ops->writable_file_ops_api = TF_WRITABLE_FILE_OPS_API;
  ops->writable_file_ops_size = TF_WRITABLE_FILE_OPS_SIZE;
  ops->read_only_memory_region_ops_abi = TF_READ_ONLY_MEMORY_REGION_OPS_ABI;
  ops->read_only_memory_region_ops_api = TF_READ_ONLY_MEMORY_REGION_OPS_API;
  ops->read_only_memory_region_ops_size = TF_READ_ONLY_MEMORY_REGION_OPS_SIZE;
}

/// Initializes a TensorFlow plugin.
///

	}

	cache := store.lock()
	defer store.unlock()

	// We should only update the in-memory cache if there were no changes
	// to the in-memory cache since the disk loading began. If there
	// were changes to the in-memory cache we should wait for the next
	// cycle until we can safely update the in-memory cache.
	//
	// An in-memory cache must be replaced only if we know for sure that the

                "type": "prometheus",
                "uid": "${datasource}"
              },
              "expr": "process_virtual_memory_bytes{app=\"istiod\"}",
              "format": "time_series",
              "instant": false,
              "intervalFactor": 2,
              "legendFormat": "Virtual Memory",
              "refId": "I",
              "step": 2
            },
            {
              "datasource": {

	input := make(chan minio.SnowballObject, 1)
	opts := minio.SnowballOptions{
		Opts:     minio.PutObjectOptions{},
		InMemory: *r.Source.Snowball.InMemory,
		Compress: *r.Source.Snowball.Compress,
		SkipErrs: *r.Source.Snowball.SkipErrs,
	}

	go func() {
		defer xioutil.SafeClose(input)

		for _, entry := range entries {

   * 2^n}, its memory usage is only {@code O(n)}. When the power set is constructed, the input set
   * is merely copied. Only as the power set is iterated are the individual subsets created, and
   * these subsets themselves occupy only a small constant amount of memory.
   *
   * @param set the set of elements to construct a power set from

//
// Returns a TF_Buffer. The memory pointed to by the result is owned by
// lib_handle. The data in the buffer will be the serialized OpList proto for
// ops defined in the library.
TF_CAPI_EXPORT extern TF_Buffer TF_GetOpList(TF_Library* lib_handle);

// Frees the memory associated with the library handle.
// Does NOT unload the library.

	info := madmin.GetProcInfo(context.Background(), globalLocalNodeName)
	return madminProcInfo.NewJSONWith(&info), nil
}

// GetMemInfoHandler - returns memory information.
func (s *peerRESTServer) GetMemInfoHandler(_ *grid.MSS) (*grid.JSON[madmin.MemInfo], *grid.RemoteErr) {
	info := madmin.GetMemInfo(context.Background(), globalLocalNodeName)

						SRDeleteOp: getSRBucketDeleteOp(globalSiteReplicationSys.isEnabled()),
					})
					writeErrorResponse(ctx, w, toAPIError(ctx, err), r.URL)
					return
				}

				// Load updated bucket metadata into memory.
				globalNotificationSys.LoadBucketMetadata(GlobalContext, bucket)

				// Make sure to add Location information here only for bucket
				w.Header().Set(xhttp.Location, pathJoin(SlashSeparator, bucket))

* Introduce node memory pressure condition to scheduler ([#25531](https://github.com/kubernetes/kubernetes/pull/25531), [@ingvagabund](https://github.com/ingvagabund))
* Fix detection of docker cgroup on RHEL ([#25907](https://github.com/kubernetes/kubernetes/pull/25907), [@ncdc](https://github.com/ncdc))

on(){return f.fireWith(this,arguments),this},fired:function(){return!!o}};return f},E.extend({Deferred:function(e){var o=[["notify","progress",E.Callbacks("memory"),E.Callbacks("memory"),2],["resolve","done",E.Callbacks("once memory"),E.Callbacks("once memory"),0,"resolved"],["reject","fail",E.Callbacks("once memory"),E.Callbacks("once memory"),1,"rejected"]],i="pending",a={state:function(){return i},always:function(){return s.done(arguments).fail(arguments),this},"catch":function(e){return a.th...