leaspy.models.utils.attributes.abstract_attributes module
- class AbstractAttributes(name: str, dimension: Optional[int] = None, source_dimension: Optional[int] = None)
Bases:
ABCAbstract base class for attributes of models.
Contains the common attributes & methods of the different attributes classes. Such classes are used to update the models’ attributes.
- Parameters
- namestr
- dimensionint (default None)
- source_dimensionint (default None)
- Raises
LeaspyModelInputErrorif any inconsistent parameter.
- Attributes
- namestr
Name of the associated leaspy model.
- dimensionint
Number of features of the model
- source_dimensionint
Number of sources of the model TODO? move to AbstractManifoldModelAttributes?
- univariatebool
Whether model is univariate or not (i.e. dimension == 1)
- has_sourcesbool
Whether model has sources or not (not univariate and source_dimension >= 1) TODO? move to AbstractManifoldModelAttributes?
- update_possibilitiestuple[str] (default empty)
Contains the available parameters to update. Different models have different parameters.
Methods
Returns the essential attributes of a given model.
move_to_device(device)Move the tensor attributes of this class to the specified device.
update(names_of_changed_values, values)Update model group average parameter(s).
- abstract get_attributes() Tuple[FloatTensor, ...]
Returns the essential attributes of a given model.
- Returns
- Depends on the subclass, please refer to each specific class.
- move_to_device(device: device)
Move the tensor attributes of this class to the specified device.
- Parameters
- devicetorch.device
- abstract update(names_of_changed_values: Tuple[str, ...], values: Dict[str, FloatTensor]) None
Update model group average parameter(s).
- Parameters
- names_of_changed_valueslist [str]
Values to be updated
- valuesdict [str, torch.Tensor]
New values used to update the model’s group average parameters
- Raises
LeaspyModelInputErrorIf names_of_changed_values contains unknown values to update.