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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 _run_variantcall_batch_multicore(items, regions, final_file):
 """Run variant calling on a batch of items using multiple cores. """

    batch_name = _get_batch_name(items)
    variantcaller = _get_batch_variantcaller(items)
    work_bams = [dd.get_work_bam(d) or dd.get_align_bam(d) for d in items]
    def split_fn(data):
        out = []
        for region in regions:
            region = _region_to_coords(region)
            chrom, start, end = region
            region_str = "_".join(str(x) for x in region)
            out_file = os.path.join(dd.get_work_dir(items[0]), variantcaller, chrom,
                                    "%s-%s.vcf.gz" % (batch_name, region_str))
            out.append((region, work_bams, out_file))
        return final_file, out
    parallel = {"type": "local", "num_jobs": dd.get_num_cores(items[0]), "cores_per_job": 1}
    run_parallel = dmulti.runner(parallel, items[0]["config"])
    to_run = copy.deepcopy(items[0])
    to_run["sam_ref"] = dd.get_ref_file(to_run)
    to_run["group_orig"] = items
    parallel_split_combine([[to_run]], split_fn, run_parallel,
                           "variantcall_sample", "concat_variant_files",
                           "vrn_file", ["region", "sam_ref", "config"])
    return final_file