def operation_mode():
# Set to share the coordinate_manager by default
ME.set_sparse_tensor_operation_mode(
ME.SparseTensorOperationMode.SHARE_COORDINATE_MANAGER)
print(ME.sparse_tensor_operation_mode())
coords0, feats0 = to_sparse_coo(data_batch_0)
coords0, feats0 = ME.utils.sparse_collate(coords=[coords0], feats=[feats0])
coords1, feats1 = to_sparse_coo(data_batch_1)
coords1, feats1 = ME.utils.sparse_collate(coords=[coords1], feats=[feats1])
for _ in range(2):
# sparse tensors
A = ME.SparseTensor(coordinates=coords0, features=feats0)
B = ME.SparseTensor(
coordinates=coords1,
features=feats1,
# coords_manager=A.coordinate_manager, No need to feed the coordinate_manager
)
C = A + B
# When done using it for forward and backward, you must cleanup the coords man
ME.clear_global_coordinate_manager()
