opendataval.model.ModelFactory

opendataval.model.ModelFactory(model_name: str, fetcher: DataFetcher | None = None, device: device = device(type='cpu'), *args, **kwargs) → Model

Factory to create prediction models from specified presets

Model Factory that creates a specified mode, based on the input parameters, it is recommended to import the specific model and specify additional arguments instead of relying on the factory.

Parameters

model_namestr

Name of prediction model

covar_dimtuple[int, …]

Dimensions of the covariates, typically the shape besides first dimension

label_dimtuple[int, …]

Dimensions of the labels, typically the shape besides first dimension

devicetorch.device, optional

Tensor device for acceleration, some models do not use this argument, by default torch.device(“cpu”)

argstuple[Any]

Additional positional arguments passed to the Model constructor

kwargstuple[Any]

Additional key word arguments passed to the Model constructor

Returns

Model

Preset model with the specified dimensions on the specified tensor device

Raises

ValueError

Raises exception when model name is not matched