trinity.manager

Subpackages

• trinity.manager.config_registry
  • Submodules
  • trinity.manager.config_registry.algorithm_config_manager module
    • set_algorithm_type()
    • set_repeat_times()
    • set_sample_strategy()
    • set_expert_data_ratio_in_sample_strategy()
    • set_advantage_fn()
    • set_gamma_in_advantage_fn()
    • set_lam_in_advantage_fn()
    • set_epsilon_in_advantage_fn()
    • set_opmd_baseline_in_advantage_fn()
    • set_tau_in_advantage_fn()
    • set_kl_loss_fn()
    • set_kl_coef_in_kl_loss_fn()
    • set_kl_penalty_fn()
    • set_adaptive_in_kl_penalty_fn()
    • set_kl_coef_in_kl_penalty_fn()
    • set_policy_loss_fn()
    • set_clip_range_in_policy_loss_fn()
    • set_use_token_level_loss_in_policy_loss_fn()
    • set_beta_in_policy_loss_fn()
    • set_label_smoothing_in_policy_loss_fn()
    • set_tau_in_policy_loss_fn()
    • set_mu_in_policy_loss_fn()
    • set_entropy_loss_fn()
    • set_entropy_coef_in_entropy_loss_fn()
  • trinity.manager.config_registry.buffer_config_manager module
    • set_total_epochs()
    • set_train_batch_size()
    • check_train_batch_size()
    • set_buffer_max_retry_times()
    • set_max_retry_interval()
    • set_taskset_path()
    • check_taskset_path()
    • set_taskset_args()
    • set_eval_tasksets()
    • set_default_workflow_type()
    • set_default_reward_fn_type()
    • set_system_prompt()
    • set_reply_prefix()
    • set_storage_type()
    • set_experience_buffer_path()
    • check_experience_buffer_path()
    • set_dpo_dataset_kwargs()
    • set_sft_warmup_dataset_path()
    • check_sft_warmup_dataset_path()
    • set_sft_warmup_dataset_args()
    • set_sft_warmup_steps()
  • trinity.manager.config_registry.config_registry module
    • ConfigRegistry
      • ConfigRegistry.__init__()
      • ConfigRegistry.set_unfinished_fields()
      • ConfigRegistry.default_config
      • ConfigRegistry.get()
      • ConfigRegistry.get_check_func()
      • ConfigRegistry.get_configs()
      • ConfigRegistry.register_config()
      • ConfigRegistry.register_check()
  • trinity.manager.config_registry.explorer_config_manager module
    • explorer_visible()
    • set_runner_num()
    • set_max_timeout()
    • set_explorer_max_retry_times()
    • set_eval_interval()
    • set_eval_on_latest_checkpoint()
    • set_engine_type()
    • set_engine_num()
    • set_tensor_parallel_size()
    • check_tensor_parallel_size()
    • set_use_v1()
    • set_enforce_eager()
    • set_enable_prefix_caching()
    • set_enable_chunked_prefill()
    • set_gpu_memory_utilization()
    • set_dtype()
    • set_seed()
    • set_enable_thinking()
    • set_enable_openai_api()
    • set_auxiliary_models()
    • check_auxiliary_models()
    • set_sync_method()
    • set_sync_interval()
    • set_sync_timeout()
  • trinity.manager.config_registry.model_config_manager module
    • set_total_gpu_num()
    • set_trainer_gpu_num()
    • set_project()
    • set_exp_name()
    • set_checkpoint_root_dir()
    • check_checkpoint_root_dir()
    • set_monitor_type()
    • set_model_path()
    • check_model_path()
    • set_critic_model_path()
    • set_max_prompt_tokens()
    • set_max_response_tokens()
    • set_node_num()
    • set_gpu_per_node()
  • trinity.manager.config_registry.trainer_config_manager module
    • use_critic()
    • set_trainer_type()
    • set_save_interval()
    • set_enable_preview()
    • set_actor_grad_clip()
    • set_training_args()
    • set_ppo_epochs()
    • set_training_strategy()
    • use_fsdp()
    • set_param_offload()
    • set_optimizer_offload()
    • set_resume_mode()
    • set_resume_from_path()
    • check_resume_from_path()
    • set_critic_warmup()
    • set_total_training_steps()
    • set_default_hdfs_dir()
    • set_remove_previous_ckpt_in_save()
    • set_del_local_ckpt_after_load()
    • set_max_actor_ckpt_to_keep()
    • set_max_critic_ckpt_to_keep()
    • set_norm_adv_by_std_in_grpo()
    • set_use_kl_in_reward()
    • set_kl_penalty()
    • set_kl_ctrl_type()
    • set_kl_ctrl_coef()
    • set_horizon()
    • set_target_kl()
    • set_actor_ppo_micro_batch_size_per_gpu()
    • set_ref_log_prob_micro_batch_size_per_gpu()
    • set_actor_ulysses_sequence_parallel_size()
    • set_actor_lr()
    • set_actor_warmup_style()
    • set_actor_lr_warmup_steps_ratio()
    • set_actor_kl_loss_type()
    • set_actor_checkpoint()
    • set_critic_lr()
    • set_critic_warmup_style()
    • set_critic_lr_warmup_steps_ratio()
    • set_critic_grad_clip()
    • set_critic_cliprange_value()
    • set_critic_ppo_micro_batch_size_per_gpu()
    • set_critic_ulysses_sequence_parallel_size()
    • set_critic_checkpoint()
  • Module contents

Submodules

trinity.manager.config_manager module

class trinity.manager.config_manager.ConfigManager

Bases: object

__init__()

reset_session_state()

maintain_session_state()

get_configs(*config_names: str, columns_spec: List[int] | None = None)

beginner_mode()

expert_mode()

generate_config()

run_config(parent, yaml_config: str) → None

trinity.manager.manager module

Data manager.

class trinity.manager.manager.CacheManager(config: Config, check_config: bool = False)

Bases: object

A Manager class for managing the cache dir.

__init__(config: Config, check_config: bool = False)

save_explorer(current_task_index: int, current_step: int) → None

load_explorer() → dict

save_trainer(current_step: int) → None

load_trainer() → dict

Module contents

class trinity.manager.Trainer(config: Config)

Bases: object

Consume the experience and train the model.

__init__(config: Config) → None

prepare() → None

Prepare the trainer.

train() → str

Train the model.

train_step() → bool

Train one step.

Returns:

Whether to continue training.

Return type:

bool

need_sync() → bool

Whether to sync the model weight.

sync_weight() → None

Sync the model weight.

flush_log(step: int) → None

Flush the log of the current step.

shutdown() → None

class trinity.manager.TrainEngineWrapper

Bases: ABC

A wrapper class to wrap various training engines.

abstract prepare() → None

Do some preparation before training started.

abstract property train_step_num: int

Get the current training step number.

abstract train_step() → bool

Training.

abstract save_checkpoint() → None

Save the checkpoint.

abstract sync_weight() → None

Sync the model weight.

abstract shutdown() → None

Shutdown the engine.

trinity.manager.get_trainer_wrapper(config: Config) → TrainEngineWrapper

Get a trainer wrapper.