本文整理了Java中org.nd4j.linalg.factory.Nd4j.getAffinityManager()方法的一些代码示例，展示了Nd4j.getAffinityManager()的具体用法。这些代码示例主要来源于Github/Stackoverflow/Maven等平台，是从一些精选项目中提取出来的代码，具有较强的参考意义，能在一定程度帮忙到你。Nd4j.getAffinityManager()方法的具体详情如下：
包路径：org.nd4j.linalg.factory.Nd4j
类名称：Nd4j
方法名：getAffinityManager

Nd4j.getAffinityManager介绍

暂无

代码示例

代码示例来源：origin: deeplearning4j/nd4j

public DeviceLocal() {
  int numDevices = Nd4j.getAffinityManager().getNumberOfDevices();
  for (int i = 0; i < numDevices; i++) {
    locksMap.add(new ReentrantReadWriteLock());
  }
}

代码示例来源：origin: deeplearning4j/nd4j

/**
   * This method removes object stored for current device
   *
   */
  public void clear() {
    int deviceId = Nd4j.getAffinityManager().getDeviceForCurrentThread();
    try {
      locksMap.get(deviceId).writeLock().lock();
      backingMap.remove(deviceId);
    } finally {
      locksMap.get(deviceId).writeLock().unlock();
    }
  }
}

代码示例来源：origin: deeplearning4j/nd4j

private PerformanceTracker() {
  // we put in initial holders, one per device
  val nd = Nd4j.getAffinityManager().getNumberOfDevices();
  for (int e = 0; e < nd; e++) {
    bandwidth.put(e, new AveragingTransactionsHolder());
    operations.put(e, new AveragingTransactionsHolder());
  }
}

代码示例来源：origin: deeplearning4j/nd4j

/**
 * This method sets object for current device
 *
 * @param object
 */
public void set(T object) {
  set(Nd4j.getAffinityManager().getDeviceForCurrentThread(), object);
}

代码示例来源：origin: deeplearning4j/nd4j

/**
   * This method duplicates array, and stores it to all devices
   *
   * @param array
   */
  public void broadcast(INDArray array) {
    if (array == null)
      return;

    Nd4j.getExecutioner().commit();

    int numDevices = Nd4j.getAffinityManager().getNumberOfDevices();
    for (int i = 0; i < numDevices; i++) {
      // if current thread equal to this device - we just save it, without duplication
      if (Nd4j.getAffinityManager().getDeviceForCurrentThread() == i) {
        set(i, array);
      } else {
        set(i, Nd4j.getAffinityManager().replicateToDevice(i, array));
      }

    }
  }
}

代码示例来源：origin: deeplearning4j/nd4j

/**
 * This method returns object local to current deviceId
 *
 * @return
 */
@Nullable
public T get() {
  return get(Nd4j.getAffinityManager().getDeviceForCurrentThread());
}

代码示例来源：origin: deeplearning4j/dl4j-examples

public DataSet convertDataSet(int num)  {
  int batchNumCount = 0;
  List<DataSet> dataSets = new ArrayList();
  FileSystem fs = CommonUtils.openHdfsConnect();
  try {
    while (batchNumCount != num && fileIterator.hasNext()) {
      ++ batchNumCount;
      String fullPath = fileIterator.next();
      Writable labelText = new Text(FilenameUtils.getBaseName((new File(fullPath)).getParent()));
      INDArray features = null;
      INDArray label =  Nd4j.zeros(1, labels.size()).putScalar(new int[]{0, labels.indexOf(labelText)}, 1);
      InputStream imageios = fs.open(new Path(fullPath));
      features = asMatrix(imageios);
      imageios.close();
      Nd4j.getAffinityManager().tagLocation(features, AffinityManager.Location.HOST);
      dataSets.add(new DataSet(features, label));
    }
  } catch (Exception e) {
    throw  new RuntimeException(e.getCause());
  } finally {
    CommonUtils.closeHdfsConnect(fs);
  }
  if (dataSets.size() == 0) {
    return new DataSet();
  } else {
    DataSet result = DataSet.merge( dataSets );
    return result;
  }
}

代码示例来源：origin: deeplearning4j/nd4j

if (isDebug.get())
  log.info("Workspace [{}] device_{}, current cycle: {}; max cycle: {}", id,
          Nd4j.getAffinityManager().getDeviceForCurrentThread(), cycleAllocations.get(),
          maxCycle.get());

