I am trying to make a layered nested network by following command lines similar to the example in the instruction (except using nested stochastic blockmodel):

 LayerState = minimize_nested_blockmodel_dl(g, layers=True,                                            state_args=dict(ec=g.edge_properties["Timestamp"], layers=True), verbose=True)
bs        = LayerState.get_bs()
bs += [np.zeros(1)] * (L - len(bs))
LayerState = LayerState.copy(bs=bs, sampling=True)
dS, nmoves = LayerState.mcmc_sweep(niter=500)

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/lib/python3/dist-packages/graph_tool/inference/nested_blockmodel.py", line 577, in mcmc_sweep
    return self._h_sweep(lambda s, **a: s.mcmc_sweep(**a), c=c, **kwargs)
  File "/usr/lib/python3/dist-packages/graph_tool/inference/nested_blockmodel.py", line 500, in _h_sweep
    get_entropy_args(eargs))
  File "/usr/lib/python3/dist-packages/graph_tool/inference/blockmodel.py", line 698, in _couple_state
    self._state.couple_state(state._state, entropy_args)
AttributeError: 'graph_tool::Layers<graph_tool::BlockState<boost::u' object has no attribute 'couple_state'

Any comment why it occurred or suggestion about how could it be fixed ?

Thanks.