本文整理了Java中org.nd4j.linalg.factory.Nd4j.copy()方法的一些代码示例，展示了Nd4j.copy()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.copy()方法的具体详情如下：
包路径：org.nd4j.linalg.factory.Nd4j
类名称：Nd4j
方法名：copy

Nd4j.copy介绍

[英]Copy a to b
[中]复制a到b

代码示例

代码示例来源：origin: neo4j-graph-analytics/ml-models

private INDArray pruneEmbedding(INDArray origEmbedding, int... featIdsToKeep) {
  INDArray ndPrunedEmbedding = Nd4j.create(origEmbedding.shape());
  Nd4j.copy(origEmbedding, ndPrunedEmbedding);
  return ndPrunedEmbedding.getColumns(featIdsToKeep);
}

代码示例来源：origin: neo4j-graph-analytics/ml-models

private void diffuse(List<Pruning.Feature> featuresList) {
  INDArray ndDiffused = Nd4j.create(embedding.shape());
  Nd4j.copy(embedding, ndDiffused);
  featuresList.addAll(featuresList);
  features = featuresList.toArray(new Pruning.Feature[0]);
  for (int i = features.length / 2; i < features.length; i++) {
    features[i] = new Pruning.Feature("diffuse", features[i]);
  }
  for (int diffIteration = 0; diffIteration < diffusionIterations; diffIteration++) {
    INDArray ndDiffusedTemp = Nd4j.create(embedding.shape());
    nodeQueue.set(0);
    final ArrayList<Future<?>> futures = new ArrayList<>();
    for (int i = 0; i < concurrency; i++) {
      futures.add(executorService.submit(new DiffusionTask(ndDiffused, ndDiffusedTemp)));
    }
    ParallelUtil.awaitTermination(futures);
    ndDiffused = ndDiffusedTemp;
  }
  embedding = Nd4j.concat(1, embedding, ndDiffused);
}

代码示例来源：origin: CampagneLaboratory/variationanalysis

private void keepLongestMask(int minibatchSize, INDArray mask, int[] randomIndex1, int[] randomIndex2) {
  if (mask == null) return;
  INDArray[] tmpBuffer = new INDArray[minibatchSize];
  // Find the longest mask and keep it as mixup ask:
  for (int exampleIndex = 0; exampleIndex < minibatchSize; exampleIndex++) {
    int random1 = randomIndex1[exampleIndex];
    int random2 = randomIndex2[exampleIndex];
    final INDArray mask1 = mask.getRow(random1);
    final INDArray mask2 = mask.getRow(random2);
    tmpBuffer[exampleIndex] = Nd4j.createUninitializedDetached(mask1.shape());
    if (mask1.sub(mask2).sumNumber().doubleValue() < 0) {
      // mask2 has more 1s than mask1, use mask2:
      Nd4j.copy(mask2, tmpBuffer[exampleIndex]);
    } else {
      Nd4j.copy(mask1, tmpBuffer[exampleIndex]);
    }
  }
  for (int exampleIndex = 0; exampleIndex < minibatchSize; exampleIndex++) {
    // assign tmpBuffer[inputIndex] back into the minibatch:
    mask.putRow(exampleIndex, tmpBuffer[exampleIndex]);
  }
}

代码示例来源：origin: CampagneLaboratory/variationanalysis

private DataSet enrichWithErrors(DataSet ds) {
  if (!args().errorEnrichment) {
    return ds;
  }
  if (queue.isEmpty()) {
    // no errors were collected yet. Return the un-enriched dataset.
    return ds;
  }
  int size = this.args().numErrorsAdded;
  INDArray inputs = Nd4j.zeros(size, featureCalculator.numberOfFeatures());
  INDArray labels = Nd4j.zeros(size, labelMapper.numberOfLabels());
  int i = 0;
  for (ErrorRecord errorRecord : queue.getRandomSample(size)) {
    // we are going to call nextRecord directly, without checking hasNextRecord, because we have
    // determined how many times we can call (in size). We should get the exception if we were
    // wrong in our estimate of size.
    // fill in features and labels for a given record i:
    Nd4j.copy(errorRecord.features.get(new PointIndex(0)), inputs.get(new PointIndex(i)));
    Nd4j.copy(errorRecord.label, labels.get(new PointIndex(i)));
    i++;
  }
  DataSet errorDataSet = new DataSet(inputs, labels);
  array[0] = ds;
  array[1] = errorDataSet;
  final DataSet enrichedDataset = DataSet.merge(ObjectArrayList.wrap(array));
  return enrichedDataset;
}

代码示例来源：origin: neo4j-graph-analytics/ml-models

final INDArray temp = Nd4j.zerosLike(transpose);
for (int i = numPrevFeatures; i < embedding.columns(); i++) {
  Nd4j.copy(transpose, temp);
  final int[] total =
      temp.subiRowVector(transpose.getRow(i))

代码示例来源：origin: apache/opennlp-sandbox

Nd4j.copy(hPrev, hs1);