_bucket_megabytes: 512
+    trace:
+      _target_: verl.workers.config.TraceConfig
+      backend: null
+      token2text: false
+    skip_rollout: false
+    skip_dump_dir: /tmp/rollout_dump
+    skip_tokenizer_init: true
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+      all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+      ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+    layered_summon: false
+    rollout_filter_value: 0.9
+    rollout_filter_strategy: top_p
+    rollout_filter_type: largest
+    rollout_filter_include_zero: true
+    rollout_filter_top_p_prob_mode: linear
+    rollout_filter_selection_eps: 0.01
+    rollout_filter_empty_stop_steps: 5
+    rollout_filter_metric: reward_variance
+    gradient_analysis_num_buckets: 6
+    gradient_analysis_bucket_mode: quantile
+  model:
+    _target_: verl.workers.config.HFModelConfig
+    path: ${model_path}
+    hf_config_path: null
+    tokenizer_path: null
+    use_shm: false
+    trust_remote_code: false
+    custom_chat_template: null
+    external_lib: null
+    override_config: {}
+    enable_gradient_checkpointing: true
+    enable_activation_offload: false
+    use_remove_padding: false
+    lora_rank: ${lora.rank}
+    lora_alpha: ${lora.alpha}
+    target_modules: ${lora.target_modules}
+    exclude_modules: null
+    use_liger: false
+    use_fused_kernels: false
+    fused_kernel_options:
+      impl_backend: torch
+  hybrid_engine: true
+  nccl_timeout: 600
+data:
+  tokenizer: null
+  use_shm: false
+  train_files: ~/data/rlhf/gsm8k/train.parquet
+  val_files: ~/data/rlhf/gsm8k/test.parquet
+  prompt_key: prompt
+  reward_fn_key: data_source
+  max_prompt_length: null
+  max_response_length: null
+  train_batch_size: null
+  val_batch_size: null
+  return_raw_input_ids: false
+  return_raw_chat: false
+  return_full_prompt: false
+  shuffle: true
+  dataloader_num_workers: 8
+  validation_shuffle: false
+  filter_overlong_prompts: false
+  filter_overlong_prompts_workers: 1
+  truncation: error
+  image_key: images
+  video_key: videos
+  trust_remote_code: false
+  custom_cls:
+    path: null
+    name: null
+  return_multi_modal_inputs: true
+  sampler:
+    class_path: null
+    class_name: null
+  datagen:
+    path: null
+    name: null
+  apply_chat_template_kwargs: {}
+critic:
+  optim:
+    _target_: verl.workers.config.FSDPOptimizerConfig
+    lr: 1.0e-05
+    lr_warmup_steps_ratio: 0.0
+    total_training_steps: -1
+    weight_decay: 0.01
+    lr_warmup_steps: -1
+    betas:
+    - 0.9
+    - 0.999
+    clip_grad: 1.0
+    min_lr_ratio: 0.0
+    num_cycles: 0.5
+    warmup_style: constant
+  model:
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    path: ${model_path}
+    tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+    override_config: {}
+    external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+    trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+    _target_: verl.workers.config.FSDPCriticModelCfg
+    use_shm: false
+    enable_gradient_checkpointing: true
+    enable_activation_offload: false
+    use_remove_padding: false
+    lora_rank: ${lora.rank}
+    lora_alpha: ${lora.alpha}
+    target_modules: ${lora.target_modules}
+  _target_: verl.workers.config.FSDPCriticConfig
+  rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+  strategy: fsdp
+  enable: null
+  ppo_mini_batch_size: ${ppo_mini_batch_size}
+  ppo_micro_batch_size: null
+  ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+  use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+  ppo_max_token_len_per_gpu: 32768
+  forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+  ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+  shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+  cliprange_value: 0.5
+  loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+  checkpoint:
+    _target_: verl.trainer.config.CheckpointConfig
+    save_contents:
+    - model
+    - optimizer
+    - extra
+    load_contents: ${.save_contents}
+    async_save: false
+  profiler:
+    _target_: verl.utils.profiler.ProfilerConfig
+    tool: ${oc.select:global_profiler.tool,null}
+    enable: false
+    all_ranks: false
+    ranks: []
+    save_path: ${oc.select:global_profiler.save_path,null}
+    tool_config:
+      nsys:
+        _target_: verl.utils.profiler.config.NsightToolConfig
+        discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+      npu:
+        _target_: verl.utils.profiler.config.NPUToolConfig
+        contents: []
+        level: level1
+        analysis: true
+        discrete: false
+      torch:
+        _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+        step_start: 0
+        step_end: null
+      torch_memory:
+        _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+        trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+        stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+  forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+  forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+  ulysses_sequence_parallel_size: 1
+  grad_clip: 1.0
+reward_model:
+  enable: false
+  enable_resource_pool: false
+  n_gpus_per_node: 0
+  nnodes: 0
+  strategy: fsdp
+  model:
+    input_tokenizer: ${actor_rollout_ref.model.path}
+    path: ~/models/FsfairX-LLaMA3-RM-v0.1
+    external_lib: ${actor_rollout_ref.model.external_lib}
+    trust_remote_code: false
+    use_shm: false
+    use_remove_padding: false
+    use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+  micro_batch_size: null
+  micro_batch_size_per_gpu: null
+  max_length: null
+  use_dynamic_bsz: ${critic.use_dynamic_bsz}
+  forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+  reward_manager: naive
+  launch_reward_fn_async: false
+  sandbox_fusion:
+    url: null
+    max_concurrent: 64
+    memory_limit_mb: 1024
+  profiler:
+    _target_: verl.utils.profiler.ProfilerConfig
+    tool: ${oc.select:global_profiler.tool,null}
+    enable: false
+    all_ranks: false
+    ranks: []
+    save_path: ${oc.select:global_profiler.save_path,null}
+    tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+  ulysses_sequence_parallel_size: 1
+custom_reward_function:
+  path: null
+  name: compute_score
+algorithm:
+  _target_: verl.trainer.config.AlgoConfig
+  gamma: 1.0
+  lam: 1.0
+  adv_estimator: gae
+  norm_adv_by_std_in_grpo: true
+  use_kl_in_reward: false
+  kl_penalty: kl
+  kl_ctrl:
+    _target_: verl.trainer.config.KLControlConfig
+    type: fixed
+    kl_coef: 0.0
+    horizon: 10000
+    target_kl: 0.1
+  use_pf_ppo: false
+  pf_ppo:
+    reweight_method: pow
+    weight_pow: 2.0
+  high_level_gamma: 0.95
+  bi_level_gae: false
+  zero_task_advantage: false
+  soft_advantage_reweight: false
+trainer:
+  balance_batch: true
+  total_epochs: 30
+  total_training_steps: 200
+  project_name: ragen
+  experiment_name: rubikscube2_withthink_fulltrajc_sa
+  logger:
+  - console
+  - wandb
+  log_val_generations: 0
+  rollout_data_dir: null
+  validation_data_dir: null
+  nnodes: 1
+  n_gpus_per_node: 8
+  save_freq: -1
+  esi_redundant_time: 0
+  resume_mode: auto
+  resume_from_path: null
+  val_before_train: true
+  val_only: false
+  test_freq: 10
+  critic_warmup: 0
+  default_hdfs_dir: null
+  del_local_ckpt_after_load: false
+  default_local_dir: checkpoints/${trainer.project_name}/${trainer.experiment_name}
+  max_actor_ckpt_to_keep: 1
+  max_critic_ckpt_to_keep: 1
+  ray_wait_register_center_timeout: 300
+  device: cuda
+  use_legacy_worker_impl: auto
+  local_log_dir: results/
+  validation_steps: 1
+  generations_to_log_to_wandb:
+    val: 20
+  log_group_rv_table: false
+  gradient_analysis_mode: false
+  gradient_analysis_every: 50
+  gradient_analysis_env_groups: null
+  gradient_analysis_group_size: null
+  gradient_analysis_log_prefilter: false
+  gradient_analysis_only: false
+  exit_after_gradient_analysis: false
+global_profiler:
+  _target_: verl.utils.profiler.ProfilerConfig
+  tool: null
+  steps: null
+  profile_continuous_steps: false
+  save_path: outputs/profile
+  global_tool_config:
+    nsys:
+      _target_: verl.utils.profiler.config.NsightToolConfig
+      discrete: false
+      controller_nsight_options:
+        trace: cuda,nvtx,cublas,ucx
+        cuda-memory-usage: 'true'
+        cuda-graph-trace: graph
+      worker_nsight_options:
+        trace: cuda,nvtx,cublas,ucx
+        cuda-memory-usage: 'true'
+        cuda-graph-trace: graph
+        capture-range: cudaProfilerApi
+        capture-range-end: null
+        kill: none
+    torch_memory:
+      trace_alloc_max_entries: 100000
+      stack_depth: 32
+      context: all
+      stacks: all
+      kw_args: {}
+ray_kwargs:
+  ray_init:
+    num_cpus: null
+  timeline_json_file: null
+custom_envs:
+  SimpleSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 20
+    env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+      \ when reasoning:\n1. First compare the box position with the target position;\
+      \ the useful push directions are usually the directions that reduce their row/column\
+      \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+      \ push direction. A move that only repositions the player can be useful if it\
+      \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+      \ dead end unless that square is the target or clearly on the only path to the\
+      \ target.\n4. Prefer short plans that move the single box steadily toward the\
+      \ target; avoid wandering moves that do not improve player position or box position.\n\
+      5. If the box and target are aligned in the same row or column, try to keep\
+      \ the box on that line and push along it.\n6. If they are not aligned, first\
+      \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+      7. Check that after each push, the player can still reach the next required\
+      \ pushing side of the box.\n8. Output only the required XML-like format and\
+      \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+      \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+      \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+      \ pull a box. \nThe answer should be a sequence of actions, like <answer>Right\
+      \ || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 2
+      max_steps: 100
+  LargerSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+      \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+      \ you can push it by moving in the same direction. \nYou cannot push a box through\
+      \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+      \ like <answer>Right || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 8
+      dim_y: 8
+      num_boxes: 2
+      max_steps: 100
+      search_depth: 10
+  SokobanDifferentGridVocab:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+      \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+      \ you can push it by moving in the same direction. \nYou cannot push a box through\
+      \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+      \ like <answer>Right || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      search_depth: 30
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      grid_lookup:
+        0: W
+        1: .
