Is there a straightforward way to go from a scipy.sparse.csr_matrix (the kind returned by an sklearn CountVectorizer) to a torch.sparse.FloatTensor?
Currently, I’m just using torch.from_numpy(X.todense()), but for large vocabularies that eats up quite a bit of RAM.