function engine = belprop_inf_engine(fg, max_iter, momentum, tol, maximize)if nargin < 2, max_iter = length(fg.G); endif nargin < 3, momentum = 0; endif nargin < 4, tol = 1e-3; endif nargin < 5, maximize = 0; endengine.fgraph = fg;engine.max_iter = max_iter;engine.momentum = momentum;engine.tol = tol;engine.maximize = maximize;% store results computed by enter_evidence herendoms = length(fg.doms);nvars = length(fg.vars);engine.marginal_domains = cell(1, ndoms);% to compute the marginal on each variable, we need to know which domain to marginalize% so we represent each domain as a bit vector, and compute its (pre-evidence) weightengine.dom_weight = [];% engine.dom_bitv = sparse(ndoms, nvars);% ns = fg.node_sizes;% for i=1:ndoms%   engine.dom_bitv(i, fg.doms{i}) = 1;%   engine.dom_weight(i) = prod(ns(fg.doms{i}));% endengine = class(engine, 'belprop_inf_engine');