+        2: G
+        3: C
+        4: B
+        5: A
+        6: '@'
+      grid_vocab:
+        W: wall
+        .: empty
+        G: target
+        C: box on target
+        B: box
+        A: player
+        '@': player on target
+  CoordSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 20
+    env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+      \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+      \ the zero-indexed coordinates of the player, each box, and each target. \n\
+      Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+      \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+      \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+      \ pull a box.\nThe answer should be a sequence of actions, like <answer>Right\
+      \ || Right || Up</answer>.\n"
+    max_tokens: 120
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      observation_format: grid_coord
+  VisualSimpleSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: You are solving the Sokoban puzzle. You are the player and you
+      need to push all boxes to targets. When you are right next to a box, you can
+      push it by moving in the same direction. You cannot push a box through a wall,
+      and you cannot pull a box. The answer should be a sequence of actions, like
+      <answer>Right || Right || Up</answer>
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      render_mode: rgb_array
+  Alfworld:
+    env_type: alfworld
+    max_actions_per_traj: 50
+    parallel_friendly: false
+    max_workers: 1
+    env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+      Complete household tasks by navigating and interacting with objects.
+
+
+      You should first reason step-by-step about the current situation. This reasoning
+      process MUST be enclosed within <think> </think> tags.
+
+      Once you''ve finished your reasoning, you should choose an admissible action
+      for current step and present it within <answer>...</answer> tags.
+
+      '
+    max_tokens: 512
+    env_config:
+      eval_dataset: eval_in_distribution
+  AlfworldOOD:
+    env_type: alfworld
+    max_actions_per_traj: 50
+    parallel_friendly: false
+    max_workers: 1
+    env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+      Complete household tasks by navigating and interacting with objects.
+
+
+      You should first reason step-by-step about the current situation. This reasoning
+      process MUST be enclosed within <think> </think> tags.
+
+      Once you''ve finished your reasoning, you should choose an admissible action
+      for current step and present it within <answer>...</answer> tags.
+
+      '
+    max_tokens: 512
+    env_config:
+      eval_dataset: eval_out_of_distribution
+  Countdown:
+    env_type: countdown
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving the Countdown puzzle. You should use the num
+      list to create an equation that equals the target. Example answer format: <think>
+      To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+      = 4. So the answer is 2 + 5 - 3 = 4. </think><answer>2 + 5 - 3</answer>'
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config: null
+  Bandit:
+    env_type: bandit
+    max_actions_per_traj: 1
+    env_instruction: ''
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      split: train
+  BanditTest:
+    env_type: bandit
+    max_actions_per_traj: 1
+    env_instruction: ''
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      split: test
+  DeepCoder:
+    env_type: deepcoder
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving a coding task. Provide a complete Python function
+      solution only. Format: <answer>...</answer>'
+    max_tokens: 8000
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 1
+  FrozenLake:
+    env_type: frozen_lake
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+      go to the target. You may move to the unintended direction due to the slippery
+      ice. Example answer format: <think>To forbid the hole and go to the target,
+      I should go left then go up.</think><answer>Left || Up</answer>'
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      success_rate: 0.8
+  CoordFrozenLake:
+    env_type: frozen_lake
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+      both a symbol grid and zero-indexed coordinates for the start, goal, player,
+      and any holes.
+
+      Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+      (5, 5).
+
+      Beware that the ice is slippery, so the agent might slide and end up in an unintended
+      tile.
+
+      Respond with a sequence of actions such as <answer>Left || Up || Up</answer>.
+
+      '
+    max_tokens: 120
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      observation_format: grid_coord
+      success_rate: 0.8
+  MetamathQA:
+    env_type: metamathqa
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving Math problems. '
+    max_tokens: 100
+    env_config: null
+  WebShopFull:
+    env_type: webshop
+    max_actions_per_traj: 15
+    env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+      environment.
+    max_tokens: 200
+    env_config:
+      dataset: full
+  WebShop:
+    env_type: webshop
+    max_actions_per_traj: 9
+    env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+      a product that close to the production description. You need to search, read
+      the search results, pick a product, choose the size and color and buy. You should
+      only choose action from the available actions list provided later.  Example
+      process: I need a gingko light and 20x20 pillow cover that is hand painted.
+      First search[gingko light 20x20 pillow cover hand painted], answer format: <answer>search[blanket
+      with fleece throw]</answer>. Valid answer is search[<keywords>] or click[<clickable>].'
+    max_tokens: 200
+    env_config:
+      dataset: small
+  Lean:
+    env_type: lean
+    max_actions_per_traj: 30
+    env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+      propose a sequence of tactics that completes the proof. Think step by step about
+      which tactics to apply next. Provide tactics separated by '||', for example
+      <answer>intro || simp || rfl</answer>.
+    max_tokens: 512
+    parallel_friendly: true
+    max_workers: 32
+    env_config: null
+  SimpleSudoku:
+    env_type: sudoku
+    max_actions_per_traj: 20
+    env_instruction: 'You are a careful 4x4 Sudoku solver. Use these reusable abstractions
+      when reasoning:
+
+      1. In <think>, explain the constraint logic behind the move, not just the final
+      placement. Mention which row, column, or 2x2 box makes the move safe or forced.
+
+      2. Treat each move as a constraint-preserving placement: place a number only
+      if it does not already appear in the same row, column, or 2x2 box.
+
+      3. First look for highly forced cells. If an empty cell has only one legal candidate
+      after checking its row, column, and box, fill it immediately and explain why
+      other numbers are excluded.
+
+      4. If no cell is obviously forced, scan each row, column, and 2x2 box for missing
+      numbers. If a missing number can go in only one empty position within that unit,
+      place it there and state that unit-level reason.
