d2 := new(dch2)
	d2[0] = mkdch()
	d2[1] = mkdch()
	return d2
}

// split reads a single demand channel and replicates its
// output onto two, which may be read at different rates.
// A process is created at first demand for an item and dies
// after the item has been sent to both outputs.

// When multiple generations of split exist, the newest
// will service requests on one channel, which is

	// Add all possible GOPATH paths into trimStrings
	// Split GOPATH depending on the OS type
	if runtime.GOOS == "windows" {
		pathSeparator = ";"
	}

	goPathList = strings.Split(goPath, pathSeparator)
	goRootList = strings.Split(goRoot, pathSeparator)
	defaultgoPathList = strings.Split(build.Default.GOPATH, pathSeparator)
	defaultgoRootList = strings.Split(build.Default.GOROOT, pathSeparator)

}

func parseClusterTopology(topology string) (clusterTopology, error) {
	if topology == "" {
		return nil, nil
	}
	out := make(clusterTopology)

	values := strings.Split(topology, ",")
	for _, v := range values {
		parts := strings.Split(v, ":")
		if len(parts) != 2 {
			return nil, fmt.Errorf("failed parsing topology mapping entry %s", v)
		}
		sourceCluster, err := parseClusterIndex(parts[0])
		if err != nil {

  std::vector<absl::string_view> splits = absl::StrSplit(subscripts, kEllipsis);
  auto index = splits[0].find(label);
  if (index != splits[0].npos) {
    return index;
  }
  if (splits.size() < 2) {
    return absl::nullopt;
  }
  index = splits[1].find(label);
  if (index != splits[1].npos) {
    return index - splits[1].length();
  }
  return absl::nullopt;
}

        // If this happens, we split the generated method into a chain of multiple.
        // The first split is always $deserializeLambda$. It processes as many lambdas as possible,
        // and if there are too many, it calls another split method $deserializeLambda0$ as its last operation.

  %2:2 = "tf.Split"(%cst, %arg0) {device = "/CPU:0"} : (tensor<i32>,  tensor<1x4xf32>) -> (tensor<1x2xf32>, tensor<1x2xf32>)
  %3:2 = "tf.Split"(%cst, %2#0) {device = "/CPU:0"} : (tensor<i32>,  tensor<1x2xf32>) -> (tensor<1x1xf32>, tensor<1x1xf32>)
  %4:2 = "tf.Split"(%cst, %2#1) {device = "/CPU:0"} : (tensor<i32>,  tensor<1x2xf32>) -> (tensor<1x1xf32>, tensor<1x1xf32>)

  // CHECK-NOT: tf_mlrt.executeop(
  // CHECK: [[device:%.*]] = tf_mlrt_tpu.get_tpu_host_device
  // CHECK: [[split:%.*]]:2 = tf_mlrt.executeop.device([[device]])
  // CHECK: tf_mlrt_tpu.compile_and_execute([[split]]#0, [[split]]#1)
  %0, %1 = "tf.Split"(%arg0, %arg1) {__op_key = 0: i32, device = "/device:CPU:0"} : (tensor<i32>, tensor<2xf32>) -> (tensor<f32>, tensor<f32>)

                final List<String> sides = split(line, "=>");
                if (sides.size() > 1) { // explicit mapping
                    if (sides.size() != 2) {
                        throw new DictionaryException("more than one explicit mapping specified on the same line");
                    }
                    final List<String> inputStrings = split(sides.get(0), ",");

	}

	// Check that we did split text sections.
	out, err = testenv.Command(t, testenv.GoToolPath(t), "tool", "nm", exe).CombinedOutput()
	if err != nil {
		t.Fatalf("nm failure: %s\n%s\n", err, string(out))
	}
	if !bytes.Contains(out, []byte("runtime.text.1")) {
		t.Errorf("runtime.text.1 not found, text section not split?")
	}

	// Result should be runnable.

                    fessConfig.getIndexFieldVersion()));
        }
        split(fessConfig.getQueryAdditionalAnalyzedFields(), ",")
                .of(stream -> stream.map(String::trim).filter(StringUtil::isNotBlank).forEach(s -> notAnalyzedFieldSet.remove(s)));
        split(fessConfig.getQueryAdditionalDefaultFields(), ",").of(stream -> stream.filter(StringUtil::isNotBlank).map(s -> {