mlx.nn.losses.hinge_loss#

hinge_loss(inputs: array, targets: array, reduction: Literal['none', 'mean', 'sum'] = 'none') array#

Computes the hinge loss between inputs and targets.

\[\text{hinge}(y, y_{\text{pred}}) = \max(0, 1 - y \cdot y_{\text{pred}})\]
Parameters:
  • inputs (array) – The predicted values.

  • targets (array) – The target values. They should be -1 or 1.

  • reduction (str, optional) – Specifies the reduction to apply to the output: 'none' | 'mean' | 'sum'. Default: 'none'.

Returns:

The computed hinge loss.

Return type:

array