The following code gives an error that the dimensions for the matrices in spmm do not match up
def sgc_precompute(features, adj, degree):
    t = perf_counter()
    for i in range(degree):
        features = torch.spmm(adj, torch.transpose(features, 1,0))
    precompute_time = perf_counter()-t
    return torch.transpose(features, 1, 0), precompute_time

I’m confused because the following code works. Notice that the only change was that I explicitly set features to torch.transpose(features, 1,0) and then passed features as an argument to spmm, instead of just passing in torch.transpose(features, 1,0) directly
def sgc_precompute(features, adj, degree):
    t = perf_counter()
    features = torch.transpose(features, 1, 0)
    for i in range(degree):
        features = torch.spmm(adj, features)
    precompute_time = perf_counter()-t
    return torch.transpose(features, 1, 0), precompute_time