Regularizers¶
Regularization in PyKEEN.
Functions¶
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Get the regularizer class. |
Classes¶
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A simple L_p norm based regularizer. |
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A regularizer which does not perform any regularization. |
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A convex combination of regularizers. |
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A simple x^p based regularizer. |
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A regularizer for the soft constraints in TransH. |
Class Inheritance Diagram¶
Base Classes¶
- class Regularizer(device, weight=1.0, apply_only_once=False)[source]¶
A base class for all regularizers.
Initializes internal Module state, shared by both nn.Module and ScriptModule.
- apply_only_once: bool¶
Should the regularization only be applied once? This was used for ConvKB and defaults to False.
- abstract forward(x)[source]¶
Compute the regularization term for one tensor.
- Return type
FloatTensor
- classmethod get_normalized_name()[source]¶
Get the normalized name of the regularizer class.
- Return type
- hpo_default: ClassVar[Mapping[str, Any]]¶
The default strategy for optimizing the regularizer’s hyper-parameters
- regularization_term: torch.FloatTensor¶
The current regularization term (a scalar)
- property term: torch.FloatTensor¶
Return the weighted regularization term.
- Return type
FloatTensor
- weight: torch.FloatTensor¶
The overall regularization weight