human
Here's a good function header given the following:
I wrote the below code

    def local_recursive_function(list_opt, out, optimized_vars, depth):
        if (not getattr(out, 'owner', None)):
            return ([out], optimized_vars)
        node = out.owner
        if hasattr(node, 'fgraph'):
            return (node.outputs, optimized_vars)
        for (idx, inp) in enumerate(node.inputs):
            if (inp in optimized_vars):
                nw_in = optimized_vars[inp]
            elif inp.owner:
                (outs, optimized_vars) = local_recursive_function(list_opt, inp, optimized_vars, (depth + 1))
                for (k, v) in zip(inp.owner.outputs, outs):
                    optimized_vars[k] = v
                nw_in = outs[inp.owner.outputs.index(inp)]
            else:
                nw_in = inp
                optimized_vars[inp] = inp
            node.inputs[idx] = nw_in
        results = node.outputs
        for opt in list_opt:
            ret = opt.transform(node)
            if ((ret is not False) and (ret is not None)):
                assert (len(ret) == len(node.outputs)), opt
                for (k, v) in zip(node.outputs, ret):
                    optimized_vars[k] = v
                results = ret
                if ret[0].owner:
                    node = out.owner
                else:
                    break
        return (results, optimized_vars)
    if out.owner:
        out_index = out.owner.outputs.index(out)
    else:
        out_index = 0
    (final_outs, optimized_nodes) = local_recursive_function(list_optimizations, out, {}, 0)
    return final_outs[out_index]

What's a good function header?
assistant
#Here's a good function header.

def pre_greedy_local_optimizer(list_optimizations, out):