+
+      5. Prefer moves that reduce uncertainty and create new forced cells for the
+      next turn. A good move should make the remaining puzzle more constrained, not
+      more ambiguous.
+
+      6. Solve incrementally: choose exactly one placement, explain it briefly in
+      <think>, then output that one move in <answer>.
+
+      7. Never modify bracketed initial cells or already-filled cells. Only place
+      numbers into dots.
+
+      8. Avoid exploratory guesses when a forced move exists. In this environment,
+      reliable progress usually comes from constraint propagation rather than trial-and-error.
+
+      9. If a previous move was invalid or the board did not change, do not repeat
+      the same placement. Recompute legal candidates and explain the corrected constraint-consistent
+      choice.
+
+      10. Use row, column, and box agreement as confidence: the strongest placements
+      are those supported by multiple constraints at once.
+
+      11. Keep <think> concise but meaningful: identify the target cell, list or compare
+      its legal candidates, and give the decisive constraint.
+
+      12. Output only the required XML-like format and choose valid Sudoku placements.
+
+
+      You are solving a Sudoku puzzle. Fill in the grid so that every row, column,
+      and 2x2 box contains the numbers 1-4 without repetition.
+
+      Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+      shown as dots (.).
+
+      Place numbers one at a time using the format: <answer>place 1 at row 2 col 3</answer>
+
+      Always output: <think> [brief constraint-based reasoning] </think> <answer>
+      [one placement] </answer>
+
+      The environment will provide feedback on valid/invalid moves and show conflicts
+      if any occur.
+
+      '
+    max_tokens: 150
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      grid_size: 4
+      difficulty: easy
+      render_format: with_feedback
+      show_conflicts: false
+      show_valid_numbers: false
+      max_steps: 20
+  MediumSudoku:
+    env_type: sudoku
+    max_actions_per_traj: 30
+    env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+      row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+      Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+      shown as dots (.).
+
+      Place numbers one at a time using the format: <answer>place 5 at row 2 col 3</answer>
+      or <answer>2,3,5</answer>
+
+      The environment will provide feedback on valid/invalid moves and show conflicts
+      if any occur.
+
+      '
+    max_tokens: 150
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      grid_size: 9
+      difficulty: medium
+      render_format: with_feedback
+      show_conflicts: true
+      show_valid_numbers: true
+      max_steps: 81
+  SearchQA:
+    env_type: search
+    max_actions_per_traj: 10
+    env_instruction: "You are a search agent answering questions by searching for\
+      \ information.\nUse search[your query] to find relevant documents, and finish[your\
+      \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+      \ about the current situation. This reasoning process MUST be enclosed within\
+      \ <think> </think> tags.\nThen provide your action within <answer>...</answer>\
+      \ tags.\n\nExamples:\n  <think>I need to find information about Ben Platt's\
+      \ father.</think><answer>search[Ben Platt father parent]</answer>\n  <think>Based\
+      \ on the search results, Ben Platt's father is Henry Platt.</think><answer>finish[Henry\
+      \ Platt]</answer>\n"
+    max_tokens: 300
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 10
+      max_search_results: 5
+  SearchQAMock:
+    env_type: search
+    max_actions_per_traj: 10
+    env_instruction: "You are a search agent answering questions by searching for\
+      \ information.\nUse search[your query] to find relevant documents, and finish[your\
+      \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+      \ about the current situation. This reasoning process MUST be enclosed within\
+      \ <think> </think> tags.\nThen provide your action within <answer>...</answer>\
+      \ tags.\n\nExamples:\n  <think>I need to find information about Ben Platt's\
+      \ father.</think><answer>search[Ben Platt father parent]</answer>\n  <think>Based\
+      \ on the search results, Ben Platt's father is Henry Platt.</think><answer>finish[Henry\
+      \ Platt]</answer>\n"
+    max_tokens: 300
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 10
+      max_search_results: 5
+      mock_mode: true
+  game_2048:
+    env_type: game_2048
+    max_actions_per_traj: 700
+    env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+      by sliding Up, Right, Down, or Left.
+
+      If a move is invalid (no tiles move), a small penalty is applied. Respond with
+      a single action.
+
+      Example: <answer>Up</answer>
+
+      '
+    max_tokens: 8192
+    env_config: null
+  rubikscube:
+    env_type: rubikscube
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+      is to restore the cube so that each of the faces consists of a single, unique
+      color.
+
+      Available actions use standard Singmaster notation for face rotations: U, U'',
+      D, D'', L, L'', R, R'', F, F'', B, B''.
+
+      - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+      - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+      prime ('') means 90° counter-clockwise (e.g., "R''").
+
+      Respond with a sequence of actions separated by "||".
+
+      Example: <answer>U</answer>
+
+      '
+    max_tokens: 96
+    env_config:
+      scramble_depth: 2
+      max_steps: 7
+      render_mode: text
+system:
+  CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+  train: 10000
+  val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sas
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+  rank: 0
+  alpha: 64
+  target_modules: all-linear
+agent_proxy:
+  context_window_mode: full
+  max_context_window: 5
+  batch_adjust_mode: copy
+  max_turn: 10
+  action_sep: '||'
+  max_actions_per_turn: 4
+  use_turn_scores: false
+  enable_think: true
+  reward_normalization:
+    grouping: state
+    method: identity
+collapse_detection:
+  compute_freq: 5
+  micro_batch_size: 128
+  first_turn_enabled: true
+  multi_turn_enabled: true
+  num_samples: 64
+es_manager:
+  format_penalty: -0.1
+  train:
+    env_groups: 8
+    group_size: 16
+    env_configs:
+      tags:
+      - rubikscube
+      n_groups:
+      - 8
+  val:
+    env_groups: 512
+    group_size: 1
+    env_configs:
+      tags:
+      - rubikscube
+      n_groups:
+      - 512
+ctx_manager:
+  generation:
+    gen_config:
+      response_length: ${actor_rollout_ref.rollout.response_length}
+      temperature: ${actor_rollout_ref.rollout.temperature}
+      top_p: ${actor_rollout_ref.rollout.top_p}
+      top_k: ${actor_rollout_ref.rollout.top_k}
+      kwargs: null

outputs/2026-06-16/18-42-33/.hydra/hydra.yaml

@@ -0,0 +1,177 @@
+hydra:
+  run:
+    dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+  sweep:
+    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task:
+    - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+    - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+    - actor_rollout_ref.rollout.rollout_filter_value=0.9
+    - trainer.total_training_steps=200
+    - trainer.n_gpus_per_node=8
+    - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sas
+    - custom_envs.rubikscube.env_config.scramble_depth=2
+    - trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa
+  job:
+    name: train
+    chdir: null
+    override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=2,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sas,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa,trainer.n_gpus_per_node=8,trainer.total_training_steps=200
+    id: ???
+    num: ???
