org.nd4j.linalg.factory.Nd4j.read()方法的使用及代码示例

x33g5p2x  于2022-01-24 转载在 其他  
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本文整理了Java中org.nd4j.linalg.factory.Nd4j.read()方法的一些代码示例，展示了Nd4j.read()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.read()方法的具体详情如下：
包路径：org.nd4j.linalg.factory.Nd4j
类名称：Nd4j
方法名：read

Nd4j.read介绍

[英]Read in an ndarray from a data input stream
[中]从数据输入流读入数据数组

代码示例

代码示例来源：origin: deeplearning4j/nd4j

  1. /**
  2.  * Read an ndarray from a byte array
  3.  * @param arr the array to read from
  4.  * @return the deserialized ndarray
  5.  * @throws IOException
  6.  */
  7. public static INDArray fromByteArray(byte[] arr) throws IOException {
  8.   ByteArrayInputStream bis = new ByteArrayInputStream(arr);
  9.   INDArray ret = read(bis);
  10.   return ret;
  11. }

代码示例来源：origin: deeplearning4j/nd4j

  1. /**
  2.  * Raad an ndarray from an input stream
  3.  * @param reader the input stream to use
  4.  * @return the given ndarray
  5.  * @throws IOException
  6.  */
  7. public static INDArray read(InputStream reader) throws IOException {
  8.   return read(new DataInputStream(reader));
  9. }

代码示例来源：origin: deeplearning4j/nd4j

  1. private INDArray[] loadINDArrays(int numArrays, DataInputStream dis, boolean isMask) throws IOException {
  2.   INDArray[] result = null;
  3.   if (numArrays > 0) {
  4.     result = new INDArray[numArrays];
  5.     for (int i = 0; i < numArrays; i++) {
  6.       INDArray arr = Nd4j.read(dis);
  7.       result[i] = isMask && arr.equals(EMPTY_MASK_ARRAY_PLACEHOLDER.get()) ? null : arr;
  8.     }
  9.   }
  10.   return result;
  11. }

代码示例来源：origin: deeplearning4j/nd4j

  1. private static NormalizerStats readMinMaxStats(DataInputStream dis) throws IOException {
  2.   return new MinMaxStats(Nd4j.read(dis), Nd4j.read(dis));
  3. }

代码示例来源：origin: deeplearning4j/nd4j

  1. private static NormalizerStats readDistributionStats(DataInputStream dis) throws IOException {
  2.   return new DistributionStats(Nd4j.read(dis), Nd4j.read(dis));
  3. }

代码示例来源：origin: deeplearning4j/nd4j

  1. @Override
  2. public NormalizerStandardize restore(@NonNull InputStream stream) throws IOException {
  3.   DataInputStream dis = new DataInputStream(stream);
  4.   boolean fitLabels = dis.readBoolean();
  5.   NormalizerStandardize result = new NormalizerStandardize(Nd4j.read(dis), Nd4j.read(dis));
  6.   result.fitLabel(fitLabels);
  7.   if (fitLabels) {
  8.     result.setLabelStats(Nd4j.read(dis), Nd4j.read(dis));
  9.   }
  10.   return result;
  11. }

代码示例来源：origin: deeplearning4j/nd4j

  1. /**
  2.  * Read a binary ndarray from the given file
  3.  * @param read the nd array to read
  4.  * @return the loaded ndarray
  5.  * @throws IOException
  6.  */
  7. public static INDArray readBinary(File read) throws IOException {
  8.   BufferedInputStream bis = new BufferedInputStream(new FileInputStream(read));
  9.   DataInputStream dis = new DataInputStream(bis);
  10.   INDArray ret = Nd4j.read(dis);
  11.   dis.close();
  12.   return ret;
  13. }

代码示例来源：origin: deeplearning4j/nd4j

  1. private DataSet read(int idx) throws IOException {
  2.   BufferedInputStream bis = new BufferedInputStream(new FileInputStream(paths.get(idx)[0]));
  3.   DataInputStream dis = new DataInputStream(bis);
  4.   BufferedInputStream labelInputStream = new BufferedInputStream(new FileInputStream(paths.get(idx)[1]));
  5.   DataInputStream labelDis = new DataInputStream(labelInputStream);
  6.   DataSet d = new DataSet(Nd4j.read(dis), Nd4j.read(labelDis));
  7.   dis.close();
  8.   labelDis.close();
  9.   return d;
  10. }