代码示例来源：origin: deeplearning4j/nd4j

/**
 * Setup the given byte buffer
 * for serialization (note that this is for uncompressed INDArrays)
 * 4 bytes int for rank
 * 4 bytes for data opType
 * shape buffer
 * data buffer
 *
 * @param arr the array to setup
 * @param allocated the byte buffer to setup
 * @param rewind whether to rewind the byte buffer or nt
 */
public static void doByteBufferPutUnCompressed(INDArray arr, ByteBuffer allocated, boolean rewind) {
  // ensure we send data to host memory
  Nd4j.getExecutioner().commit();
  Nd4j.getAffinityManager().ensureLocation(arr, AffinityManager.Location.HOST);
  ByteBuffer buffer = arr.data().pointer().asByteBuffer().order(ByteOrder.nativeOrder());
  ByteBuffer shapeBuffer = arr.shapeInfoDataBuffer().pointer().asByteBuffer().order(ByteOrder.nativeOrder());
  //2 four byte ints at the beginning
  allocated.putInt(arr.rank());
  //put data opType next so its self describing
  allocated.putInt(arr.data().dataType().ordinal());
  allocated.put(shapeBuffer);
  allocated.put(buffer);
  if (rewind)
    allocated.rewind();
}

代码示例来源：origin: deeplearning4j/nd4j

this.guid = Nd4j.getWorkspaceManager().getUUID();
this.memoryManager = Nd4j.getMemoryManager();
this.deviceId = Nd4j.getAffinityManager().getDeviceForCurrentThread();

代码示例来源：origin: deeplearning4j/dl4j-examples

.workers(Nd4j.getAffinityManager().getNumberOfDevices())

代码示例来源：origin: deeplearning4j/dl4j-examples

.prefetchBuffer(16 * Nd4j.getAffinityManager().getNumberOfDevices())
.reportScoreAfterAveraging(true)
.averagingFrequency(10)
.workers(Nd4j.getAffinityManager().getNumberOfDevices())
.build();

代码示例来源：origin: deeplearning4j/dl4j-examples

.workers(Nd4j.getAffinityManager().getNumberOfDevices())

代码示例来源：origin: org.deeplearning4j/deeplearning4j-parallel-wrapper_2.11

@Override
  public Thread newThread(@NotNull Runnable r) {
    Thread t = Executors.defaultThreadFactory().newThread(r);
    int cThread = workerCounter.getAndIncrement();
    t.setName("ParallelWrapper training thread " + cThread);
    t.setDaemon(true);
    t.setUncaughtExceptionHandler(handler);
    Nd4j.getAffinityManager().attachThreadToDevice(t,
            cThread % Nd4j.getAffinityManager().getNumberOfDevices());
    return t;
  }
});

代码示例来源：origin: org.nd4j/nd4j-cuda-7.5

public void init() {
  int numDevices = Nd4j.getAffinityManager().getNumberOfDevices();
  deviceCachedAmount = new ArrayList<>();
  for (int i = 0; i < numDevices; i++) {
    deviceCachedAmount.add(new AtomicLong());
  }
}

代码示例来源：origin: org.nd4j/nd4j-cuda-10.0

public DeviceTADManager() {
  int numDevices = Nd4j.getAffinityManager().getNumberOfDevices();
  for (int i = 0; i < numDevices; i++) {
    tadCache.add(i, new ConcurrentHashMap<TadDescriptor, Pair<DataBuffer, DataBuffer>>());
  }
}

代码示例来源：origin: org.deeplearning4j/deeplearning4j-parallel-wrapper

@Override
  public Thread newThread(@NotNull Runnable r) {
    Thread t = Executors.defaultThreadFactory().newThread(r);
    int cThread = workerCounter.getAndIncrement();
    t.setName("ParallelWrapper training thread " + cThread);
    t.setDaemon(true);
    t.setUncaughtExceptionHandler(handler);
    Nd4j.getAffinityManager().attachThreadToDevice(t,
            cThread % Nd4j.getAffinityManager().getNumberOfDevices());
    return t;
  }
});

代码示例来源：origin: org.nd4j/nd4j-cuda-7.5

public EventsProvider() {
  int numDev = Nd4j.getAffinityManager().getNumberOfDevices();
  for (int i = 0; i < numDev; i++) {
    queue.add(new ConcurrentLinkedQueue<cudaEvent_t>());
  }
}

代码示例来源：origin: org.deeplearning4j/deeplearning4j-core

public MagicQueue build() {
    if (numberOfBuckets < 1)
      numberOfBuckets = Nd4j.getAffinityManager().getNumberOfDevices();
    MagicQueue queue = new MagicQueue(numberOfBuckets, capacity, type);
    queue.mode = this.mode;
    return queue;
  }
}

代码示例来源：origin: org.nd4j/nd4j-api

/**
 * This method returns object local to current deviceId
 *
 * @return
 */
@Nullable
public T get() {
  return get(Nd4j.getAffinityManager().getDeviceForCurrentThread());
}