+    config_name: _10_rubikscube
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /mnt/general/wanghy/RAGEN_v2
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /mnt/general/wanghy/RAGEN_v2/config
+      schema: file
+      provider: main
+    - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-16/18-42-33
+    choices:
+      reward_model: dp_reward_model
+      critic: dp_critic
+      critic/../engine@critic.model.fsdp_config: fsdp
+      critic/../optim@critic.optim: fsdp
+      model@actor_rollout_ref.model: hf_model
+      rollout@actor_rollout_ref.rollout: rollout
+      ref@actor_rollout_ref.ref: dp_ref
+      ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+      data: legacy_data
+      actor@actor_rollout_ref.actor: dp_actor
+      actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+      actor/../optim@actor_rollout_ref.actor.optim: fsdp
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

outputs/2026-06-16/18-42-33/.hydra/overrides.yaml

@@ -0,0 +1,8 @@
+- system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- trainer.n_gpus_per_node=8
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube2_withthink_fulltraj_sas
+- custom_envs.rubikscube.env_config.scramble_depth=2
+- trainer.experiment_name=rubikscube2_withthink_fulltrajc_sa

outputs/2026-06-18/11-52-39/.hydra/config.yaml

@@ -0,0 +1,1048 @@
+actor_rollout_ref:
+  actor:
+    optim:
+      _target_: verl.workers.config.FSDPOptimizerConfig
+      lr: 1.0e-06
+      lr_warmup_steps_ratio: 0.0
+      total_training_steps: -1
+      weight_decay: 0.01
+      lr_warmup_steps: -1
+      betas:
+      - 0.9
+      - 0.999
+      clip_grad: 1.0
+      min_lr_ratio: 0.0
+      num_cycles: 0.5
+      warmup_style: constant
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    _target_: verl.workers.config.FSDPActorConfig
+    strategy: fsdp
+    ppo_mini_batch_size: ${ppo_mini_batch_size}
+    ppo_micro_batch_size: null
+    ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+    use_dynamic_bsz: false
+    ppo_max_token_len_per_gpu: 16384
+    clip_ratio: 0.2
+    clip_ratio_low: 0.2
+    clip_ratio_high: 0.28
+    freeze_vision_tower: false
+    policy_loss:
+      _target_: verl.workers.config.PolicyLossConfig
+      loss_mode: vanilla
+      clip_cov_ratio: 0.0002
+      clip_cov_lb: 1.0
+      clip_cov_ub: 5.0
+      kl_cov_ratio: 0.0002
+      ppo_kl_coef: 0.1
+    clip_ratio_c: 3.0
+    loss_agg_mode: token-mean
+    entropy_coeff: 0.001
+    tis_imp_ratio_cap: -1
+    use_kl_loss: false
+    use_torch_compile: true
+    kl_loss_coef: 0.0
+    kl_loss_type: kl
+    ppo_epochs: 1
+    shuffle: false
+    checkpoint:
+      _target_: verl.trainer.config.CheckpointConfig
+      save_contents:
+      - model
+      - optimizer
+      - extra
+      load_contents: ${.save_contents}
+      async_save: false
+    use_fused_kernels: ${oc.select:actor_rollout_ref.model.use_fused_kernels,false}
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: false
+      all_ranks: false
+      ranks: []
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config:
+        nsys:
+          _target_: verl.utils.profiler.config.NsightToolConfig
+          discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+        npu:
+          _target_: verl.utils.profiler.config.NPUToolConfig
+          contents: []
+          level: level1
+          analysis: true
+          discrete: false
+        torch:
+          _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+          step_start: 0
+          step_end: null
+        torch_memory:
+          _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+          trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+          stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+    grad_clip: 1.0
+    ulysses_sequence_parallel_size: 1
+    entropy_from_logits_with_chunking: false
+    entropy_checkpointing: false
+    use_remove_padding: ${oc.select:actor_rollout_ref.model.use_remove_padding,false}
+    use_ref: true
+    grpo_advantage_length_weight: ${grpo_advantage_length_weight}
+    filter_loss_scaling: none
+  ref:
+    strategy: ${actor_rollout_ref.actor.strategy}
+    use_torch_compile: ${oc.select:actor_rollout_ref.actor.use_torch_compile,true}
+    log_prob_micro_batch_size: null
+    log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+    log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+    log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: false
+      all_ranks: false
+      ranks: []
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config:
+        nsys:
+          _target_: verl.utils.profiler.config.NsightToolConfig
+          discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+        npu:
+          _target_: verl.utils.profiler.config.NPUToolConfig
+          contents: []
+          level: level1
+          analysis: true
+          discrete: false
+        torch:
+          _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+          step_start: 0
+          step_end: null
+        torch_memory:
+          _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+          trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+          stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    model: null
+    ulysses_sequence_parallel_size: ${oc.select:actor_rollout_ref.actor.ulysses_sequence_parallel_size,1}
+    entropy_from_logits_with_chunking: false
+    entropy_checkpointing: false
+  rollout:
+    _target_: verl.workers.config.RolloutConfig
+    name: vllm
+    mode: sync
+    temperature: 1
+    top_k: -1
+    top_p: 1
+    prompt_length: 1
+    response_length: 500
+    dtype: bfloat16
+    gpu_memory_utilization: 0.7
+    ignore_eos: false
+    enforce_eager: true
+    cudagraph_capture_sizes: null
+    free_cache_engine: true
+    tensor_model_parallel_size: 1
+    data_parallel_size: 1
+    expert_parallel_size: 1
+    max_num_batched_tokens: 16384
+    max_model_len: 16384
+    max_num_seqs: 1024
+    enable_chunked_prefill: true
+    enable_prefix_caching: true
+    load_format: auto
+    log_prob_micro_batch_size: null
+    log_prob_micro_batch_size_per_gpu: ${log_prob_micro_batch_size_per_gpu}
+    log_prob_use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+    log_prob_max_token_len_per_gpu: ${oc.select:actor_rollout_ref.actor.ppo_max_token_len_per_gpu,16384}
+    disable_log_stats: true
+    do_sample: true
+    'n': 1
+    over_sample_rate: 0
+    multi_stage_wake_up: false
+    engine_kwargs:
+      vllm: {}
+      sglang: {}
+    val_kwargs:
+      _target_: verl.workers.config.SamplingConfig
+      top_k: -1
+      top_p: 1.0
+      temperature: 0.5
+      'n': 1
+      do_sample: true
+    multi_turn:
+      _target_: verl.workers.config.MultiTurnConfig
+      enable: false
+      max_assistant_turns: null
+      tool_config_path: null
+      max_user_turns: null
+      max_parallel_calls: 1
+      max_tool_response_length: 256
+      tool_response_truncate_side: middle
+      interaction_config_path: null
+      use_inference_chat_template: false
+      tokenization_sanity_check_mode: strict
+      format: hermes
+      num_repeat_rollouts: null
+    calculate_log_probs: false
+    agent:
+      _target_: verl.workers.config.AgentLoopConfig
+      num_workers: 8
+      agent_loop_config_path: null
+      custom_async_server:
+        _target_: verl.workers.config.CustomAsyncServerConfig
+        path: null
+        name: null
+    update_weights_bucket_megabytes: 512
+    trace:
+      _target_: verl.workers.config.TraceConfig
+      backend: null
+      token2text: false
+    skip_rollout: false
+    skip_dump_dir: /tmp/rollout_dump
+    skip_tokenizer_init: true
+    profiler:
+      _target_: verl.utils.profiler.ProfilerConfig
+      tool: ${oc.select:global_profiler.tool,null}
+      enable: ${oc.select:actor_rollout_ref.actor.profiler.enable,false}
+      all_ranks: ${oc.select:actor_rollout_ref.actor.profiler.all_ranks,false}
+      ranks: ${oc.select:actor_rollout_ref.actor.profiler.ranks,[]}
+      save_path: ${oc.select:global_profiler.save_path,null}
+      tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+    layered_summon: false
+    rollout_filter_value: 0.9
+    rollout_filter_strategy: top_p
+    rollout_filter_type: largest
+    rollout_filter_include_zero: true
+    rollout_filter_top_p_prob_mode: linear
+    rollout_filter_selection_eps: 0.01
+    rollout_filter_empty_stop_steps: 5
+    rollout_filter_metric: reward_variance
+    gradient_analysis_num_buckets: 6
+    gradient_analysis_bucket_mode: quantile
+  model:
+    _target_: verl.workers.config.HFModelConfig
+    path: ${model_path}
+    hf_config_path: null
+    tokenizer_path: null
+    use_shm: false
+    trust_remote_code: false
+    custom_chat_template: null
+    external_lib: null
+    override_config: {}
+    enable_gradient_checkpointing: true
+    enable_activation_offload: false
+    use_remove_padding: false
+    lora_rank: ${lora.rank}
+    lora_alpha: ${lora.alpha}
+    target_modules: ${lora.target_modules}
+    exclude_modules: null
+    use_liger: false
+    use_fused_kernels: false
+    fused_kernel_options:
+      impl_backend: torch
+  hybrid_engine: true
+  nccl_timeout: 600
+data:
+  tokenizer: null
+  use_shm: false
+  train_files: ~/data/rlhf/gsm8k/train.parquet
+  val_files: ~/data/rlhf/gsm8k/test.parquet
+  prompt_key: prompt
+  reward_fn_key: data_source
+  max_prompt_length: null
+  max_response_length: null
+  train_batch_size: null
+  val_batch_size: null
+  return_raw_input_ids: false
+  return_raw_chat: false
+  return_full_prompt: false
+  shuffle: true
+  dataloader_num_workers: 8
+  validation_shuffle: false
+  filter_overlong_prompts: false
+  filter_overlong_prompts_workers: 1
+  truncation: error
+  image_key: images
+  video_key: videos
+  trust_remote_code: false
+  custom_cls:
+    path: null
+    name: null
+  return_multi_modal_inputs: true
+  sampler:
+    class_path: null
+    class_name: null
+  datagen:
+    path: null
+    name: null
+  apply_chat_template_kwargs: {}
+critic:
+  optim:
+    _target_: verl.workers.config.FSDPOptimizerConfig
+    lr: 1.0e-05
+    lr_warmup_steps_ratio: 0.0
+    total_training_steps: -1
+    weight_decay: 0.01
+    lr_warmup_steps: -1
+    betas:
+    - 0.9
+    - 0.999
+    clip_grad: 1.0
+    min_lr_ratio: 0.0
+    num_cycles: 0.5
+    warmup_style: constant
+  model:
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      optimizer_offload: false
+      offload_policy: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+      model_dtype: fp32
+      use_orig_params: false
+      ulysses_sequence_parallel_size: 1
+      entropy_from_logits_with_chunking: false
+      use_torch_compile: true
+      entropy_checkpointing: false
+      forward_only: false
+      strategy: fsdp
+    path: ${model_path}
+    tokenizer_path: ${oc.select:actor_rollout_ref.model.path,"~/models/deepseek-llm-7b-chat"}
+    override_config: {}
+    external_lib: ${oc.select:actor_rollout_ref.model.external_lib,null}
+    trust_remote_code: ${oc.select:actor_rollout_ref.model.trust_remote_code,false}
+    _target_: verl.workers.config.FSDPCriticModelCfg
+    use_shm: false
+    enable_gradient_checkpointing: true
+    enable_activation_offload: false
+    use_remove_padding: false
+    lora_rank: ${lora.rank}
+    lora_alpha: ${lora.alpha}
+    target_modules: ${lora.target_modules}
+  _target_: verl.workers.config.FSDPCriticConfig
+  rollout_n: ${oc.select:actor_rollout_ref.rollout.n,1}
+  strategy: fsdp
+  enable: null
+  ppo_mini_batch_size: ${ppo_mini_batch_size}
+  ppo_micro_batch_size: null
+  ppo_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+  use_dynamic_bsz: ${oc.select:actor_rollout_ref.actor.use_dynamic_bsz,false}
+  ppo_max_token_len_per_gpu: 32768
+  forward_max_token_len_per_gpu: ${.ppo_max_token_len_per_gpu}
+  ppo_epochs: ${oc.select:actor_rollout_ref.actor.ppo_epochs,1}
+  shuffle: ${oc.select:actor_rollout_ref.actor.shuffle,false}
+  cliprange_value: 0.5
+  loss_agg_mode: ${oc.select:actor_rollout_ref.actor.loss_agg_mode,token-mean}
+  checkpoint:
+    _target_: verl.trainer.config.CheckpointConfig
+    save_contents:
+    - model
+    - optimizer
+    - extra
+    load_contents: ${.save_contents}
+    async_save: false
+  profiler:
+    _target_: verl.utils.profiler.ProfilerConfig
+    tool: ${oc.select:global_profiler.tool,null}
+    enable: false
+    all_ranks: false
+    ranks: []
+    save_path: ${oc.select:global_profiler.save_path,null}
+    tool_config:
+      nsys:
+        _target_: verl.utils.profiler.config.NsightToolConfig
+        discrete: ${oc.select:global_profiler.global_tool_config.nsys.discrete}
+      npu:
+        _target_: verl.utils.profiler.config.NPUToolConfig
+        contents: []
+        level: level1
+        analysis: true
+        discrete: false
+      torch:
+        _target_: verl.utils.profiler.config.TorchProfilerToolConfig
+        step_start: 0
+        step_end: null
+      torch_memory:
+        _target_: verl.utils.profiler.config.TorchMemoryToolConfig
+        trace_alloc_max_entries: ${oc.select:global_profiler.global_tool_config.torch_memory.trace_alloc_max_entries,100000}
+        stack_depth: ${oc.select:global_profiler.global_tool_config.torch_memory.stack_depth,32}
+  forward_micro_batch_size: ${oc.select:.ppo_micro_batch_size,null}
+  forward_micro_batch_size_per_gpu: ${oc.select:.ppo_micro_batch_size_per_gpu,null}
+  ulysses_sequence_parallel_size: 1
+  grad_clip: 1.0
+reward_model:
+  enable: false
+  enable_resource_pool: false
+  n_gpus_per_node: 0
+  nnodes: 0
+  strategy: fsdp
+  model:
+    input_tokenizer: ${actor_rollout_ref.model.path}
+    path: ~/models/FsfairX-LLaMA3-RM-v0.1
+    external_lib: ${actor_rollout_ref.model.external_lib}
+    trust_remote_code: false
+    use_shm: false
+    use_remove_padding: false
+    use_fused_kernels: ${actor_rollout_ref.model.use_fused_kernels}
+    fsdp_config:
+      _target_: verl.workers.config.FSDPEngineConfig
+      wrap_policy:
+        min_num_params: 0
+      param_offload: false
+      reshard_after_forward: true
+      fsdp_size: -1
+      forward_prefetch: false
+  micro_batch_size: null
+  micro_batch_size_per_gpu: null
+  max_length: null
+  use_dynamic_bsz: ${critic.use_dynamic_bsz}
+  forward_max_token_len_per_gpu: ${critic.forward_max_token_len_per_gpu}
+  reward_manager: naive
+  launch_reward_fn_async: false
+  sandbox_fusion:
+    url: null
+    max_concurrent: 64
+    memory_limit_mb: 1024
+  profiler:
+    _target_: verl.utils.profiler.ProfilerConfig
+    tool: ${oc.select:global_profiler.tool,null}
+    enable: false
+    all_ranks: false
+    ranks: []
+    save_path: ${oc.select:global_profiler.save_path,null}
+    tool_config: ${oc.select:actor_rollout_ref.actor.profiler.tool_config,null}
+  ulysses_sequence_parallel_size: 1
+custom_reward_function:
+  path: null
+  name: compute_score
+algorithm:
+  _target_: verl.trainer.config.AlgoConfig
+  gamma: 1.0
+  lam: 1.0
+  adv_estimator: gae
+  norm_adv_by_std_in_grpo: true
+  use_kl_in_reward: false
+  kl_penalty: kl
+  kl_ctrl:
+    _target_: verl.trainer.config.KLControlConfig
+    type: fixed
+    kl_coef: 0.0
+    horizon: 10000
+    target_kl: 0.1
+  use_pf_ppo: false
+  pf_ppo:
+    reweight_method: pow
+    weight_pow: 2.0
+  high_level_gamma: 0.95
+  bi_level_gae: false
+  zero_task_advantage: false
+  soft_advantage_reweight: false
+trainer:
+  balance_batch: true
+  total_epochs: 30
+  total_training_steps: 200
+  project_name: ragen
+  experiment_name: rubikscube1_withthink_fulltrajc_sa
+  logger:
+  - console
+  - wandb
+  log_val_generations: 0
+  rollout_data_dir: null
+  validation_data_dir: null
+  nnodes: 1
+  n_gpus_per_node: 8
+  save_freq: 200
+  esi_redundant_time: 0
+  resume_mode: auto
+  resume_from_path: null
+  val_before_train: true
+  val_only: false
+  test_freq: 10
+  critic_warmup: 0
+  default_hdfs_dir: null
+  del_local_ckpt_after_load: false
+  default_local_dir: /mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa_rl
+  max_actor_ckpt_to_keep: 1
+  max_critic_ckpt_to_keep: 1
+  ray_wait_register_center_timeout: 300
+  device: cuda
+  use_legacy_worker_impl: auto
+  local_log_dir: results/
+  validation_steps: 1
+  generations_to_log_to_wandb:
+    val: 20
+  log_group_rv_table: false
+  gradient_analysis_mode: false
+  gradient_analysis_every: 50
+  gradient_analysis_env_groups: null
+  gradient_analysis_group_size: null
+  gradient_analysis_log_prefilter: false
+  gradient_analysis_only: false
+  exit_after_gradient_analysis: false
+global_profiler:
+  _target_: verl.utils.profiler.ProfilerConfig
+  tool: null
+  steps: null
+  profile_continuous_steps: false
+  save_path: outputs/profile
+  global_tool_config:
+    nsys:
+      _target_: verl.utils.profiler.config.NsightToolConfig
+      discrete: false
+      controller_nsight_options:
