sleepless.engine.predictor_torch

Predcition script.

Functions

predict_torch(dataset, model, weight, ...)	Prepare data and model to runs inference on data.
run(model, data_loader, name, device, ...)	Runs inference on input data, outputs HDF5 files with predictions.

sleepless.engine.predictor_torch.run(model, data_loader, name, device, output_folder)

Runs inference on input data, outputs HDF5 files with predictions.

Parameters:

• model (Module) – neural network model fitted

• data_loader (DataLoader) – dataset

• name (str) – the local name of this dataset (e.g. train, or test), to be used when saving measures files.

• device (device) – device to use

• output_folder (str) – folder where to store output prediction (HDF5 files)

sleepless.engine.predictor_torch.predict_torch(dataset, model, weight, output_folder, model_parameters)

Prepare data and model to runs inference on data.

Parameters:

• dataset (dict) – A dictionary containing a torch.utils.data.ConcatDataset per key

• model (Module) – neural network model not fitted

• weight (str) – weigth path to fit the neural network

• output_folder (str) – folder where prediciton will be saved

• model_parameters (Mapping) – a dictionary where the following keys need to be defined, batch_size: int parallel: int device: str transform: list (if data are not trasnformed yet)