Module org.tensorflow.ndarray
Package org.tensorflow.ndarray.impl.dense

Class AbstractDenseNdArray<T,​U extends NdArray<T>>

    • Field Summary

      • Fields inherited from class org.tensorflow.ndarray.impl.AbstractNdArray

        dimensions

    • Method Summary

      All Methods Instance Methods Abstract Methods Concrete Methods 
      Modifier and Type Method Description
      protected abstract DataBuffer<T> buffer()  
      NdArraySequence<U> elements​(int dimensionIdx)
      Returns a sequence of all elements at a given dimension.
      boolean equals​(Object obj)
      Checks equality between n-dimensional arrays.
      U get​(long... coords)
      Returns the N-dimensional element of this array at the given coordinates.
      T getObject​(long... coords)
      Returns the value of the scalar found at the given coordinates.
      int hashCode()  
      U read​(DataBuffer<T> dst)
      Read the content of this N-dimensional array into the destination buffer.
      U set​(NdArray<T> src, long... coordinates)
      Assigns the value of the N-dimensional element found at the given coordinates.
      U setObject​(T value, long... coords)
      Assigns the value of the scalar found at the given coordinates.
      U slice​(long position, DimensionalSpace sliceDimensions)  
      U slice​(Index... indices)
      Creates a multi-dimensional view (or slice) of this array by mapping one or more dimensions to the given index selectors.
      protected void slowCopyTo​(NdArray<T> array)  
      String toString()
      A String showing the type and shape of this dense ndarray.
      U write​(DataBuffer<T> src)
      Write the content of this N-dimensional array from the source buffer.

      • Methods inherited from class org.tensorflow.ndarray.impl.AbstractNdArray

        dimensions, scalars, shape, slowEquals, slowHashCode

      • Methods inherited from interface org.tensorflow.ndarray.Shaped

        rank, size

    • Constructor Detail

      • AbstractDenseNdArray

        protected AbstractDenseNdArray​(DimensionalSpace dimensions)

    • Method Detail

      • elements

        public NdArraySequence<U> elements​(int dimensionIdx)
        Description copied from interface: NdArray
        Returns a sequence of all elements at a given dimension.

        Logically, the N-dimensional array can be flatten in a single vector, where the scalars of the (n - 1)th element precedes those of the (n)th element, for a total of Shaped.size() values.

        For example, given a n x m matrix on the [x, y] axes, elements are iterated in the following order:

        x0y0, x0y1, ..., x0ym-1, x1y0, x1y1, ..., xn-1ym-1

        The returned sequence can then be iterated to visit each elements, either by calling Iterable.forEach(Consumer) or NdArraySequence.forEachIndexed(BiConsumer). 

        
    // Iterate matrix for initializing each of its vectors
    matrixOfFloats.elements(0).forEach(v -> {
      v.set(vector(1.0f, 2.0f, 3.0f));
    });

    // Iterate a vector for reading each of its scalar
    vectorOfFloats.scalars().forEachIdx((coords, s) -> {
      System.out.println("Value " + s.getFloat() + " found at " + coords);
    });
        Parameters:
        dimensionIdx - index of the dimension
        Returns:
        an NdArray sequence

      • slice

        public U slice​(long position,
               DimensionalSpace sliceDimensions)
        Specified by:
        slice in class org.tensorflow.ndarray.impl.AbstractNdArray<T,​U extends NdArray<T>>

      • slice

        public U slice​(Index... indices)
        Description copied from interface: NdArray
        Creates a multi-dimensional view (or slice) of this array by mapping one or more dimensions to the given index selectors.

        Slices allow to traverse an N-dimensional array in any of its axis and/or to filter only elements of interest. For example, for a given matrix on the [x, y] axes, it is possible to iterate elements at y=0 for all x.

        Any changes applied to the returned slice affect the data of this array as well, as there is no copy involved.

        Example of usage: 

        
    FloatNdArray matrix3d = NdArrays.ofFloats(shape(3, 2, 4));  // with [x, y, z] axes

    // Iterates elements on the x axis by preserving only the 3rd value on the z axis,
    // (i.e. [x, y, 2])
    matrix3d.slice(all(), all(), at(2)).elements(0).forEach(m -> {
      assertEquals(shape(2), m); // y=2, z=0 (scalar)
    });

    // Creates a slice that contains only the last element of the y axis and elements with an
    // odd `z` coordinate.
    FloatNdArray slice = matrix3d.slice(all(), at(1), odd());
    assertEquals(shape(3, 2), slice.shape());  // x=3, y=0 (scalar), z=2 (odd coordinates)

    // Iterates backward the elements on the x axis
    matrix3d.slice(flip()).elements(0).forEach(m -> {
      assertEquals(shape(2, 4), m);  // y=2, z=4
    });
        Parameters:
        indices - index selectors per dimensions, starting from dimension 0 of this array.
        Returns:
        the element resulting of the index selection

      • get

        public U get​(long... coords)
        Description copied from interface: NdArray
        Returns the N-dimensional element of this array at the given coordinates.

        Elements of any of the dimensions of this array can be retrieved. For example, if the number of coordinates is equal to the number of dimensions of this array, then a rank-0 (scalar) array is returned, which value can then be obtained by calling `array.getObject()`.

        Any changes applied to the returned elements affect the data of this array as well, as there is no copy involved.