+        trace: cuda,nvtx,cublas,ucx
+        cuda-memory-usage: 'true'
+        cuda-graph-trace: graph
+      worker_nsight_options:
+        trace: cuda,nvtx,cublas,ucx
+        cuda-memory-usage: 'true'
+        cuda-graph-trace: graph
+        capture-range: cudaProfilerApi
+        capture-range-end: null
+        kill: none
+    torch_memory:
+      trace_alloc_max_entries: 100000
+      stack_depth: 32
+      context: all
+      stacks: all
+      kw_args: {}
+ray_kwargs:
+  ray_init:
+    num_cpus: null
+  timeline_json_file: null
+custom_envs:
+  SimpleSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 20
+    env_instruction: "You are a careful Sokoban solver. Use these reusable abstractions\
+      \ when reasoning:\n1. First compare the box position with the target position;\
+      \ the useful push directions are usually the directions that reduce their row/column\
+      \ distance.\n2. Before pushing, move the player to the square opposite the intended\
+      \ push direction. A move that only repositions the player can be useful if it\
+      \ sets up the next push.\n3. Never push a box into a wall, corner, or narrow\
+      \ dead end unless that square is the target or clearly on the only path to the\
+      \ target.\n4. Prefer short plans that move the single box steadily toward the\
+      \ target; avoid wandering moves that do not improve player position or box position.\n\
+      5. If the box and target are aligned in the same row or column, try to keep\
+      \ the box on that line and push along it.\n6. If they are not aligned, first\
+      \ push to fix one coordinate, then reposition and push to fix the other coordinate.\n\
+      7. Check that after each push, the player can still reach the next required\
+      \ pushing side of the box.\n8. Output only the required XML-like format and\
+      \ choose valid Sokoban actions.\n\nYou are the player and you need to push all\
+      \ boxes to targets. \nWhen you are right next to a box, you can push it by moving\
+      \ in the same direction. \nYou cannot push a box through a wall, and you cannot\
+      \ pull a box. \nThe answer should be a sequence of actions, like <answer>Right\
+      \ || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 2
+      max_steps: 100
+  LargerSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+      \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+      \ you can push it by moving in the same direction. \nYou cannot push a box through\
+      \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+      \ like <answer>Right || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 8
+      dim_y: 8
+      num_boxes: 2
+      max_steps: 100
+      search_depth: 10
+  SokobanDifferentGridVocab:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: "You are solving the Sokoban puzzle. \nYou are the player and\
+      \ you need to push all boxes to targets. \nWhen you are right next to a box,\
+      \ you can push it by moving in the same direction. \nYou cannot push a box through\
+      \ a wall, and you cannot pull a box. \nThe answer should be a sequence of actions,\
+      \ like <answer>Right || Right || Up</answer>\n"
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      search_depth: 30
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      grid_lookup:
+        0: W
+        1: .
+        2: G
+        3: C
+        4: B
+        5: A
+        6: '@'
+      grid_vocab:
+        W: wall
+        .: empty
+        G: target
+        C: box on target
+        B: box
+        A: player
+        '@': player on target
+  CoordSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 20
+    env_instruction: "You are solving the Sokoban puzzle. You are the player and you\
+      \ need to push all boxes to targets.\nYou are provided with a symbol grid and\
+      \ the zero-indexed coordinates of the player, each box, and each target. \n\
+      Coordinates range from the top-left corner (0, 0) to the bottom-right corner\
+      \ (5, 5). \nWhen you are exactly next to a box, you can push it by moving in\
+      \ the same direction. \nYou cannot push a box through a wall, and you cannot\
+      \ pull a box.\nThe answer should be a sequence of actions, like <answer>Right\
+      \ || Right || Up</answer>.\n"
+    max_tokens: 120
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      observation_format: grid_coord
+  VisualSimpleSokoban:
+    env_type: sokoban
+    max_actions_per_traj: 10
+    env_instruction: You are solving the Sokoban puzzle. You are the player and you
+      need to push all boxes to targets. When you are right next to a box, you can
+      push it by moving in the same direction. You cannot push a box through a wall,
+      and you cannot pull a box. The answer should be a sequence of actions, like
+      <answer>Right || Right || Up</answer>
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      dim_x: 6
+      dim_y: 6
+      num_boxes: 1
+      max_steps: 100
+      render_mode: rgb_array
+  Alfworld:
+    env_type: alfworld
+    max_actions_per_traj: 50
+    parallel_friendly: false
+    max_workers: 1
+    env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+      Complete household tasks by navigating and interacting with objects.
+
+
+      You should first reason step-by-step about the current situation. This reasoning
+      process MUST be enclosed within <think> </think> tags.
+
+      Once you''ve finished your reasoning, you should choose an admissible action
+      for current step and present it within <answer>...</answer> tags.
+
+      '
+    max_tokens: 512
+    env_config:
+      eval_dataset: eval_in_distribution
+  AlfworldOOD:
+    env_type: alfworld
+    max_actions_per_traj: 50
+    parallel_friendly: false
+    max_workers: 1
+    env_instruction: 'You are an expert agent in the ALFRED Embodied Environment.
+
+      Complete household tasks by navigating and interacting with objects.
+
+
+      You should first reason step-by-step about the current situation. This reasoning
+      process MUST be enclosed within <think> </think> tags.
+
+      Once you''ve finished your reasoning, you should choose an admissible action
+      for current step and present it within <answer>...</answer> tags.
+
+      '
+    max_tokens: 512
+    env_config:
+      eval_dataset: eval_out_of_distribution
+  Countdown:
+    env_type: countdown
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving the Countdown puzzle. You should use the num
+      list to create an equation that equals the target. Example answer format: <think>
+      To find an equation using [3, 5, 2] to get 4. Let''s check 2 + 5 = 7, 7 - 3
+      = 4. So the answer is 2 + 5 - 3 = 4. </think><answer>2 + 5 - 3</answer>'
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config: null
+  Bandit:
+    env_type: bandit
+    max_actions_per_traj: 1
+    env_instruction: ''
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      split: train
+  BanditTest:
+    env_type: bandit
+    max_actions_per_traj: 1
+    env_instruction: ''
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      split: test
+  DeepCoder:
+    env_type: deepcoder
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving a coding task. Provide a complete Python function
+      solution only. Format: <answer>...</answer>'
+    max_tokens: 8000
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 1
+  FrozenLake:
+    env_type: frozen_lake
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving the FrozenLake puzzle. Forbid the whole and
+      go to the target. You may move to the unintended direction due to the slippery
+      ice. Example answer format: <think>To forbid the hole and go to the target,
+      I should go left then go up.</think><answer>Left || Up</answer>'
+    max_tokens: 100
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      success_rate: 0.8
+  CoordFrozenLake:
+    env_type: frozen_lake
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving the FrozenLake puzzle. The observation includes
+      both a symbol grid and zero-indexed coordinates for the start, goal, player,
+      and any holes.
+
+      Coordinates range from the top-left corner (0, 0) to the bottom-right corner
+      (5, 5).
+
+      Beware that the ice is slippery, so the agent might slide and end up in an unintended
+      tile.
+
+      Respond with a sequence of actions such as <answer>Left || Up || Up</answer>.
