tuning.rst

Tuning of graph parameters

All tuners work with internal graph representation (also called optimization graph, see Adaptation of Graphs). To optimise custom domain graph pass adapter. If your graph class is inherited from OptGraph no adapter is needed. Tuners optimise parameters stored in OptNode.parameters.

Multi-objective optimisation is supported only by OptunaTuner.

To specify parameters search space use SearchSpace class. Initialize SearchSpace with dictionary of the form {'operation_name': {'param_name': { 'hyperopt-dist': <hyperopt distribution function>, 'sampling-scope': [sampling scope], 'type': <type of parameter>}, ...}, ...}. Three types of parameters are available: continuous, discrete and categorical.

import numpy as np
from hyperopt import hp
from golem.core.tuning.search_space import SearchSpace


params_per_operation = {
    'operation_name_1': {
        'parameter_name_1': {
            'hyperopt-dist': hp.uniformint,
            'sampling-scope': [2, 21],
            'type': 'discrete'},
        'parameter_name_2': {
            'hyperopt-dist': hp.loguniform,
            'sampling-scope': [1e-3, 1],
            'type': 'continuous'}
    },
    'operation_name_2': {
        'parameter_name_1': {
            'hyperopt-dist': hp.choice,
            'sampling-scope': [["first", "second", "third"]],
            'type': 'categorical'},
        'parameter_name_2':
            'hyperopt-dist': hp.uniform,
            'sampling-scope': [0.05, 1.0],
            'type': 'continuous'}
    }}

search_space = SearchSpace(params_per_operation)

Simultaneous

You can tune all parameters of graph nodes simultaneously using SimultaneousTuner, OptunaTuner or IOptTuner.

Note

IOptTuner implements deterministic algorithm.

IOptTuner is implemented using IOpt library. See the documentation (in Russian) to learn more about the optimisation algorithm.

.. automodule:: golem.core.tuning.simultaneous
   :members:

.. autoclass:: golem.core.tuning.iopt_tuner.IOptTuner
   :members:

.. autoclass:: golem.core.tuning.optuna_tuner.OptunaTuner
   :members:

Sequential

SequentialTuner allows you to tune graph parameters sequentially node by node.

.. automodule:: golem.core.tuning.sequential
   :members: