use mean value for loss
@@ -79,7 +79,8 @@ class LossCrossEntropy(Loss):
logits = [self.model.get_logits(x, **kwargs) for x in x]
loss = sum(
- softmax_cross_entropy_with_logits(labels=y, logits=logit)
+ tf.reduce_mean(softmax_cross_entropy_with_logits(labels=y,
+ logits=logit))
for logit in logits)
return loss