+
+      '
+    max_tokens: 120
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      observation_format: grid_coord
+      success_rate: 0.8
+  MetamathQA:
+    env_type: metamathqa
+    max_actions_per_traj: 1
+    env_instruction: 'You are solving Math problems. '
+    max_tokens: 100
+    env_config: null
+  WebShopFull:
+    env_type: webshop
+    max_actions_per_traj: 15
+    env_instruction: You are an expert autonomous agent operating in the WebShop e‑commerce
+      environment.
+    max_tokens: 200
+    env_config:
+      dataset: full
+  WebShop:
+    env_type: webshop
+    max_actions_per_traj: 9
+    env_instruction: 'You are browsing an online shop. Based on the instruction, buy
+      a product that close to the production description. You need to search, read
+      the search results, pick a product, choose the size and color and buy. You should
+      only choose action from the available actions list provided later.  Example
+      process: I need a gingko light and 20x20 pillow cover that is hand painted.
+      First search[gingko light 20x20 pillow cover hand painted], answer format: <answer>search[blanket
+      with fleece throw]</answer>. Valid answer is search[<keywords>] or click[<clickable>].'
+    max_tokens: 200
+    env_config:
+      dataset: small
+  Lean:
+    env_type: lean
+    max_actions_per_traj: 30
+    env_instruction: You are a Lean theorem prover. Given a Lean theorem statement,
+      propose a sequence of tactics that completes the proof. Think step by step about
+      which tactics to apply next. Provide tactics separated by '||', for example
+      <answer>intro || simp || rfl</answer>.
+    max_tokens: 512
+    parallel_friendly: true
+    max_workers: 32
+    env_config: null
+  SimpleSudoku:
+    env_type: sudoku
+    max_actions_per_traj: 20
+    env_instruction: 'You are a careful 4x4 Sudoku solver. Use these reusable abstractions
+      when reasoning:
+
+      1. In <think>, explain the constraint logic behind the move, not just the final
+      placement. Mention which row, column, or 2x2 box makes the move safe or forced.
+
+      2. Treat each move as a constraint-preserving placement: place a number only
+      if it does not already appear in the same row, column, or 2x2 box.
+
+      3. First look for highly forced cells. If an empty cell has only one legal candidate
+      after checking its row, column, and box, fill it immediately and explain why
+      other numbers are excluded.
+
+      4. If no cell is obviously forced, scan each row, column, and 2x2 box for missing
+      numbers. If a missing number can go in only one empty position within that unit,
+      place it there and state that unit-level reason.
+
+      5. Prefer moves that reduce uncertainty and create new forced cells for the
+      next turn. A good move should make the remaining puzzle more constrained, not
+      more ambiguous.
+
+      6. Solve incrementally: choose exactly one placement, explain it briefly in
+      <think>, then output that one move in <answer>.
+
+      7. Never modify bracketed initial cells or already-filled cells. Only place
+      numbers into dots.
+
+      8. Avoid exploratory guesses when a forced move exists. In this environment,
+      reliable progress usually comes from constraint propagation rather than trial-and-error.
+
+      9. If a previous move was invalid or the board did not change, do not repeat
+      the same placement. Recompute legal candidates and explain the corrected constraint-consistent
+      choice.
+
+      10. Use row, column, and box agreement as confidence: the strongest placements
+      are those supported by multiple constraints at once.
+
+      11. Keep <think> concise but meaningful: identify the target cell, list or compare
+      its legal candidates, and give the decisive constraint.
+
+      12. Output only the required XML-like format and choose valid Sudoku placements.
+
+
+      You are solving a Sudoku puzzle. Fill in the grid so that every row, column,
+      and 2x2 box contains the numbers 1-4 without repetition.
+
+      Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+      shown as dots (.).
+
+      Place numbers one at a time using the format: <answer>place 1 at row 2 col 3</answer>
+
+      Always output: <think> [brief constraint-based reasoning] </think> <answer>
+      [one placement] </answer>
+
+      The environment will provide feedback on valid/invalid moves and show conflicts
+      if any occur.
+
+      '
+    max_tokens: 150
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      grid_size: 4
+      difficulty: easy
+      render_format: with_feedback
+      show_conflicts: false
+      show_valid_numbers: false
+      max_steps: 20
+  MediumSudoku:
+    env_type: sudoku
+    max_actions_per_traj: 30
+    env_instruction: 'You are solving a Sudoku puzzle. Fill in the grid so that every
+      row, column, and 3x3 box contains the numbers 1-9 without repetition.
+
+      Initial cells are shown in [brackets] and cannot be modified. Empty cells are
+      shown as dots (.).
+
+      Place numbers one at a time using the format: <answer>place 5 at row 2 col 3</answer>
+      or <answer>2,3,5</answer>
+
+      The environment will provide feedback on valid/invalid moves and show conflicts
+      if any occur.
+
+      '
+    max_tokens: 150
+    parallel_friendly: false
+    max_workers: 32
+    env_config:
+      grid_size: 9
+      difficulty: medium
+      render_format: with_feedback
+      show_conflicts: true
+      show_valid_numbers: true
+      max_steps: 81
+  SearchQA:
+    env_type: search
+    max_actions_per_traj: 10
+    env_instruction: "You are a search agent answering questions by searching for\
+      \ information.\nUse search[your query] to find relevant documents, and finish[your\
+      \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+      \ about the current situation. This reasoning process MUST be enclosed within\
+      \ <think> </think> tags.\nThen provide your action within <answer>...</answer>\
+      \ tags.\n\nExamples:\n  <think>I need to find information about Ben Platt's\
+      \ father.</think><answer>search[Ben Platt father parent]</answer>\n  <think>Based\
+      \ on the search results, Ben Platt's father is Henry Platt.</think><answer>finish[Henry\
+      \ Platt]</answer>\n"
+    max_tokens: 300
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 10
+      max_search_results: 5
+  SearchQAMock:
+    env_type: search
+    max_actions_per_traj: 10
+    env_instruction: "You are a search agent answering questions by searching for\
+      \ information.\nUse search[your query] to find relevant documents, and finish[your\
+      \ answer] to submit your final answer.\n\nYou should first reason step-by-step\
+      \ about the current situation. This reasoning process MUST be enclosed within\
+      \ <think> </think> tags.\nThen provide your action within <answer>...</answer>\
+      \ tags.\n\nExamples:\n  <think>I need to find information about Ben Platt's\
+      \ father.</think><answer>search[Ben Platt father parent]</answer>\n  <think>Based\
+      \ on the search results, Ben Platt's father is Henry Platt.</think><answer>finish[Henry\
+      \ Platt]</answer>\n"
+    max_tokens: 300
+    parallel_friendly: true
+    max_workers: 32
+    env_config:
+      max_steps: 10
+      max_search_results: 5
+      mock_mode: true
+  game_2048:
+    env_type: game_2048
+    max_actions_per_traj: 700
+    env_instruction: 'You are playing the 2048 game on a 4x4 grid. Merge equal tiles
+      by sliding Up, Right, Down, or Left.
+
+      If a move is invalid (no tiles move), a small penalty is applied. Respond with
+      a single action.
+
+      Example: <answer>Up</answer>
+
+      '
+    max_tokens: 8192
+    env_config: null
+  rubikscube:
+    env_type: rubikscube
+    max_actions_per_traj: 10
+    env_instruction: 'You are solving a 2x2 Rubik''s Cube (Pocket Cube). The goal
+      is to restore the cube so that each of the faces consists of a single, unique
+      color.
+
+      Available actions use standard Singmaster notation for face rotations: U, U'',
+      D, D'', L, L'', R, R'', F, F'', B, B''.
+
+      - Faces: U (Up), D (Down), L (Left), R (Right), F (Front), B (Back).
+
+      - Modifiers: A letter alone means 90° clockwise (e.g., ''R''). A letter with
+      prime ('') means 90° counter-clockwise (e.g., "R''").
+
+      Respond with a sequence of actions separated by "||".
