if (ret) ret = attr_value->ParseFromArray(buffer->data, buffer->length);
  TF_DeleteBuffer(buffer);
  return ret;
}

std::vector<std::pair<string, string>> GetGradDefs(
    const tensorflow::GraphDef& graph_def) {
  std::vector<std::pair<string, string>> grads;
  for (const tensorflow::GradientDef& grad : graph_def.library().gradient()) {
    grads.emplace_back(grad.function_name(), grad.gradient_func());
  }

    return (existingCounter == null) ? 0 : existingCounter.get();
  }

  /**
   * {@inheritDoc}
   *
   * <p>If the data in the multiset is modified by any other threads during this method, it is
   * undefined which (if any) of these modifications will be reflected in the result.
   */
  @Override
  public int size() {
    long sum = 0L;
    for (AtomicInteger value : countMap.values()) {

that may not be expressible using a single hardware instruction.
It implements these forms as multiple instructions, often using the <code>R11</code> register
to hold temporary values.
Hand-written assembly can use <code>R11</code>, but doing so requires
being sure that the linker is not also using it to implement any of the other
instructions in the function.
</p>

<p>

	testCases := []struct {
		inputConfig            string
		objectName             string
		objectTags             string
		objectModTime          time.Time
		isDelMarker            bool
		hasManyVersions        bool
		expectedAction         Action
		isNoncurrent           bool
		objectSuccessorModTime time.Time
		versionID              string
	}{

#     rbe_win_clang:  Options specific to compiling using Clang.
#
#     rbe_linux_cpu:                  RBE options to build with only CPU support.
#     rbe_linux_cuda:                 RBE options to build with GPU support using clang.
#     rbe_linux_cuda_nvcc:            RBE options to build with GPU support using nvcc.
#
# Embedded Linux options (experimental and only tested with TFLite build yet)

   * See [ConnectionPool].
   */
  open fun dnsStart(
    call: Call,
    domainName: String,
  ) {
  }

  /**
   * Invoked immediately after a DNS lookup.
   *
   * This method is invoked after [dnsStart].
   */
  open fun dnsEnd(
    call: Call,
    domainName: String,
    inetAddressList: List<@JvmSuppressWildcards InetAddress>,
  ) {
  }

  /**

}

class FunctionErrorInjectionPass : public tensorflow::FunctionOptimizationPass {
 public:
  FunctionErrorInjectionPass(string error_node, string error_device)
      : error_node_(error_node), error_device_(error_device) {}
  absl::Status Run(const std::string& function_name,
                   const tensorflow::DeviceSet& device_set,
                   const tensorflow::ConfigProto& config_proto,

- Introduces a new metric: `admission_webhook_request_total` with the following labels: name (string) - the webhook name, type (string) - the admission type, operation (string) - the requested verb, code (int) - the HTTP status code, rejected (bool) - whether the request was rejected, namespace (string) - the namespace of the requested resource. ([#103162](https://github.com/kubernetes/kubernetes/pull/103162), [@rmoriar1](https://github.com/rmoriar1))...

   * ThreadLocal is usually implemented with a WeakReference, which can have negative performance
   * properties; for example, calling WeakReference.get() on Android will block during an
   * otherwise-concurrent GC cycle.
   */
  private static final class TaskNonReentrantExecutor extends AtomicReference<RunningState>
      implements Executor, Runnable {

    /**

func removeStandardStorageClass(metadata map[string]string) map[string]string {
	if metadata[xhttp.AmzStorageClass] == storageclass.STANDARD {
		delete(metadata, xhttp.AmzStorageClass)
	}
	return metadata
}

// cleanMetadataKeys takes keyNames to be filtered
// and returns a new map with all the entries with keyNames removed.
func cleanMetadataKeys(metadata map[string]string, keyNames ...string) map[string]string {