67bd0ba416366c2b31006a5bf951ae9586135f7c,tf_unet/layers.py,,pixel_wise_softmax,#,60

Before Change

    with tf.name_scope("pixel_wise_softmax"):
        exponential_map = tf.exp(output_map)
        evidence = tf.add(exponential_map,tf.reverse(exponential_map,[False,False,False,True]))
        return tf.div(exponential_map,evidence, name="pixel_wise_softmax")

def pixel_wise_softmax_2(output_map):
    with tf.name_scope("pixel_wise_softmax_2"):
        exponential_map = tf.exp(output_map)

After Change

    with tf.name_scope("pixel_wise_softmax"):
        max_axis = tf.reduce_max(output_map, axis=3, keepdims=True)
        exponential_map = tf.exp(output_map - max_axis)
        normalize = tf.reduce_sum(exponential_map, axis=3, keepdims=True)
        return exponential_map / normalize

def cross_entropy(y_,output_map):
    with tf.name_scope("xent"):
        return -tf.reduce_mean(y_*tf.log(tf.clip_by_value(output_map,1e-10,1.0)), name="cross_entropy")

Instances