Closed mroavi closed 1 year ago
Some of the tests for the PR task are not passing. I believe this issue is related to arithmetic overflow or underflow.
Here is a minimal working example:
using Test, OMEinsum, KaHyPar, TensorInference problems = dataset_from_artifact("uai2014")["PR"] problem_sets = [ ("Alchemy", TreeSA(ntrials = 1, niters = 5, βs = 0.1:0.1:100)), ] for (problem_set_name, optimizer) in problem_sets for (id, problem) in problems[problem_set_name] tn = TensorNetworkModel(read_model(problem); optimizer, evidence=read_evidence(problem)) solution = probability(tn) |> first |> log10 @test isapprox(solution, read_solution(problem); atol=1e-3) end end
Looking a bit deeper, it seems that the probability(tn) function does return a value equal to (exp(1396.0094457811008) * fill(1.0)). However, evaluating this operation results in an Inf value.
probability(tn)
(exp(1396.0094457811008) * fill(1.0))
Inf
Some of the tests for the PR task are not passing. I believe this issue is related to arithmetic overflow or underflow.
Here is a minimal working example: