leaspy.io.realizations.PopulationRealization

class PopulationRealization(name: str, shape: Tuple[int, ...], *, tensor: Tensor | None = None, tensor_copy: bool = True, **kwargs)

Bases: AbstractRealization

Class for realizations of population variables.

Parameters:

nameParamType

The name of the variable associated with the realization.

shapeTuple[int, …]

The shape of the tensor realization.

tensortorch.Tensor, optional

If not None, the tensor realization to be stored.

tensor_copybool (default True)

Whether the tensor provided is copied or not.

**kwargsdict

Additional parameters.

Attributes:

tensor

Methods

initialize(model, **kwargs)	Initialize the realization from a model instance.
set_autograd()	Set autograd for tensor of realizations.
set_tensor_realizations_element(element, dim)	Manually change the value (in-place) of tensor_realizations at dimension dim.
to_dict()	Return a serialized dictionary of realization attributes.
unset_autograd()	Unset autograd for tensor of realizations

initialize(model: AbstractModel, **kwargs: KwargsType) → None

Initialize the realization from a model instance.

Parameters:

modelAbstractModel

The model from which to initialize the realization.

**kwargsKwargsType

Additional parameters for initialization.

set_autograd() → None

Set autograd for tensor of realizations.

TODO remove? only in legacy code

Raises:

ValueError

if inconsistent internal request

See also

torch.Tensor.requires_grad_

set_tensor_realizations_element(element: Tensor, dim: tuple[int, ...]) → None

Manually change the value (in-place) of tensor_realizations at dimension dim.

Parameters:

elementtorch.Tensor

The element to put in the tensor realization.

dimTuple[int, …]

The dimension where to put the element.

to_dict() → Dict[str, Any]

Return a serialized dictionary of realization attributes.

unset_autograd() → None

Unset autograd for tensor of realizations

TODO remove? only in legacy code

Raises:

ValueError

if inconsistent internal request

See also

torch.Tensor.requires_grad_