def __init__(self, model: GraphModel, props: Dict[(str, str)]):
    self._edges: List[List[EdgeProp]] = []
    self._maxdiff = 0.0
    self._iters = 0
    self._sentMessages = []
    self._oldBeliefsV: List[LDFactor] = []
    self._old_beliefs_f: List[LDFactor] = []
    self._update_seq = []
    self.model = model
    self.factors = [LDFactor.from_inferlo_factor(DiscreteFactor.from_factor(f)) for f in model.get_factors()]
    self.nrVars = model.num_variables
    self.nrFactors = len(self.factors)
    self.nbV: List[List[Neighbor]] = [[] for _ in range(self.nrVars)]
    self.nbF: List[List[Neighbor]] = [[] for _ in range(self.nrFactors)]
    for factor_id in range(len(self.factors)):
        factor = self.factors[factor_id]
        for var_iter_index in range(len(factor.var_idx)):
            var_id = factor.var_idx[var_iter_index]
            nbv_len = len(self.nbV[var_id])
            nbf_len = len(self.nbF[factor_id])
            assert (var_iter_index == nbf_len)
            self.nbV[var_id].append(Neighbor(iter=nbv_len, node=factor_id, dual=nbf_len))
            self.nbF[factor_id].append(Neighbor(iter=nbf_len, node=var_id, dual=nbv_len))
    self.logdomain = bool(int(props.get('logdomain', 0)))
    self.updates = props['updates']
    self.inference = props.get('inference', 'SUMPROD')
    self.verbose = int(props.get('verbose', 0))
    self.damping = float(props.get('damping', 0.0))
    self.maxiter = int(props.get('maxiter', 10000))
    self.maxtime = float(props.get('maxtime', np.inf))
    self.tol = float(props['tol'])
    self._construct()
def __init__(self, model: GraphModel, props: Dict[(str, str)]):
    self._edges: List[List[EdgeProp]] = []
    self._maxdiff = 0.0
    self._iters = 0
    self._sentMessages = []
    self._oldBeliefsV: List[LDFactor] = []
    self._old_beliefs_f: List[LDFactor] = []
    self._update_seq = []
    self.model = model
    self.factors = [LDFactor.from_inferlo_factor(DiscreteFactor.from_factor(f)) for f in model.get_factors()]
    self.nrVars = model.num_variables
    self.nrFactors = len(self.factors)
    self.nbV: List[List[Neighbor]] = [[] for _ in range(self.nrVars)]
    self.nbF: List[List[Neighbor]] = [[] for _ in range(self.nrFactors)]
    for factor_id in range(len(self.factors)):
        factor = self.factors[factor_id]
        for var_iter_index in range(len(factor.var_idx)):
            var_id = factor.var_idx[var_iter_index]
            nbv_len = len(self.nbV[var_id])
            nbf_len = len(self.nbF[factor_id])
            assert (var_iter_index == nbf_len)
            self.nbV[var_id].append(Neighbor(iter=nbv_len, node=factor_id, dual=nbf_len))
            self.nbF[factor_id].append(Neighbor(iter=nbf_len, node=var_id, dual=nbv_len))
    self.logdomain = bool(int(props.get('logdomain', 0)))
    self.updates = props['updates']
    self.inference = props.get('inference', 'SUMPROD')
    self.verbose = int(props.get('verbose', 0))
    self.damping = float(props.get('damping', 0.0))
    self.maxiter = int(props.get('maxiter', 10000))
    self.maxtime = float(props.get('maxtime', np.inf))
    self.tol = float(props['tol'])
    self._construct()