def METHOD_NAME(self):
    embeddings_list = np.array(self.embeddings)
    num = embeddings_list.shape[0]
    embeddings = embeddings_list[:num//2] + embeddings_list[num//2:]
    embeddings = embeddings.squeeze()
    embeddings = sklearn.preprocessing.normalize(embeddings)
    thresholds = np.arange(0, 4, 0.02)
    embeddings1 = embeddings[0::2]
    embeddings2 = embeddings[1::2]
    accuracy = calculate_roc(thresholds, embeddings1, embeddings2,
        np.asarray(self.actual_issame), nrof_folds=self.nfolds)
    return np.mean(accuracy)