代码示例来源：origin: deeplearning4j/nd4j

  1. @Override
  2. public void load(InputStream from) {
  3.   try {
  4.     DataInputStream dis = from instanceof BufferedInputStream ? new DataInputStream(from)
  5.             : new DataInputStream(new BufferedInputStream(from));
  6.     byte included = dis.readByte();
  7.     boolean hasFeatures = (included & BITMASK_FEATURES_PRESENT) != 0;
  8.     boolean hasLabels = (included & BITMASK_LABELS_PRESENT) != 0;
  9.     boolean hasLabelsSameAsFeatures = (included & BITMASK_LABELS_SAME_AS_FEATURES) != 0;
  10.     boolean hasFeaturesMask = (included & BITMASK_FEATURE_MASK_PRESENT) != 0;
  11.     boolean hasLabelsMask = (included & BITMASK_LABELS_MASK_PRESENT) != 0;
  12.     features = (hasFeatures ? Nd4j.read(dis) : null);
  13.     if (hasLabels) {
  14.       labels = Nd4j.read(dis);
  15.     } else if (hasLabelsSameAsFeatures) {
  16.       labels = features;
  17.     } else {
  18.       labels = null;
  19.     }
  20.     featuresMask = (hasFeaturesMask ? Nd4j.read(dis) : null);
  21.     labelsMask = (hasLabelsMask ? Nd4j.read(dis) : null);
  22.     dis.close();
  23.   } catch (Exception e) {
  24.     throw new RuntimeException("Error loading DataSet",e);
  25.   }
  26. }

代码示例来源：origin: deeplearning4j/nd4j

  1. /**
  2.  * Create an ndarray from a base 64
  3.  * representation
  4.  * @param base64 the base 64 to convert
  5.  * @return the ndarray from base 64
  6.  * @throws IOException
  7.  */
  8. public static INDArray fromBase64(String base64) throws IOException {
  9.   byte[] arr = Base64.decodeBase64(base64);
  10.   ByteArrayInputStream bis = new ByteArrayInputStream(arr);
  11.   DataInputStream dis = new DataInputStream(bis);
  12.   INDArray predict = Nd4j.read(dis);
  13.   return predict;
  14. }

代码示例来源：origin: deeplearning4j/nd4j

  1. @Override
  2. public NormalizerMinMaxScaler restore(@NonNull InputStream stream) throws IOException {
  3.   DataInputStream dis = new DataInputStream(stream);
  4.   boolean fitLabels = dis.readBoolean();
  5.   double targetMin = dis.readDouble();
  6.   double targetMax = dis.readDouble();
  7.   NormalizerMinMaxScaler result = new NormalizerMinMaxScaler(targetMin, targetMax);
  8.   result.fitLabel(fitLabels);
  9.   result.setFeatureStats(Nd4j.read(dis), Nd4j.read(dis));
  10.   if (fitLabels) {
  11.     result.setLabelStats(Nd4j.read(dis), Nd4j.read(dis));
  12.   }
  13.   return result;
  14. }

代码示例来源：origin: deeplearning4j/nd4j

  1. /**
  2.  * Returns a set of arrays
  3.  * from base 64 that is tab delimited.
  4.  * @param base64 the base 64 that's tab delimited
  5.  * @return the set of arrays
  6.  */
  7. public static INDArray[] arraysFromBase64(String base64) throws IOException {
  8.   String[] base64Arr = base64.split("\t");
  9.   INDArray[] ret = new INDArray[base64Arr.length];
  10.   for (int i = 0; i < base64Arr.length; i++) {
  11.     byte[] decode = Base64.decodeBase64(base64Arr[i]);
  12.     ByteArrayInputStream bis = new ByteArrayInputStream(decode);
  13.     DataInputStream dis = new DataInputStream(bis);
  14.     INDArray predict = Nd4j.read(dis);
  15.     ret[i] = predict;
  16.   }
  17.   return ret;
  18. }

代码示例来源：origin: deeplearning4j/nd4j

  1. /**
  2.  * Restore a MultiNormalizerStandardize that was previously serialized by this strategy
  3.  *
  4.  * @param stream the input stream to restore from
  5.  * @return the restored MultiNormalizerStandardize
  6.  * @throws IOException
  7.  */
  8. public MultiNormalizerStandardize restore(@NonNull InputStream stream) throws IOException {
  9.   DataInputStream dis = new DataInputStream(stream);
  10.   boolean fitLabels = dis.readBoolean();
  11.   int numInputs = dis.readInt();
  12.   int numOutputs = dis.readInt();
  13.   MultiNormalizerStandardize result = new MultiNormalizerStandardize();
  14.   result.fitLabel(fitLabels);
  15.   List<DistributionStats> featureStats = new ArrayList<>();
  16.   for (int i = 0; i < numInputs; i++) {
  17.     featureStats.add(new DistributionStats(Nd4j.read(dis), Nd4j.read(dis)));
  18.   }
  19.   result.setFeatureStats(featureStats);
  20.   if (fitLabels) {
  21.     List<DistributionStats> labelStats = new ArrayList<>();
  22.     for (int i = 0; i < numOutputs; i++) {
  23.       labelStats.add(new DistributionStats(Nd4j.read(dis), Nd4j.read(dis)));
  24.     }
  25.     result.setLabelStats(labelStats);
  26.   }
  27.   return result;
  28. }

