var (
	memTotalMD     = NewGaugeMD(memTotal, "Total memory on the node")
	memUsedMD      = NewGaugeMD(memUsed, "Used memory on the node")
	memUsedPercMD  = NewGaugeMD(memUsedPerc, "Used memory percentage on the node")
	memFreeMD      = NewGaugeMD(memFree, "Free memory on the node")
	memBuffersMD   = NewGaugeMD(memBuffers, "Buffers memory on the node")
	memCacheMD     = NewGaugeMD(memCache, "Cache memory on the node")

   * 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

import com.google.common.annotations.GwtIncompatible;
import com.google.common.annotations.J2ktIncompatible;
import java.io.DataOutput;
import java.io.IOException;

/**
 * An extension of {@code DataOutput} for writing to in-memory byte arrays; its methods offer
 * identical functionality but do not throw {@link IOException}.
 *
 * @author Jayaprabhakar Kadarkarai
 * @since 1.0
 */
@J2ktIncompatible
@GwtIncompatible

	rootAccess                  bool
	syncEvents                  bool
	objectMaxVersions           int64
}

const (
	cgroupV1MemLimitFile = "/sys/fs/cgroup/memory/memory.limit_in_bytes"
	cgroupV2MemLimitFile = "/sys/fs/cgroup/memory.max"
)

func cgroupMemLimit() (limit uint64) {
	buf, err := os.ReadFile(cgroupV2MemLimitFile)
	if err != nil {
		buf, err = os.ReadFile(cgroupV1MemLimitFile)
	}

 * lock, but also maximizes memory footprint. On the other extreme, one could use a single lock for
 * all tasks, which minimizes memory footprint but also minimizes concurrency. Instead of choosing
 * either of these extremes, {@code Striped} allows the user to trade between required concurrency
 * and memory footprint. For example, if a set of tasks are CPU-bound, one could easily create a

import com.google.common.annotations.GwtIncompatible;
import com.google.common.annotations.J2ktIncompatible;
import java.io.DataOutput;
import java.io.IOException;

/**
 * An extension of {@code DataOutput} for writing to in-memory byte arrays; its methods offer
 * identical functionality but do not throw {@link IOException}.
 *
 * @author Jayaprabhakar Kadarkarai
 * @since 1.0
 */
@J2ktIncompatible
@GwtIncompatible

 *       <i>deeply</i> immutable.
 * </ul>
 *
 * <h4>Performance notes</h4>
 *
 * <ul>
 *   <li>Implementations can be generally assumed to prioritize memory efficiency, then speed of
 *       access, and lastly speed of creation.
 *   <li>The {@code copyOf} methods will sometimes recognize that the actual copy operation is

//
// 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.

 * [Flipper](https://fbflipper.com/): A desktop debugging platform for mobile developers.
 * [Fresco](https://github.com/facebook/fresco): An Android library for managing images and the memory they use.
 * [Glide](https://github.com/bumptech/glide): An image loading and caching library for Android focused on smooth scrolling.

### Memory per Process { #memory-per-process }

Now, when the program loads things in memory, for example, a machine learning model in a variable, or the contents of a large file in a variable, all that **consumes a bit of the memory (RAM)** of the server.