def adv_loss(preds, labels):
"""
Calculates the sum of BCE losses between the predicted classifications and true labels.
@param preds: The predicted classifications at each scale.
@param labels: The true labels. (Same for every scale).
@return: The adversarial loss.
"""
# calculate the loss for each scale
scale_losses = []
for i in xrange(len(preds)):
loss = bce_loss(preds[i], labels)
scale_losses.append(loss)
# condense into one tensor and avg
return tf.reduce_mean(tf.pack(scale_losses))
loss_functions.py 文件源码
python
阅读 29
收藏 0
点赞 0
评论 0
评论列表
文章目录