For some reason, when I open the web document, real_a and fake_b are matching, but the real_b is from another image; however in the images folder the images are correct. Does someone know why does this happen?

I understand that these two python files show two different methods to construct a model. The original n_epoch is 500 which works perfect for both python files. But if I change n_epoch to 20, only tutorial_mnist_mlp_static.py can achieve a high test accuracy (~0.97). The other file tutorial_mnist_mlp_static_2.py only get 0.47.

The models built from these two files looks the same for me (the s

According to scipy, scipy.misc.toimage()

toimage is deprecated! toimage is deprecated in SciPy 1.0.0, and will be removed in 1.2.0. Use Pillow’s Image.fromarray directly instead.

which is used on line 46 of utils/visualizer.py is now a deprecated function under the newest scipy version. As a result this co

Hi, thanks for the great code!

I wonder do you have plans to support resuming from checkpoints for classification? As we all know, in terms of training ImageNet, the training process is really long and it can be interrupted somehow, but I haven't notice any code related to "resume" in scripts/classification/train_imagenet.py.

Maybe @hetong007 ? Thanks in advance.

In config.py:
parser.add_argument('--padd_size',type=int,help='net pad size',default=0)#math.floor(opt.ker_size/2)

I'm wondering why you commented out the code for same padding to use valid padding instead? Is this important? (I checked both paper and ICCV talk, and it wasn't mentioned)

Traceback (most recent call last):
File "train.py", line 45, in
train_display_images_b = torch.stack([train_loader_b.dataset[i] for i in range(display_size)]).cuda()
File "train.py", line 45, in
train_display_images_b = torch.stack([train_loader_b.dataset[i] for i in range(display_size)]).cuda()
File "/content/MUNIT/data.py", line 119, in getitem
pat

This project is fantastic.

If anyone would be interested in trying this project out on Kubeflow let me know (kubeflow.slack.com) I'd be happy to support that by providing a Kubeflow cluster.

It would be great to understand how well the following works

Try to run the sample notebook on Kubeflow

• Deploy Kubeflow
• Navigate to JupyterHub
• Launch Jupyter

I am afraid that the image links in TUTORIAL.md are 404.
Is that because of my Internet connection or they're just not found?

I am not clear about what the iteration means. Could you explain more about it? Also, how is it related to epoch?

Thanks.