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 instatiate 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: Optional[Tensor] = None) Tuple[Tensor, 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.
Examples using braindecode.augmentation.Transform#
Searching the best data augmentation on BCIC IV 2a Dataset