"sample": [tf.add_n(d_losses), tf.add_n(g_losses)],
"metrics": self.gan.metrics
})
print(standard_loss.metrics)
for k,v in standard_loss.metrics.items():
loss.metrics[k]=v
self.loss = loss
self.metrics = self.loss.metrics
After Change
d_losses=[l2_loss]
for i,l in enumerate(g_losses):
self.add_metric("gl"+str(i), l)
for i,l in enumerate(d_losses):
self.add_metric("dl"+str(i),l)
loss = hc.Config({
"d_fake":standard_loss.d_fake,