+
+      Example: <answer>U</answer>
+
+      '
+    max_tokens: 96
+    env_config:
+      scramble_depth: 1
+      max_steps: 7
+      render_mode: text
+system:
+  CUDA_VISIBLE_DEVICES: 0,1,2,3,4,5,6,7
+seed:
+  train: 10000
+  val: 123
+micro_batch_size_per_gpu: 1
+log_prob_micro_batch_size_per_gpu: ${micro_batch_size_per_gpu}
+ppo_mini_batch_size: 32
+model_path: /mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa
+enable_response_mask: true
+grpo_advantage_length_weight: false
+lora:
+  rank: 0
+  alpha: 64
+  target_modules: all-linear
+agent_proxy:
+  context_window_mode: full
+  max_context_window: 5
+  batch_adjust_mode: copy
+  max_turn: 10
+  action_sep: '||'
+  max_actions_per_turn: 4
+  use_turn_scores: false
+  enable_think: true
+  reward_normalization:
+    grouping: state
+    method: identity
+collapse_detection:
+  compute_freq: 5
+  micro_batch_size: 128
+  first_turn_enabled: true
+  multi_turn_enabled: true
+  num_samples: 64
+es_manager:
+  format_penalty: -0.1
+  train:
+    env_groups: 8
+    group_size: 16
+    env_configs:
+      tags:
+      - rubikscube
+      n_groups:
+      - 8
+  val:
+    env_groups: 512
+    group_size: 1
+    env_configs:
+      tags:
+      - rubikscube
+      n_groups:
+      - 512
+ctx_manager:
+  generation:
+    gen_config:
+      response_length: ${actor_rollout_ref.rollout.response_length}
+      temperature: ${actor_rollout_ref.rollout.temperature}
+      top_p: ${actor_rollout_ref.rollout.top_p}
+      top_k: ${actor_rollout_ref.rollout.top_k}
+      kwargs: null

outputs/2026-06-18/11-52-39/.hydra/hydra.yaml

@@ -0,0 +1,179 @@
+hydra:
+  run:
+    dir: outputs/${now:%Y-%m-%d}/${now:%H-%M-%S}
+  sweep:
+    dir: multirun/${now:%Y-%m-%d}/${now:%H-%M-%S}
+    subdir: ${hydra.job.num}
+  launcher:
+    _target_: hydra._internal.core_plugins.basic_launcher.BasicLauncher
+  sweeper:
+    _target_: hydra._internal.core_plugins.basic_sweeper.BasicSweeper
+    max_batch_size: null
+    params: null
+  help:
+    app_name: ${hydra.job.name}
+    header: '${hydra.help.app_name} is powered by Hydra.
+
+      '
+    footer: 'Powered by Hydra (https://hydra.cc)
+
+      Use --hydra-help to view Hydra specific help
+
+      '
+    template: '${hydra.help.header}
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (group=option)
+
+
+      $APP_CONFIG_GROUPS
+
+
+      == Config ==
+
+      Override anything in the config (foo.bar=value)
+
+
+      $CONFIG
+
+
+      ${hydra.help.footer}
+
+      '
+  hydra_help:
+    template: 'Hydra (${hydra.runtime.version})
+
+      See https://hydra.cc for more info.
+
+
+      == Flags ==
+
+      $FLAGS_HELP
+
+
+      == Configuration groups ==
+
+      Compose your configuration from those groups (For example, append hydra/job_logging=disabled
+      to command line)
+
+
+      $HYDRA_CONFIG_GROUPS
+
+
+      Use ''--cfg hydra'' to Show the Hydra config.
+
+      '
+    hydra_help: ???
+  hydra_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][HYDRA] %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+    root:
+      level: INFO
+      handlers:
+      - console
+    loggers:
+      logging_example:
+        level: DEBUG
+    disable_existing_loggers: false
+  job_logging:
+    version: 1
+    formatters:
+      simple:
+        format: '[%(asctime)s][%(name)s][%(levelname)s] - %(message)s'
+    handlers:
+      console:
+        class: logging.StreamHandler
+        formatter: simple
+        stream: ext://sys.stdout
+      file:
+        class: logging.FileHandler
+        formatter: simple
+        filename: ${hydra.runtime.output_dir}/${hydra.job.name}.log
+    root:
+      level: INFO
+      handlers:
+      - console
+      - file
+    disable_existing_loggers: false
+  env: {}
+  mode: RUN
+  searchpath: []
+  callbacks: {}
+  output_subdir: .hydra
+  overrides:
+    hydra:
+    - hydra.mode=RUN
+    task:
+    - system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+    - actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+    - actor_rollout_ref.rollout.rollout_filter_value=0.9
+    - trainer.total_training_steps=200
+    - trainer.n_gpus_per_node=8
+    - model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa
+    - custom_envs.rubikscube.env_config.scramble_depth=1
+    - trainer.experiment_name=rubikscube1_withthink_fulltrajc_sa
+    - trainer.save_freq=200
+    - trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa_rl
+  job:
+    name: train
+    chdir: null
+    override_dirname: actor_rollout_ref.rollout.rollout_filter_strategy=top_p,actor_rollout_ref.rollout.rollout_filter_value=0.9,custom_envs.rubikscube.env_config.scramble_depth=1,model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa,system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7',trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa_rl,trainer.experiment_name=rubikscube1_withthink_fulltrajc_sa,trainer.n_gpus_per_node=8,trainer.save_freq=200,trainer.total_training_steps=200
+    id: ???
+    num: ???
+    config_name: _10_rubikscube
+    env_set: {}
+    env_copy: []
+    config:
+      override_dirname:
+        kv_sep: '='
+        item_sep: ','
+        exclude_keys: []
+  runtime:
+    version: 1.3.2
+    version_base: '1.3'
+    cwd: /mnt/general/wanghy/RAGEN_v2
+    config_sources:
+    - path: hydra.conf
+      schema: pkg
+      provider: hydra
+    - path: /mnt/general/wanghy/RAGEN_v2/config
+      schema: file
+      provider: main
+    - path: /mnt/general/wanghy/RAGEN_v2/verl/verl/trainer/config
+      schema: file
+      provider: command-line
+    - path: ''
+      schema: structured
+      provider: schema
+    output_dir: /mnt/general/wanghy/RAGEN_v2/outputs/2026-06-18/11-52-39
+    choices:
+      reward_model: dp_reward_model
+      critic: dp_critic
+      critic/../engine@critic.model.fsdp_config: fsdp
+      critic/../optim@critic.optim: fsdp
+      model@actor_rollout_ref.model: hf_model
+      rollout@actor_rollout_ref.rollout: rollout
+      ref@actor_rollout_ref.ref: dp_ref
+      ref/../engine@actor_rollout_ref.ref.fsdp_config: fsdp
+      data: legacy_data
+      actor@actor_rollout_ref.actor: dp_actor
+      actor/../engine@actor_rollout_ref.actor.fsdp_config: fsdp
+      actor/../optim@actor_rollout_ref.actor.optim: fsdp
+      hydra/env: default
+      hydra/callbacks: null
+      hydra/job_logging: default
+      hydra/hydra_logging: default
+      hydra/hydra_help: default
+      hydra/help: default
+      hydra/sweeper: basic
+      hydra/launcher: basic
+      hydra/output: default
+  verbose: false

outputs/2026-06-18/11-52-39/.hydra/overrides.yaml

@@ -0,0 +1,10 @@
+- system.CUDA_VISIBLE_DEVICES='0,1,2,3,4,5,6,7'
+- actor_rollout_ref.rollout.rollout_filter_strategy=top_p
+- actor_rollout_ref.rollout.rollout_filter_value=0.9
+- trainer.total_training_steps=200
+- trainer.n_gpus_per_node=8
+- model_path=/mnt/general/wanghy/LLaMA-Factory/saves/qwen3/full/sft/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa
+- custom_envs.rubikscube.env_config.scramble_depth=1
+- trainer.experiment_name=rubikscube1_withthink_fulltrajc_sa
+- trainer.save_freq=200
+- trainer.default_local_dir=/mnt/general/wanghy/RAGEN_v2/saves/qwen2.5_3B_it_rubikscube1_withthink_fulltraj_sa_rl