code: def _cnn_score_variants(in_file, tensor_type, data):
      
      out_file = "%s-cnnscore.vcf.gz" % utils.splitext_plus(in_file)[0]
      if not utils.file_uptodate(out_file, in_file):
          runner = broad.runner_from_config(data["config"])
          gatk_type = runner.gatk_type()
          assert gatk_type == "gatk4", "CNN filtering requires GATK4"
          with file_transaction(data, out_file) as tx_out_file:
              params = ["-T", "CNNScoreVariants", "--variant", in_file, "--reference", dd.get_ref_file(data),
                      "--output", tx_out_file, "--input", dd.get_align_bam(data)]
              params += ["--tensor-type", tensor_type]
              runner.run_gatk(params)
      return vcfutils.bgzip_and_index(out_file, data["config"])
docs: Score variants with pre-trained CNN models.