tf.keras.losses.circle

Computes the Circle loss.

tf.keras.losses.circle(
    y_true,
    y_pred,
    ref_labels=None,
    ref_embeddings=None,
    remove_diagonal=True,
    gamma=80,
    margin=0.4
)

It is designed to minimize within-class distances and maximize between-class distances in L2 normalized embedding space.

y_true Tensor with ground truth labels in integer format.
y_pred Tensor with predicted L2 normalized embeddings.
ref_labels Optional integer tensor with labels for reference embeddings. If None, defaults to y_true.
ref_embeddings Optional tensor with L2 normalized reference embeddings. If None, defaults to y_pred.
remove_diagonal Boolean, whether to remove self-similarities from positive mask. Defaults to True.
gamma Float, scaling factor for the loss. Defaults to 80.
margin Float, relaxation factor for the loss. Defaults to 0.4.

Circle loss value.