tfa.losses.sparsemax_loss

Sparsemax loss function 1.

tfa.losses.sparsemax_loss(
    logits: tfa.types.TensorLike,
    sparsemax: tfa.types.TensorLike,
    labels: tfa.types.TensorLike,
    name: Optional[str] = None
) -> tf.Tensor

Computes the generalized multi-label classification loss for the sparsemax function. The implementation is a reformulation of the original loss function such that it uses the sparsemax probability output instead of the internal \( au \) variable. However, the output is identical to the original loss function.

logits A Tensor. Must be one of the following types: float32, float64.
sparsemax A Tensor. Must have the same type as logits.
labels A Tensor. Must have the same type as logits.
name A name for the operation (optional).

A Tensor. Has the same type as logits.