// TensorHandles we've computed into a single parallel TensorHandle.
  std::vector<std::unique_ptr<ParallelTensor>> per_device_outputs;
  per_device_outputs.reserve(first_op_output_count);
  for (int i = 0; i < first_op_output_count; ++i) {
    std::vector<TensorHandlePtr> components;
    components.reserve(underlying_devices_.size());
    for (int j = 0; j < underlying_devices_.size(); ++j) {

	Logger                   logger.Interface
	NowFunc                  func() time.Time
	CreateBatchSize          int
}

// Open initialize db session based on dialector
func Open(dialector Dialector, opts ...Option) (db *DB, err error) {
	config := &Config{}

	sort.Slice(opts, func(i, j int) bool {
		_, isConfig := opts[i].(*Config)
		_, isConfig2 := opts[j].(*Config)
		return isConfig && !isConfig2
	})

    assertThat(e.getStackTrace()[index - 1].getMethodName()).isEqualTo("get");
  }

  private static int findStackFrame(ExecutionException e, String clazz, String method) {
    StackTraceElement[] elements = e.getStackTrace();
    for (int i = 0; i < elements.length; i++) {
      StackTraceElement element = elements[i];
      if (element.getClassName().equals(clazz) && element.getMethodName().equals(method)) {

  public Object measureSize() {
    list = impl.newExecutionList();
    for (int i = 0; i < numListeners; i++) {
      list.add(listener, directExecutor());
    }
    return list.getImpl();
  }

  @Benchmark
  int addThenExecute_singleThreaded(int reps) {
    int returnValue = 0;
    for (int i = 0; i < reps; i++) {
      list = impl.newExecutionList();

func (h *HTTPRangeSpec) ToHeader() (string, error) {
	if h == nil {
		return "", nil
	}
	start := strconv.Itoa(int(h.Start))
	end := strconv.Itoa(int(h.End))
	switch {
	case h.Start >= 0 && h.End >= 0:
		if h.Start > h.End {
			return "", errInvalidRange
		}
	case h.IsSuffixLength:
		end = strconv.Itoa(int(h.Start * -1))
		start = ""
	case h.Start > -1:
		end = ""
	default:

    private static int id = 0;
    private static final Logger log = LoggerFactory.getLogger(Transport.class);


    /**
     * Read bytes from the input stream into a buffer
     * 
     * @param in
     * @param b
     * @param off
     * @param len
     * @return number of bytes read
     * @throws IOException
     */

But when you declare them with Python types (in the example above, as `int`), they are converted to that type and validated against it.

All the same process that applied for path parameters also applies for query parameters:

* Editor support (obviously)
* Data <abbr title="converting the string that comes from an HTTP request into Python data">"parsing"</abbr>
* Data validation
* Automatic documentation

## Defaults

  if len(version_segments) == 2:
    version_segments.append('0')
  for seg in version_segments:
    if not seg.isdigit():
      return None

  version_str = ''.join(['%03d' % int(seg) for seg in version_segments])
  return int(version_str)


def retrieve_bazel_version():
  """Retrieve installed bazel version (or bazelisk).

  Returns:
    The bazel version detected.
  """

   * @param hc the hash code holder
   * @param wasUncontended false if CAS failed before call
   */
  final void retryUpdate(long x, @CheckForNull int[] hc, boolean wasUncontended) {
    int h;
    if (hc == null) {
      threadHashCode.set(hc = new int[1]); // Initialize randomly
      int r = rng.nextInt(); // Avoid zero to allow xorShift rehash
      h = hc[0] = (r == 0) ? 1 : r;
    } else h = hc[0];

		APICode: "kms:NotSupported",
		Err:     "requested functionality is not supported",
	}
)

// Error is a KMS error that can be translated into an S3 API error.
//
// It does not implement the standard error Unwrap interface for
// better error log messages.
type Error struct {
	Code    int    // The HTTP status code returned to the client
	APICode string // The API error code identifying the error