946c74ea83f93967e28c585d0bbcd17afbfebb13,niftynet/layer/loss_segmentation.py,,cross_entropy,#Any#Any#Any#,267

Before Change

    entropy = tf.nn.sparse_softmax_cross_entropy_with_logits(
        logits=prediction, labels=ground_truth)
    if weight_map is not None:
        weight_map = tf.cast(tf.size(entropy), dtype=tf.float32) / \
                     tf.reduce_sum(weight_map) * weight_map
        entropy = tf.multiply(entropy, weight_map)
    return tf.reduce_mean(entropy)

After Change

        return tf.reduce_mean(entropy)

    weight_sum = tf.maximum(tf.reduce_sum(weight_map), 1e-6)
    return tf.reduce_sum(entropy * weight_map / weight_sum)


def cross_entropy_dense(prediction, ground_truth, weight_map=None):
    if weight_map is not None:

Instances