braindecode.training.CroppedLoss#

class braindecode.training.CroppedLoss(loss_function)[source]#

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)[source]#

Forward pass.

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

  • targets (torch.Tensor) – Target labels with shape (batch_size, n_classes, n_times).

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