*
   * @param loader the cache loader used to obtain new values
   * @return a cache having the requested features
   */
  public <K1 extends K, V1 extends V> LoadingCache<K1, V1> build(
      CacheLoader<? super K1, V1> loader) {
    checkWeightWithWeigher();
    return new LocalCache.LocalLoadingCache<>(this, loader);
  }

  /**

    build_setting_default = if_oss(True, False),
    visibility = ["//visibility:private"],
)

# Setting to use when loading kernels dynamically
config_setting(
    name = "dynamic_loaded_kernels",
    define_values = {
        "dynamic_loaded_kernels": "true",
        "framework_shared_object": "true",
    },
    visibility = ["//visibility:public"],
)

config_setting(
    name = "using_rocm_hipcc",

	//
	// An in-memory cache must be replaced only if we know for sure that the
	// values loaded from disk are not stale. They might be stale if the
	// cached.updatedAt is more recent than the refresh cycle began.
	if cache.updatedAt.Before(loadedAt) {
		// No one has updated anything since the config was loaded,
		// so we just replace whatever is on the disk into memory.
		cache.iamGroupPolicyMap = newCache.iamGroupPolicyMap

//
// Each filesystem implementation can be provided by DSOs, so we provide the
// `--dsos` flag to specify a list of shared objects to be loaded in order.
// If the flag is not used, no shared objects are loaded.
//
// Every filesystem provides support for accessing URIs of form
// `[<scheme>://]<path>` where `<scheme>` is optional (if missing, we are

============================\n   */\n\n  const NAME               = 'CardRefresh'\n  const DATA_KEY           = 'lte.cardrefresh'\n  const EVENT_KEY          = `.${DATA_KEY}`\n  const JQUERY_NO_CONFLICT = $.fn[NAME]\n\n  const Event = {\n    LOADED: `loaded${EVENT_KEY}`,\n    OVERLAY_ADDED: `overlay.added${EVENT_KEY}`,\n    OVERLAY_REMOVED: `overlay.removed${EVENT_KEY}`,\n  }\n\n  const ClassName = {\n    CARD: 'card',\n  }\n\n  const Selector = {\n    CARD: `.${ClassName.CARD}`,\n    DATA_REFRESH:...

/// TensorFlow checks that the plugin supplies all mandatory operations and
/// then copies these tables to a different memory location, marking the new
/// operation tables as read-only. Once a plugin is loaded, none of these
/// operation pointers may change.
///
/// There are 4 function tables: one for each of the 3 file objects in
/// TensorFlow (i.e., `RandomAccessFile`, `WritableFile`,

                }
                return true;
            }, OptionalThing.empty());
            response.flushBuffer();
            if (logger.isDebugEnabled()) {
                logger.debug("Loaded {} docs", count);
            }
        } catch (final InvalidQueryException | ResultOffsetExceededException e) {
            if (logger.isDebugEnabled()) {

//    the SavedModel.
// - `graph` must be a graph newly allocated with TF_NewGraph().
//
// If successful, populates `graph` with the contents of the Graph and
// `meta_graph_def` with the MetaGraphDef of the loaded model.
TF_CAPI_EXPORT extern TF_Session* TF_LoadSessionFromSavedModel(
    const TF_SessionOptions* session_options, const TF_Buffer* run_options,
    const char* export_dir, const char* const* tags, int tags_len,

	if bucket != path.Clean(resource[1:]) {
		writeErrorResponse(ctx, w, errorCodes.ToAPIErr(ErrMethodNotAllowed), r.URL)
		return
	}

	// Here the parameter is the size of the form data that should
	// be loaded in memory, the remaining being put in temporary files.
	mp, err := r.MultipartReader()
	if err != nil {
		apiErr := errorCodes.ToAPIErr(ErrMalformedPOSTRequest)

    @CheckForNull volatile Thread thread;
    @CheckForNull volatile Waiter next;

    /**
     * Constructor for the TOMBSTONE, avoids use of ATOMIC_HELPER in case this class is loaded
     * before the ATOMIC_HELPER. Apparently this is possible on some android platforms.
     */
    Waiter(boolean unused) {}

    Waiter() {