def cross_entropy_loss_fn(
    outputs: jnp.ndarray,
    targets: Array,
) -> jnp.ndarray:
    """
    A cross-entropy loss function. Check `here <https://en.wikipedia.org/wiki/Cross_entropy>`_ for reference.

    Parameters
    ----------
    outputs: Array
        Model outputs to be passed to the loss.
    targets: Array
        Target data points.

    Returns
    -------
    Tuple[jnp.ndarray, Any]
        The cross-entropy loss evaluation and auxiliary objects.
    """
    targets = jax.nn.one_hot(targets, outputs.shape[-1])
    return jnp.mean(jsp.special.logsumexp(outputs, -1) - jnp.sum(targets * outputs, -1))

    A cross-entropy loss function. Check `here <https://en.wikipedia.org/wiki/Cross_entropy>`_ for reference.

    Parameters
    ----------
    outputs: Array
        Model outputs to be passed to the loss.
    targets: Array
        Target data points.

    Returns
    -------
    Tuple[jnp.ndarray, Any]
        The cross-entropy loss evaluation and auxiliary objects.
    
fortuna/loss/classification/cross_entropy.py