braindecode.augmentation.Transform#

class braindecode.augmentation.Transform(probability=1.0, random_state=None)[source]#

Basic transform class used for implementing data augmentation operations.

Parameters:

  • operation (callable) – A function taking arrays X, y (inputs and targets resp.) and other required arguments, and returning the transformed X and y.

  • probability (float, optional) – Float between 0 and 1 defining the uniform probability of applying the operation. Set to 1.0 by default (e.g always apply the operation).

  • random_state (int, optional) – Seed to be used to instantiate numpy random number generator instance. Used to decide whether or not to transform given the probability argument. Defaults to None.

Methods

forward(X: Tensor, y: Tensor | None = None) → Tensor | tuple[Tensor, Tensor | tuple[Tensor, ...]][source]#

General forward pass for an augmentation transform.

Parameters:

  • X (torch.Tensor) – EEG input example or batch.

  • y (torch.Tensor | None) – EEG labels for the example or batch. Defaults to None.

Returns:

  • torch.Tensor – Transformed inputs.

  • torch.Tensor, optional – Transformed labels. Only returned when y is not None.

get_augmentation_params(*batch)[source]#