deep-learning - keras:平滑 L1 损失

Question

尝试在 keras 中自定义损失函数(平滑 L1 损失)，如下所示

ValueError: Shape must be rank 0 but is rank 5 for 'cond/Switch' (op: 'Switch') with input shapes: [?,24,24,24,?], [?,24,24,24,?].

from keras import backend as K
import numpy as np


def smooth_L1_loss(y_true, y_pred):
    THRESHOLD = K.variable(1.0)
    mae = K.abs(y_true-y_pred)
    flag = K.greater(mae, THRESHOLD)
    loss = K.mean(K.switch(flag, (mae - 0.5), K.pow(mae, 2)), axis=-1)
    return loss

Answer 1

我知道我参加聚会晚了两年，但是如果您使用 tensorflow 作为 keras 后端，您可以使用 tensorflow 的 Huber loss (本质上是一样的)像这样:

import tensorflow as tf


def smooth_L1_loss(y_true, y_pred):
    return tf.losses.huber_loss(y_true, y_pred)