Closed kwhuang88228 closed 2 years ago
Hi, Thank you for sharing that! Based on the info that seems to be a bug, I've started now several experiments that seek to identify the source of the problem and hope to get back to you in couple days with more info!
Loading training set...
Num images: [NUM]
I want to make sure you have the training data correctly. As a further indication, you should have a file reals.png
, would you be able to upload it? Thanks!
Thank you for looking into this! I have Num images: 20004. And this is my reals.png
.
Thanks! I had a small bug in the PyTorch initialization of the mapping network's weight parameters (see e98744879e1a01da7200a9d2cd38c1f457200600), that should both resolve the same-images issue, and more importantly, I expect it to speed up the model's learning substantially.
Please consider retraining a new model from scratch (so that the weights get initialized correctly) to achieve the improved learning. I will run too further experiments now to verify it indeed gets resolved and get back to you!
python run_network.py --train --gpus 0 --batch-gpu 1 --ganformer-default --expname ffhq-scratch-new --dataset ffhq
Alright I tested the model and things look good!
Can also confirm PyTorch model is no longer generating the same images. Thank you!
Hi, I'm getting the same output image samples (see below) when I train the PyTorch implementation on FFHQ from scratch. The only changes I made (due to some memory issues mentioned in #33) were adding
--batch-gpu 1
and removing saving attention map functionality (commenting out pytorch_version/training/visualize.py lines 167-206).python run_network.py --train --gpus 0 --batch-gpu 1 --ganformer-default --expname ffhq-scratch --dataset ffhq