Training on sparse tensors

I want to train my neural network on sparse tensors that I’ve made by using:
pytorch sparse tensors
But while trying to propagate my sparse tensors into the CNN I get this error:
RuntimeError: Input type (torch.cuda.sparse.FloatTensor) and weight type (torch.cuda.FloatTensor) should be the same

What should I change in my network in order to be able to train on sparse tensors?

Thank you

I read and learn a lot from your comments here @ptrblck, maybe you could help me here?

Thank you!

Hello @nirzaa,

We currently don’t have support for convolutions for sparse inputs. Could I kindly ask you to open a feature request on with your intended use case (model, application area, dataset)? Also, please include details on the intended semantics if you want the input to be treated differently if it has a sparse layout vs. a regular strided layout.


the link to the issue I opened on github is here:
link to the issue on github

Thank you very much

This library from facebookresearch at least at first glance seems to implement the desired features for basic CNNs. GitHub - facebookresearch/SparseConvNet: Submanifold sparse convolutional networks