neuralogic.core.settings package

Submodules

neuralogic.core.settings.settings_proxy module

class SettingsProxy(*, optimizer: Optimizer, error_function: ErrorFunction, initializer: Initializer, iso_value_compression: bool, chain_pruning: bool, prune_only_identities: bool, grounder: Grounder)

Bases: object

Proxy class for the Java Settings object.

It provides a Pythonic interface to configure various parameters of the NeuraLogic backend, such as optimizers, initializers, error functions, and grounding algorithms.

property chain_pruning: bool

Whether to use chain pruning (reducing redundant chains of operations).

property debug_exporting: bool

property default_fact_value: float

property error_function: Any

The error function used for training.

get_aggregation_function(aggregation: Aggregation) → Any

get_combination_function(combination: Combination) → Any

Returns the Java combination function for the given Python enum value.

Parameters:

combination (Combination) – The combination function enum value.

Returns:

The Java combination function object.

Return type:

Any

get_transformation_function(transformation: Transformation) → Any

property grounder: Any

The grounding algorithm to use.

property initializer: Any

The weight initializer used for model parameters.

property initializer_const: float

property initializer_uniform_scale: float

property iso_value_compression: bool

Whether to use iso-value compression.

property optimizer: Optimizer

The optimizer used for training.

property prune_only_identities: bool

property relation_combination: CombinationFunction

property relation_transformation: TransformationFunction

property rule_aggregation: AggregationFunction

property rule_combination: CombinationFunction

property rule_transformation: TransformationFunction

to_json() → str

Exports the settings to a JSON string.

Returns:

The JSON representation of the settings.

Return type:

str

Module contents

class Settings(*, optimizer: Optimizer = <neuralogic.nn.optim.adam.Adam object>, error_function: ErrorFunction = <neuralogic.nn.loss.MSE object>, initializer: Initializer = <neuralogic.nn.init.Uniform object>, iso_value_compression: bool = True, chain_pruning: bool = True, prune_only_identities: bool = False, grounder: Grounder = Grounder.BUP)

Bases: object

property chain_pruning: bool

create_disconnected_proxy() → SettingsProxy

create_proxy() → SettingsProxy

property error_function: ErrorFunction

property grounder: Grounder

property initializer: Initializer

property iso_value_compression: bool

property optimizer: Optimizer

property prune_only_identities: bool