cotengra.hyperoptimizers.hyper_optuna
=====================================

.. py:module:: cotengra.hyperoptimizers.hyper_optuna

.. autoapi-nested-parse::

   Hyper optimization using optuna.



Classes
-------

.. autoapisummary::

   cotengra.hyperoptimizers.hyper_optuna.OptunaOptLib


Functions
---------

.. autoapisummary::

   cotengra.hyperoptimizers.hyper_optuna.make_getter
   cotengra.hyperoptimizers.hyper_optuna.make_retriever


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

.. py:function:: make_getter(name, param)

.. py:function:: make_retriever(methods, space)

.. py:class:: OptunaOptLib

   Bases: :py:obj:`cotengra.hyperoptimizers.hyper.HyperOptLib`


   Hyper-optimization using ``optuna``.


   .. py:method:: setup(methods, space, optimizer=None, sampler='TPESampler', sampler_opts=None, **create_study_opts)

      Initialize the optimizer state.

      :param methods: The list of contraction methods to optimize over.
      :type methods: list[str]
      :param space: The search space for each method.
      :type space: dict[str, dict[str, dict]]
      :param optimizer: The parent ``HyperOptimizer`` instance, for accessing
                        attributes like ``max_repeats``.
      :type optimizer: HyperOptimizer, optional
      :param kwargs: Extra options specific to the optimizer library.



   .. py:method:: get_setting()

      Suggest the next setting to trial.

      :returns: **setting** -- Must contain at least ``{"method": str, "params": dict}``.
                May also include tokens for reporting.
      :rtype: dict



   .. py:method:: report_result(setting, trial, score)

      Report the result of a trial.

      :param setting: The setting dict returned by ``get_setting``.
      :type setting: dict
      :param trial: The trial result dict.
      :type trial: dict
      :param score: The scalar score for this trial.
      :type score: float