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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def construct_tpb_graph(experiments: TomographyExperiment):
 """ Construct a graph where an edge signifies two experiments are diagonal in a TPB. """

    g = nx.Graph()
    for expt in experiments:
        assert len(expt) == 1, 'already grouped?'
        expt = expt[0]

        if expt not in g:
            g.add_node(expt, count=1)
        else:
            g.nodes[expt]['count'] += 1

    for expt1, expt2 in itertools.combinations(experiments, r=2):
        expt1 = expt1[0]
        expt2 = expt2[0]

        if expt1 == expt2:
            continue

        max_weight_in = _max_weight_state([expt1.in_state, expt2.in_state])
        max_weight_out = _max_weight_operator([expt1.out_operator, expt2.out_operator])
        if max_weight_in is not None and max_weight_out is not None:
            g.add_edge(expt1, expt2)

    return g