Inference Does Not Work for Non-Tree Factor Graphs about fglib HOT 6 OPEN

In the docstring for inference.sum_product it says that the algorithm only works for tree graphs. The algorithm for non-trees is different - try inference.loopy_belief_propagation. However be warned that this algorithm is non-exact, all message-passing algorithms on a loopy graph are non exact!

from fglib.

Thanks for the response.
I tried inference.loopy_belief_propagation. However, I've run into another error.
Is model what I think it is? An arbitrary structured graph?

# Perform loopy-belief propagation on factor graph
# and request belief of variable node x3
belief = inference.loopy_belief_propagation(fg, 10, (x3,))

The terminal output is shown below.

Traceback (most recent call last):
  File "fglib_example.py", line 39, in <module>
    belief = inference.loopy_belief_propagation(fg, 10, (x3,))
  File "/home/bradley/.local/lib/python3.6/site-packages/fglib/inference.py", line 165, in loopy_belief_propagation
    return _schedule(model, 'spa', iterations, query_node, order)
  File "/home/bradley/.local/lib/python3.6/site-packages/fglib/inference.py", line 205, in _schedule
    b[n].append(n.belief(model))
  File "/home/bradley/.local/lib/python3.6/site-packages/fglib/nodes.py", line 140, in belief
    belief *= self.graph[n][self]['object'].get_message(n, self)
TypeError: unsupported operand type(s) for *=: 'NoneType' and 'NoneType'

from fglib.

@studentbrad did you ever resolve this? I have the same issue for loopy graph when trying to compute marginals

from fglib.

@goodyguts, for my loopy graph I tried:

score_node_list = [n for (n, attr) in M.nodes(data=True) if attr["type"] == "vn"]
belief = fg_lib.inference.loopy_belief_propagation(M,iterations=100, query_node = score_node_list)

and runs without error, but no marginals. Can you comment please thx!

from fglib.

@mercicle, I wasn't able to get this implementation of loopy belief propagation working.
Of course I appreciate the authors work, but there are other tools for doing the same loopy belief on a structured graph.

from fglib.

@mercicle, I wasn't able to get this implementation of loopy belief propagation working.
Of course I appreciate the authors work, but there are other tools for doing the same loopy belief on a structured graph

Could you please let us know what tool you finally used for the loopy BP? Thanks!

from fglib.