Package org.ejml.simple

Examples of org.ejml.simple.SimpleMatrix

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      // TODO: factor out unknown word vector code from DVParser
      wordVectors.put(word, embedding.get(word));
    }

    String unkWord = op.unkWord;
    SimpleMatrix unknownWordVector = wordVectors.get(unkWord);
    wordVectors.put(UNKNOWN_WORD, unknownWordVector);
    if (unknownWordVector == null) {
      throw new RuntimeException("Unknown word vector not specified in the word vector file");
    }
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   * Creates a zero initialized tensor
   */
  public SimpleTensor(int numRows, int numCols, int numSlices) {
    slices = new SimpleMatrix[numSlices];
    for (int i = 0; i < numSlices; ++i) {
      slices[i] = new SimpleMatrix(numRows, numCols);
    }

    this.numRows = numRows;
    this.numCols = numCols;
    this.numSlices = numSlices;
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    this.slices = new SimpleMatrix[slices.length];
    for (int i = 0; i < numSlices; ++i) {
      if (slices[i].numRows() != numRows || slices[i].numCols() != numCols) {
        throw new IllegalArgumentException("Slice " + i + " has matrix dimensions " + slices[i].numRows() + "," + slices[i].numCols() + ", expected " + numRows + "," + numCols);
      }
      this.slices[i] = new SimpleMatrix(slices[i]);
    }
   
  }
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      throw new AssertionError("Number of rows in the input does not match number of columns in tensor");
    }
    if (numRows != numCols) {
      throw new AssertionError("Can only perform this operation on a SimpleTensor with square slices");
    }
    SimpleMatrix inT = in.transpose();
    SimpleMatrix out = new SimpleMatrix(numSlices, 1);
    for (int slice = 0; slice < numSlices; ++slice) {
      double result = inT.mult(slices[slice]).mult(in).get(0);
      out.set(slice, result);
    }
    return out;
  }
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      }
      for (int col = 0; col < numCols; ++col) {
        data[row][col] = Double.valueOf(pieces[col]);
      }
    }
    return new SimpleMatrix(data);
  }
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  @SafeVarargs
  public static void vectorToParams(double[] theta, Iterator<SimpleMatrix> ... matrices) {
    int index = 0;
    for (Iterator<SimpleMatrix> matrixIterator : matrices) {
      while (matrixIterator.hasNext()) {
        SimpleMatrix matrix = matrixIterator.next();
        int numElements = matrix.getNumElements();
        for (int i = 0; i < numElements; ++i) {
          matrix.set(i, theta[index]);
          ++index;
        }
      }
    }
    if (index != theta.length) {
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  public static double[] paramsToVector(int totalSize, Iterator<SimpleMatrix> ... matrices) {
    double[] theta = new double[totalSize];
    int index = 0;
    for (Iterator<SimpleMatrix> matrixIterator : matrices) {
      while (matrixIterator.hasNext()) {
        SimpleMatrix matrix = matrixIterator.next();
        int numElements = matrix.getNumElements();
        //System.out.println(Integer.toString(numElements)); // to know what matrices are
        for (int i = 0; i < numElements; ++i) {
          theta[index] = matrix.get(i);
          ++index;
        }
      }
    }
    if (index != totalSize) {
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  public static double[] paramsToVector(double scale, int totalSize, Iterator<SimpleMatrix> ... matrices) {
    double[] theta = new double[totalSize];
    int index = 0;
    for (Iterator<SimpleMatrix> matrixIterator : matrices) {
      while (matrixIterator.hasNext()) {
        SimpleMatrix matrix = matrixIterator.next();
        int numElements = matrix.getNumElements();
        for (int i = 0; i < numElements; ++i) {
          theta[index] = matrix.get(i) * scale;
          ++index;
        }
      }
    }
    if (index != totalSize) {
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   * Applies softmax to all of the elements of the matrix.  The return
   * matrix will have all of its elements sum to 1.  If your matrix is
   * not already a vector, be sure this is what you actually want.
   */
  public static SimpleMatrix softmax(SimpleMatrix input) {
    SimpleMatrix output = new SimpleMatrix(input);
    for (int i = 0; i < output.numRows(); ++i) {
      for (int j = 0; j < output.numCols(); ++j) {
        output.set(i, j, Math.exp(output.get(i, j)));
      }
    }
    double sum = output.elementSum();
    // will be safe, since exp should never return 0
    return output.scale(1.0 / sum);
  }
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  /**
   * Applies log to each of the entries in the matrix.  Returns a new matrix.
   */
  public static SimpleMatrix elementwiseApplyLog(SimpleMatrix input) {
    SimpleMatrix output = new SimpleMatrix(input);
    for (int i = 0; i < output.numRows(); ++i) {
      for (int j = 0; j < output.numCols(); ++j) {
        output.set(i, j, Math.log(output.get(i, j)));
      }
    }
    return output;
  }
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Related Classes of org.ejml.simple.SimpleMatrix

  • com.sketchingbits.mlearning.clustering.KMeans
  • edu.stanford.nlp.neural.Embedding
  • edu.stanford.nlp.neural.EmbeddingITest
  • edu.stanford.nlp.neural.NeuralUtils
  • edu.stanford.nlp.neural.NeuralUtilsTest
  • edu.stanford.nlp.neural.SimpleTensor
  • edu.stanford.nlp.parser.dvparser.AverageDVModels
  • edu.stanford.nlp.parser.dvparser.DumpMatrices
  • edu.stanford.nlp.parser.dvparser.DVModel
  • edu.stanford.nlp.parser.dvparser.DVParserCostAndGradient
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