2ba7725df0cbc3183d9cdc49f797614d24c9f80e,detector/detector.py,,metrics,#Any#Any#,130

Before Change

    // TODO: Doesn"t make much sense over training data, averaging with initial
    // (bad) predictions.
    auc, update_auc_op = tf.metrics.auc(labels, logits, curve="PR")
    tf.add_to_collection("metric_ops", update_auc_op)
    tf.add_to_collection("metrics", auc)
    tf.summary.scalar("auc", auc)


def loss(logits, labels):

After Change

        )
        tf.summary.scalar(f"iauc/{cls}", auc)

    auc, _ = tf.metrics.auc(
        labels, normalized_logits,
        curve="PR", name="auc",
        metrics_collections="metrics",

Instances