GPU Support for rascaline

[Luthaf]

From @clecust in #270, split into it's own issue

GPU Support for rascaline.torch.LodeSphericalExpansion

I encountered an issue when attempting to use rascaline.torch.LodeSphericalExpansion() with GPU input data. It appears that the computation primarily occurs on the CPU, and the results (x) are displayed on the CPU as well. Below is a snippet of my main code:

# lode
LR_HYPERS = {
    "cutoff": 4.0,
    "max_radial": 1,
    "max_angular": 1,
    "atomic_gaussian_width": 2.0,
    "center_atom_weight": 0.0,
    "radial_basis": {"Gto": {}},
    "potential_exponent": 1,
}
lr = rascaline.torch.LodeSphericalExpansion(**LR_HYPERS).to("cuda")
# data
sys = rascaline.torch.System(
    torch.tensor(atom0.numbers, dtype=torch.int64).to("cuda"),
    pos.to("cuda"),
    cell.to("cuda"),
)
# compute
lrv = lr.forward([sys, sys], gradients=["positions"])
# get block
lrvp = lr.keys_to_samples("species_center")
lrvp = lrvp.components_to_properties(["spherical_harmonics_m"])
lrvp = lrvp.keys_to_properties(["species_neighbor", "spherical_harmonics_l"])
x = lrvp.block().values