The dataset is a 100K*100K adjacent matrix which represents the relationship of network nodes.The input is some rows(mini-batch) of the adjacent matrix, just like [0 0 0 0 0 0 1 0…… 0 0 0 1 0 0 0 0].I want to input the batch to a fully connected layers.If the tensor is dense, it would use too much memory.
I have read the doc of torch.sparse, but I’m confused to use torch.sparse.FloatTensor as input.just like conventional tensor?And , it doesn’t support cuda now, does it?