*       and virtual memory, this is not a problem - because it is mapped read-only, the kernel
   *       can always page it to disk "for free". However, on systems where killing processes
   *       happens all the time in normal conditions (i.e., android) the OS must make a tradeoff

#include "tensorflow/c/eager/c_api.h"

#include <algorithm>
#include <cstddef>
#include <cstdint>
#include <memory>
#include <string>
#include <utility>
#include <vector>

#include "absl/algorithm/container.h"
#include "absl/memory/memory.h"
#include "tensorflow/c/c_api.h"
#include "tensorflow/c/c_api_internal.h"
#include "tensorflow/c/eager/abstract_tensor_handle.h"

 * [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.

		if len(dui.BucketsUsage) > 0 {
			internalLogOnceIf(GlobalContext, fmt.Errorf("unable to retrieve usage information for bucket: %s, relying on older value cached in-memory: err(%v)", bucket, err), "bucket-usage-cache-"+bucket)
		} else {

#FESS_JAVA_OPTS="$FESS_JAVA_OPTS -Djavax.net.ssl.trustStorePassword=changeit"

# min and max heap sizes should be set to the same value to avoid
# stop-the-world GC pauses during resize, and so that we can lock the
# heap in memory on startup to prevent any of it from being swapped
# out.
FESS_JAVA_OPTS="$FESS_JAVA_OPTS -Xms${FESS_MIN_MEM}"
FESS_JAVA_OPTS="$FESS_JAVA_OPTS -Xmx${FESS_MAX_MEM}"

==============================================================================*/

#include "tensorflow/c/eager/parallel_device/parallel_device_lib.h"

#include <string>
#include <utility>

#include "absl/memory/memory.h"
#include "absl/status/status.h"
#include "absl/strings/str_cat.h"
#include "absl/types/optional.h"
#include "absl/types/span.h"
#include "tensorflow/c/eager/c_api.h"

 *  Fix: Immediately update the connection's flow control window instead of waiting for the
    receiving stream to process it.

    This change may increase OkHttp's memory use for applications that make many concurrent HTTP
    calls and that can receive data faster than they can process it. Previously, OkHttp limited

   * interned, and so does not prevent these instances from being garbage-collected. This most
   * likely does not perform as well as {@link #newStrongInterner}, but is the best alternative when
   * the memory usage of that implementation is unacceptable.
   */
  @GwtIncompatible("java.lang.ref.WeakReference")
  public static <E> Interner<E> newWeakInterner() {
    return newBuilder().weak().build();
  }

 * <p>
 * Unlike a cache, this session data is not subject to purging. For this same reason, session data should also not be
 * abused as a cache (i.e. for storing values that can be re-calculated) to avoid memory exhaustion.
 * <p>
 * <strong>Note:</strong> Actual implementations must be thread-safe.
 *
 * @see Session#getData()
 * @since 4.0.0
 */
@Experimental
@ThreadSafe
@Provider
public interface SessionData {

 * offering expected O(n + k log k) performance (worst case O(n log k)) for n calls to {@link
 * #offer} and a call to {@link #topK}, with O(k) memory. In comparison, quickselect has the same
 * asymptotics but requires O(n) memory, and a {@code PriorityQueue} implementation takes O(n log
 * k). In benchmarks, this implementation performs at least as well as either implementation, and