代码示例来源：origin: deeplearning4j/nd4j

  1. /**
  2.  * Restore a MultiNormalizerMinMaxScaler that was previously serialized by this strategy
  3.  *
  4.  * @param stream the input stream to restore from
  5.  * @return the restored MultiNormalizerMinMaxScaler
  6.  * @throws IOException
  7.  */
  8. public MultiNormalizerMinMaxScaler restore(@NonNull InputStream stream) throws IOException {
  9.   DataInputStream dis = new DataInputStream(stream);
  10.   boolean fitLabels = dis.readBoolean();
  11.   int numInputs = dis.readInt();
  12.   int numOutputs = dis.readInt();
  13.   double targetMin = dis.readDouble();
  14.   double targetMax = dis.readDouble();
  15.   MultiNormalizerMinMaxScaler result = new MultiNormalizerMinMaxScaler(targetMin, targetMax);
  16.   result.fitLabel(fitLabels);
  17.   List<MinMaxStats> featureStats = new ArrayList<>();
  18.   for (int i = 0; i < numInputs; i++) {
  19.     featureStats.add(new MinMaxStats(Nd4j.read(dis), Nd4j.read(dis)));
  20.   }
  21.   result.setFeatureStats(featureStats);
  22.   if (fitLabels) {
  23.     List<MinMaxStats> labelStats = new ArrayList<>();
  24.     for (int i = 0; i < numOutputs; i++) {
  25.       labelStats.add(new MinMaxStats(Nd4j.read(dis), Nd4j.read(dis)));
  26.     }
  27.     result.setLabelStats(labelStats);
  28.   }
  29.   return result;
  30. }

代码示例来源：origin: org.nd4j/nd4j-api

  1. /**
  2.  * Raad an ndarray from an input stream
  3.  * @param reader the input stream to use
  4.  * @return the given ndarray
  5.  * @throws IOException
  6.  */
  7. public static INDArray read(InputStream reader) throws IOException {
  8.   return read(new DataInputStream(reader));
  9. }

代码示例来源：origin: org.nd4j/nd4j-api

  1. /**
  2.  * Read an ndarray from a byte array
  3.  * @param arr the array to read from
  4.  * @return the deserialized ndarray
  5.  * @throws IOException
  6.  */
  7. public static INDArray fromByteArray(byte[] arr) throws IOException {
  8.   ByteArrayInputStream bis = new ByteArrayInputStream(arr);
  9.   INDArray ret = read(bis);
  10.   return ret;
  11. }

代码示例来源：origin: de.datexis/texoo-core

  1. public static INDArray getArrayFromBase64String(String encoded) {
  2.  byte[] decodedBytes = Base64.decodeBase64(encoded);
  3.  ByteArrayInputStream bais = new ByteArrayInputStream(decodedBytes);
  4.  BufferedInputStream bis = new BufferedInputStream(bais);
  5.  try(DataInputStream dis = new DataInputStream(bis)) {
  6.   return Nd4j.read(dis);
  7.  } catch(IOException ex) {
  8.   throw new RuntimeException("Could not create INDArray from Base64 String");
  9.  }
  10. }

代码示例来源：origin: org.nd4j/nd4j-api

  1. /**
  2.  * Read a binary ndarray from the given file
  3.  * @param read the nd array to read
  4.  * @return the loaded ndarray
  5.  * @throws IOException
  6.  */
  7. public static INDArray readBinary(File read) throws IOException {
  8.   BufferedInputStream bis = new BufferedInputStream(new FileInputStream(read));
  9.   DataInputStream dis = new DataInputStream(bis);
  10.   INDArray ret = Nd4j.read(dis);
  11.   dis.close();
  12.   return ret;
  13. }

代码示例来源：origin: org.nd4j/nd4j-api

  1. @Override
  2. public NormalizerStandardize restore(@NonNull InputStream stream) throws IOException {
  3.   DataInputStream dis = new DataInputStream(stream);
  4.   boolean fitLabels = dis.readBoolean();
  5.   NormalizerStandardize result = new NormalizerStandardize(Nd4j.read(dis), Nd4j.read(dis));
  6.   result.fitLabel(fitLabels);
  7.   if (fitLabels) {
  8.     result.setLabelStats(Nd4j.read(dis), Nd4j.read(dis));
  9.   }
  10.   return result;
  11. }

代码示例来源：origin: org.nd4j/nd4j-api

  1. private DataSet read(int idx) throws IOException {
  2.   BufferedInputStream bis = new BufferedInputStream(new FileInputStream(paths.get(idx)[0]));
  3.   DataInputStream dis = new DataInputStream(bis);
  4.   BufferedInputStream labelInputStream = new BufferedInputStream(new FileInputStream(paths.get(idx)[1]));
  5.   DataInputStream labelDis = new DataInputStream(labelInputStream);
  6.   DataSet d = new DataSet(Nd4j.read(dis), Nd4j.read(labelDis));
  7.   dis.close();
  8.   labelDis.close();
  9.   return d;
  10. }

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