        Note that invoking this method is an equivalent and more efficient way to slice this array on single scalar, i.e. array.get(x, y, z) is equal to array.slice(at(x), at(y), at(z))

        Parameters:
        coords - coordinates of the element to access, none will return this array
        Returns:
        the element at this index

      • getObject

        public T getObject​(long... coords)
        Description copied from interface: NdArray
        Returns the value of the scalar found at the given coordinates.

        To access the scalar element, the number of coordinates provided must be equal to the number of dimensions of this array (i.e. its rank). For example: 

        
  FloatNdArray matrix = NdArrays.ofFloats(shape(2, 2));  // matrix rank = 2
  matrix.getObject(0, 1);  // succeeds, returns 0.0f
  matrix.getObject(0);  // throws IllegalRankException

  FloatNdArray scalar = matrix.get(0, 1);  // scalar rank = 0
  scalar.getObject();  // succeeds, returns 0.0f
        Note: if this array stores values of a primitive type, prefer the usage of the specialized method in the subclass for that type. For example, floatArray.getFloat(0); .
        Parameters:
        coords - coordinates of the scalar to resolve
        Returns:
        value of that scalar

      • set

        public U set​(NdArray<T> src,
             long... coordinates)
        Description copied from interface: NdArray
        Assigns the value of the N-dimensional element found at the given coordinates.

        The number of coordinates provided can be anywhere between 0 and rank - 1. For example: 

        
  FloatNdArray matrix = NdArrays.ofFloats(shape(2, 2));  // matrix rank = 2
  matrix.set(vector(10.0f, 20.0f), 0);  // success
  matrix.set(scalar(10.0f), 1, 0); // success
        Parameters:
        src - an array of the values to assign
        coordinates - coordinates of the element to assign
        Returns:
        this array

      • setObject

        public U setObject​(T value,
                   long... coords)
        Description copied from interface: NdArray
        Assigns the value of the scalar found at the given coordinates.

        To access the scalar element, the number of coordinates provided must be equal to the number of dimensions of this array (i.e. its rank). For example: 

        
  FloatNdArray matrix = NdArrays.ofFloats(shape(2, 2));  // matrix rank = 2
  matrix.setObject(10.0f, 0, 1);  // succeeds
  matrix.setObject(10.0f, 0);  // throws IllegalRankException

  FloatNdArray scalar = matrix.get(0, 1);  // scalar rank = 0
  scalar.setObject(10.0f);  // succeeds
        Note: if this array stores values of a primitive type, prefer the usage of the specialized method in the subclass for that type. For example, floatArray.setFloat(10.0f, 0);
        Parameters:
        value - the value to assign
        coords - coordinates of the scalar to assign
        Returns:
        this array

      • read

        public U read​(DataBuffer<T> dst)
        Description copied from interface: NdArray
        Read the content of this N-dimensional array into the destination buffer.

        The size of the buffer must be equal or greater to the Shaped.size() of this array, or an exception is thrown. After the copy, content of the buffer and of the array can be altered independently, without affecting each other.

        Parameters:
        dst - the destination buffer
        Returns:
        this array
        See Also:
        DataBuffer.size()

      • write

        public U write​(DataBuffer<T> src)
        Description copied from interface: NdArray
        Write the content of this N-dimensional array from the source buffer.

        The size of the buffer must be equal or greater to the Shaped.size() of this array, or an exception is thrown. After the copy, content of the buffer and of the array can be altered independently, without affecting each other.

        Parameters:
        src - the source buffer
        Returns:
        this array
        See Also:
        DataBuffer.size()

      • hashCode

        public int hashCode()
        Overrides:
        hashCode in class org.tensorflow.ndarray.impl.AbstractNdArray<T,​U extends NdArray<T>>

      • equals

        public boolean equals​(Object obj)
        Description copied from interface: NdArray
        Checks equality between n-dimensional arrays.

        An array is equal to another object if this object is another NdArray of the same shape, type and the elements are equal and in the same order. For example: 

        
 IntNdArray array = NdArrays.ofInts(Shape.of(2, 2))
    .set(NdArrays.vectorOf(1, 2), 0)
    .set(NdArrays.vectorOf(3, 4), 1);

 assertEquals(array, StdArrays.ndCopyOf(new int[][] {{1, 2}, {3, 4}}));  // true
 assertEquals(array, StdArrays.ndCopyOf(new Integer[][] {{1, 2}, {3, 4}}));  // true, as Integers are equal to ints
 assertNotEquals(array, NdArrays.vectorOf(1, 2, 3, 4));  // false, different shapes
 assertNotEquals(array, StdArrays.ndCopyOf(new int[][] {{3, 4}, {1, 2}}));  // false, different order
 assertNotEquals(array, StdArrays.ndCopyOf(new long[][] {{1L, 2L}, {3L, 4L}}));  // false, different types

        Note that the computation required to verify equality between two arrays can be expensive in some cases and therefore, it is recommended to not use this method in a critical path where performances matter.

        Specified by:
        equals in interface NdArray<T>
        Overrides:
        equals in class org.tensorflow.ndarray.impl.AbstractNdArray<T,​U extends NdArray<T>>
        Parameters:
        obj - object to compare this array with
        Returns:
        true if this array is equal to the provided object

      • toString

        public String toString()
        A String showing the type and shape of this dense ndarray.
        Overrides:
        toString in class Object
        Returns:
        A string containing the type and shape.

      • slowCopyTo

        protected void slowCopyTo​(NdArray<T> array)
        Overrides:
        slowCopyTo in class org.tensorflow.ndarray.impl.AbstractNdArray<T,​U extends NdArray<T>>