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Curvlearn, a Tensorflow based non-Euclidean deep learning framework.

License: Apache License 2.0

Python 100.00%
non-euclidean-deep-learning geometric-deep-learning tensorflow hyperbolic

curvature-learning-framework's Issues

Help needed

Hello, I'm trying to implement HyperML on my data using the manifold PoincareBall. I'm not familiar with TensorFlow so it has been a little hard for me to understand if I need to change some parameters in order for the model to work well.
Until now, I've made these changes:
image
I tried to implement the model but it got stuck on step 1000 and the HR metric doesn't print.
You can see that below:
image

I am doing something wrong?
Another issue relates to the results. When I get to the end of the training, how can I check if my model worked and get some recommendations for a specific user?

Thanks in advance!

version of torch

hi!i'm surprised when I find this package, but most recommendation system codes are pytorch version, so do you know if there are other torch vertion of curvature.

gpu训练

使用gpu训练的时候,显存有使用,但是gpu没有使用?使用的是CUDA_VISIBLE_DEVICES=0 python examples/hgcn/train.py 运行的hgcn. example

How can i run with the product of manifolds

Hi teams, thank you for the quick support.
I am trying to run these models with the product of manifolds. For example, with HGCN, in the config.py, I used manifold with Product(Euclidean(), Stereographic()).
But it seems doesn't work and has a bug.
Did I do any wrong?
Thank you so much.

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