braindecode.training.CroppedLoss

class braindecode.training.CroppedLoss(loss_function)

Compute Loss after averaging predictions across time. Assumes predictions are in shape: n_batch size x n_classes x n_predictions (in time)

Methods

forward(preds, targets)

Forward pass.

Parameters:

• preds (torch.Tensor) – Model’s prediction with shape (batch_size, n_classes, n_times).

• targets (torch.Tensor) – Targets with shape (batch_size,), or (batch_size, n_classes) for regression. Mixup’s (y_a, y_b, lam) is passed to loss_function as is.

Examples using braindecode.training.CroppedLoss

Cropped Decoding on BCIC IV 2a Dataset

Cropped Decoding on BCIC IV 2a Dataset

Convolutional neural network regression model on fake data.

Convolutional neural network regression model on fake data.

Fingers flexion cropped decoding on BCIC IV 4 ECoG Dataset

Fingers flexion cropped decoding on BCIC IV 4 ECoG Dataset