Korean
언어
English
Bengali
French
German
Japanese
Korean
Portuguese
Spanish
Tamil

Optimizer

class Optimizer[소스]

기반 클래스: ABC

Base class for optimization algorithm.

Initialize the optimization algorithm, setting the support level for _gradient_support_level, _bound_support_level, _initial_point_support_level, and empty options.

Methods

get_support_level

Return support level dictionary

gradient_num_diff

We compute the gradient with the numeric differentiation in the parallel way, around the point x_center.

minimize

Minimize the scalar function.

print_options

Print algorithm-specific options.

set_max_evals_grouped

Set max evals grouped

set_options

Sets or updates values in the options dictionary.

wrap_function

Wrap the function to implicitly inject the args at the call of the function.

Attributes

bounds_support_level

Returns bounds support level

gradient_support_level

Returns gradient support level

initial_point_support_level

Returns initial point support level

is_bounds_ignored

Returns is bounds ignored

is_bounds_required

Returns is bounds required

is_bounds_supported

Returns is bounds supported

is_gradient_ignored

Returns is gradient ignored

is_gradient_required

Returns is gradient required

is_gradient_supported

Returns is gradient supported

is_initial_point_ignored

Returns is initial point ignored

is_initial_point_required

Returns is initial point required

is_initial_point_supported

Returns is initial point supported

setting

Return setting

settings

The optimizer settings in a dictionary format.

The settings can for instance be used for JSON-serialization (if all settings are serializable, which e.g. doesn’t hold per default for callables), such that the optimizer object can be reconstructed as

settings = optimizer.settings
# JSON serialize and send to another server
optimizer = OptimizerClass(**settings)
반환 형식

Dict[str, Any]