def softmax(logits):
assert logits.ndim == <NUM_LIT:1><EOL>logits = logits - np.max(logits)<EOL>e = np.exp(logits)<EOL>return e / np.sum(e)<EOL>
Transforms predictions into probability values.

    Parameters
    ----------
    logits : array_like
        The logits predicted by the model.

    Returns
    -------
    `numpy.ndarray`
        Probability values corresponding to the logits.