Use TrainingLoop in Autoencoder1D #677
Conversation
| } | ||
| var trainingLoop = TrainingLoop( | ||
| training: dataset.training.map { $0.map { LabeledData(data: $0.data, label: $0.data) } }, | ||
| validation: dataset.validation.map { LabeledData(data: $0.data, label: $0.data) }, |
There was a problem hiding this comment.
I don't think this is operating in the same way as the original model. For an autoencoder like this, we just want to train through the images once, then output a single input / output image pair at the end as the validation stage. We don't want to iterate through the validation set.
Also, in the original model the input / output images were captured before training, to show the random state at the very beginning. The test images themselves were different at each epoch, and they appear to be constant here.
There was a problem hiding this comment.
Thanks for pointing out. Yes we'd better select different images every epoch to save for nicer manual validation.
Regarding iterating through the validation set, we'd better keep it as the standard way of computing stats?
xihui-wu
force-pushed
the
tlautoencoder
branch
from
e0a7dac
to
1202d54
Compare
xihui-wu
force-pushed
the
tlautoencoder
branch
from
1202d54
to
1910126
Compare
No description provided.