src.model.deeplearn.loss.multiloss_linear_superposition

Functions

vl3d_multiloss_linear_superposition(loss)

Function to compute the linear superposition of an underlying loss function on many output heads that are assumed to correspond to a single set of reference samples.

src.model.deeplearn.loss.multiloss_linear_superposition.vl3d_multiloss_linear_superposition(loss)

Function to compute the linear superposition of an underlying loss function on many output heads that are assumed to correspond to a single set of reference samples.

\[\mathcal{L}'(\pmb{y}, \pmb{\hat{y}_1}, \ldots, \pmb{\hat{y}_l}) = \sum_{k=1}^{l}{\mathcal{L}(\pmb{y}, \pmb{\hat{y}_k})}\]

Parameters:

loss – The underlying loss function L. It must be evaluable for L(y_true, y_pred[i]), for any i.

Returns:

The linear superposition of the underlying loss function for each output head.