duo_ai.core.config
==================

.. py:module:: duo_ai.core.config


Classes
-------

.. autoapisummary::

   duo_ai.core.config.MasterConfig


Functions
---------

.. autoapisummary::

   duo_ai.core.config.configure


Module Contents
---------------

.. py:class:: MasterConfig

   Main configuration class for the Duo framework.

   This class holds all experiment-level configuration, including environment, policy, algorithm, evaluation, and coordination settings.

   :param name: Name of the experiment. Default is "default".
   :type name: str, optional
   :param device: Device index for CUDA. Default is 0.
   :type device: int, optional
   :param seed: Random seed for reproducibility. Default is 10.
   :type seed: int, optional
   :param env: Environment configuration or name. Default is "procgen".
   :type env: Any, optional
   :param policy: Policy configuration or name. Default is "PPOPolicy".
   :type policy: Any, optional
   :param algorithm: Algorithm configuration or name. Default is "PPOAlgorithm".
   :type algorithm: Any, optional
   :param evaluation: Evaluation configuration. Default is None.
   :type evaluation: Any, optional
   :param eval_name: Name for evaluation run. Default is None.
   :type eval_name: str, optional
   :param overwrite: Whether to overwrite existing experiment directory. Default is False.
   :type overwrite: bool, optional
   :param use_wandb: Whether to use Weights & Biases logging. Default is False.
   :type use_wandb: bool, optional
   :param experiment_dir: Path to the experiment directory. Default is "".
   :type experiment_dir: str, optional
   :param train_novice: Path to novice training checkpoint. Default is None.
   :type train_novice: str, optional
   :param train_expert: Path to expert training checkpoint. Default is None.
   :type train_expert: str, optional
   :param test_novice: Path to novice test checkpoint. Default is None.
   :type test_novice: str, optional
   :param test_expert: Path to expert test checkpoint. Default is None.
   :type test_expert: str, optional
   :param coordination: Coordination configuration. Default is None.
   :type coordination: Any, optional

   .. rubric:: Examples

   >>> config = MasterConfig(name="my_experiment", env="procgen", policy="PPOPolicy")


   .. py:attribute:: name
      :type:  str
      :value: 'default'



   .. py:attribute:: device
      :type:  int
      :value: 0



   .. py:attribute:: seed
      :type:  int
      :value: 10



   .. py:attribute:: env
      :type:  Any
      :value: 'procgen'



   .. py:attribute:: policy
      :type:  Any
      :value: 'PPOPolicy'



   .. py:attribute:: algorithm
      :type:  Any
      :value: 'PPOAlgorithm'



   .. py:attribute:: evaluation
      :type:  Any
      :value: None



   .. py:attribute:: eval_mode
      :type:  Optional[int]
      :value: None



   .. py:attribute:: eval_name
      :type:  Optional[str]
      :value: None



   .. py:attribute:: overwrite
      :type:  bool
      :value: False



   .. py:attribute:: use_wandb
      :type:  bool
      :value: False



   .. py:attribute:: experiment_dir
      :type:  str
      :value: ''



   .. py:attribute:: train_novice
      :type:  Optional[str]
      :value: None



   .. py:attribute:: train_expert
      :type:  Optional[str]
      :value: None



   .. py:attribute:: test_novice
      :type:  Optional[str]
      :value: None



   .. py:attribute:: test_expert
      :type:  Optional[str]
      :value: None



   .. py:attribute:: coordination
      :type:  Any
      :value: None



   .. py:method:: __post_init__() -> None

      Post-initialization logic for MasterConfig.

      Converts string or dictionary fields for env, policy, algorithm, evaluation, and coordination
      into their respective configuration objects.

      :raises IndexError: If required keys are missing in configuration dictionaries.
      :raises ValueError: If configuration fields are not of expected types.

      .. rubric:: Examples

      >>> config = MasterConfig(env={"name": "procgen"})
      >>> config.__post_init__()



.. py:function:: configure(config: MasterConfig) -> None

   Set up experiment directory, logging, random seeds, and global variables for the experiment.

   :param config: The experiment configuration object.
   :type config: MasterConfig

   :rtype: None

   :raises FileExistsError: If the experiment directory exists and overwrite is not set.

   .. rubric:: Examples

   >>> configure(config)