human
Complete the below
def eppstein_matching(G, top_nodes=None):

    ''''Returns the maximum cardinality matching of the bipartite graph `G`.
    Parameters
    G : NetworkX graph
    Undirected bipartite graph
    top_nodes : container
    Container with all nodes in one bipartite node set. If not supplied
    it will be computed. But if more than one solution exists an exception
    will be raised.
    Returns
    matches : dictionary
    The matching is returned as a dictionary, `matching`, such that
    ``matching[v] == w`` if node `v` is matched to node `w`. Unmatched
    nodes do not occur as a key in mate.
    Raises
    AmbiguousSolution : Exception
    Raised if the input bipartite graph is disconnected and no container
    with all nodes in one bipartite set is provided. When determining
    the nodes in each bipartite set more than one valid solution is
    possible if the input graph is disconnected.
    Notes
    This function is implemented with David Eppstein\'s version of the algorithm
    Hopcroft--Karp algorithm (see :func:`hopcroft_karp_matching`), which
    originally appeared in the `Python Algorithms and Data Structures library
    (PADS) <http://www.ics.uci.edu/~eppstein/PADS/ABOUT-PADS.txt>`_.
    See :mod:`bipartite documentation <networkx.algorithms.bipartite>`
    for further details on how bipartite graphs are handled in NetworkX.
    See Also
    hopcroft_karp_matching'
    '''
 ... Can you provide a the Python program you requested?
assistant
#Here is the Python program you requested.
    (left, right) = bipartite_sets(G, top_nodes)
    G = nx.DiGraph(G.edges(left))
    matching = {}
    for u in G:
        for v in G[u]:
            if (v not in matching):
                matching[v] = u
                break
    while True:
        preds = {}
        unmatched = []
        pred = {u: unmatched for u in G}
        for v in matching:
            del pred[matching[v]]
        layer = list(pred)
        while (layer and (not unmatched)):
            newLayer = {}
            for u in layer:
                for v in G[u]:
                    if (v not in preds):
                        newLayer.setdefault(v, []).append(u)
            layer = []
            for v in newLayer:
                preds[v] = newLayer[v]
                if (v in matching):
                    layer.append(matching[v])
                    pred[matching[v]] = v
                else:
                    unmatched.append(v)
        if (not unmatched):
            unlayered = {}
            for u in G:
                for v in G[u]:
                    if (v not in preds):
                        unlayered[v] = None
            for key in matching.copy():
                matching[matching[key]] = key
            return matching
        def recurse(v):
            if (v in preds):
                L = preds.pop(v)
                for u in L:
                    if (u in pred):
                        pu = pred.pop(u)
                        if ((pu is unmatched) or recurse(pu)):
                            matching[v] = u
                            return True
            return False
        for v in unmatched:
            recurse(v)