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.
Args |
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).
|
Returns |
A Tensor . Has the same type as logits .
|