tfa.losses.sparsemax_loss

Sparsemax loss function 1.

tfa.losses.sparsemax_loss(
    logits: tfa.image.color_ops.TensorLike,
    sparsemax: tfa.image.color_ops.TensorLike,
    labels: tfa.image.color_ops.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 properbility 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`.

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Last updated 2020-06-10.

tfa.losses.sparsemax_loss

Args

Returns