- java.lang.Object
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- org.tensorflow.ndarray.impl.AbstractNdArray<T,U>
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- org.tensorflow.ndarray.impl.sparse.AbstractSparseNdArray<Short,ShortNdArray>
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- org.tensorflow.ndarray.impl.sparse.ShortSparseNdArray
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- All Implemented Interfaces:
NdArray<Short>,Shaped,ShortNdArray,SparseNdArray<Short,ShortNdArray>
public class ShortSparseNdArray extends AbstractSparseNdArray<Short,ShortNdArray> implements ShortNdArray
sparse array for the short data typeA sparse array as two separate dense arrays: indices, values, and a shape that represents the dense shape.
NOTE: all Sparse Arrays are readonly for the
set(NdArray, long...)andsetObject(Short, long...)methodsShortSparseNdArray st = new ShortSparseNdArray( StdArrays.of(new long[][] {{0, 0}, {1, 2}}), NdArrays.vectorOf((short)1, (short)256), Shape.of(3, 4)); }represents the dense array:
[[1, 0, 0, 0] [0, 0, 256, 0] [0, 0, 0, 0]]
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Constructor Summary
Constructors Modifier Constructor Description protectedShortSparseNdArray(LongNdArray indices, ShortNdArray values, short defaultValue, DimensionalSpace dimensions)Creates a ShortSparseNdArray
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Method Summary
All Methods Static Methods Instance Methods Concrete Methods Modifier and Type Method Description ShortNdArraycopyTo(NdArray<Short> dst)Copy the content of this array to the destination array.static ShortSparseNdArraycreate(short defaultValue, DimensionalSpace dimensions)Creates a new empty ShortSparseNdArray from a data bufferstatic ShortSparseNdArraycreate(ShortDataBuffer dataBuffer, short defaultValue, DimensionalSpace dimensions)Creates a new ShortSparseNdArray from a data bufferstatic ShortSparseNdArraycreate(ShortDataBuffer buffer, short defaultValue, Shape shape)Creates a new empty ShortSparseNdArray from a short data bufferstatic ShortSparseNdArraycreate(ShortDataBuffer dataBuffer, DimensionalSpace dimensions)Creates a new ShortSparseNdArray from a data bufferstatic ShortSparseNdArraycreate(ShortDataBuffer buffer, Shape shape)Creates a new empty ShortSparseNdArray from a short data bufferstatic ShortSparseNdArraycreate(DimensionalSpace dimensions)Creates a new empty ShortSparseNdArray from a data bufferstatic ShortSparseNdArraycreate(LongNdArray indices, ShortNdArray values, short defaultValue, DimensionalSpace dimensions)Creates a new ShortSparseNdArraystatic ShortSparseNdArraycreate(LongNdArray indices, ShortNdArray values, DimensionalSpace dimensions)Creates a new ShortSparseNdArraystatic ShortSparseNdArraycreate(ShortNdArray src)Creates a new ShortSparseNdArray from a ShortNdArraystatic ShortSparseNdArraycreate(ShortNdArray src, short defaultValue)Creates a new ShortSparseNdArray from a ShortNdArrayShortNdArraycreateDefaultArray()Creates the NdArray with the default value as a scalarShortNdArraycreateValues(Shape shape)Creates a ShortNdArray of the specified shapeShortNdArrayfromDense(ShortNdArray src)Populates this sparse array from a dense arrayShortNdArrayget(long... coordinates)Returns the N-dimensional element of this array at the given coordinates.shortgetShort(long... coordinates)Returns the short value of the scalar found at the given coordinates.ShortNdArrayread(DataBuffer<Short> dst)Read the content of this N-dimensional array into the destination buffer.ShortNdArrayread(ShortDataBuffer dst)ShortNdArrayset(NdArray<Short> src, long... coordinates)Assigns the value of the N-dimensional element found at the given coordinates.ShortNdArraysetObject(Short value, long... coordinates)Assigns the value of the scalar found at the given coordinates.ShortNdArraysetShort(short value, long... coordinates)Assigns the short value of the scalar found at the given coordinates.ShortNdArrayslice(long position, DimensionalSpace sliceDimensions)ShortNdArrayslice(Index... indices)Creates a multi-dimensional view (or slice) of this array by mapping one or more dimensions to the given index selectors.ShortNdArraytoDense()Converts the sparse array to a dense arrayShortNdArraywrite(DataBuffer<Short> src)Write the content of this N-dimensional array from the source buffer.ShortNdArraywrite(ShortDataBuffer src)-
Methods inherited from class org.tensorflow.ndarray.impl.sparse.AbstractSparseNdArray
elements, equals, getDefaultArray, getDefaultValue, getIndices, getIndicesCoordinates, getObject, getValues, hashCode, locateIndex, positionOf, setDefaultValue, setIndices, setValues, slowCopyTo, sortIndicesAndValues, toCoordinates, toString
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Methods inherited from class org.tensorflow.ndarray.impl.AbstractNdArray
dimensions, scalars, shape, slowEquals, slowHashCode
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Methods inherited from class java.lang.Object
clone, finalize, getClass, notify, notifyAll, wait, wait, wait
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Methods inherited from interface org.tensorflow.ndarray.NdArray
equals, streamOfObjects
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Methods inherited from interface org.tensorflow.ndarray.ShortNdArray
elements, getObject, scalars
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Constructor Detail
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ShortSparseNdArray
protected ShortSparseNdArray(LongNdArray indices, ShortNdArray values, short defaultValue, DimensionalSpace dimensions)
Creates a ShortSparseNdArray- Parameters:
indices- A 2-D LongNdArray of shape[N, ndims], that specifies the indices of the elements in the sparse array that contain non-default values (elements are zero-indexed). For example,indices=[[1,3], [2,4]]specifies that the elements with indexes of[1,3]and[2,4]have non-default values.values- A 1-D ShortNdArray of shape[N], which supplies the values for each element in indices. For example, givenindices=[[1,3], [2,4]], the parametervalues=[18, 3.6]specifies that element[1,3]of the sparse NdArray has a value of18, and element[2,4]of the NdArray has a value of3.6.defaultValue- Scalar value to set for indices not specified inAbstractSparseNdArray.getIndices()dimensions- the dimensional space for the dense object represented by this sparse array,
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Method Detail
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create
public static ShortSparseNdArray create(LongNdArray indices, ShortNdArray values, DimensionalSpace dimensions)
Creates a new ShortSparseNdArray- Parameters:
indices- A 2-D LongNdArray of shape[N, ndims], that specifies the indices of the elements in the sparse array that contain non-default values (elements are zero-indexed). For example,indices=[[1,3], [2,4]]specifies that the elements with indexes of[1,3]and[2,4]have non-default values.values- A 1-D NdArray of any type and shape[N], which supplies the values for each element in indices. For example, givenindices=[[1,3], [2,4]], the parametervalues=[18, 3.6]specifies that element[1,3]of the sparse NdArray has a value of18, and element[2,4]of the NdArray has a value of3.6.dimensions- the dimensional space for the dense object represented by this sparse array.- Returns:
- the new Sparse Array
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create
public static ShortSparseNdArray create(LongNdArray indices, ShortNdArray values, short defaultValue, DimensionalSpace dimensions)
Creates a new ShortSparseNdArray- Parameters:
indices- A 2-D LongNdArray of shape[N, ndims], that specifies the indices of the elements in the sparse array that contain non-default values (elements are zero-indexed). For example,indices=[[1,3], [2,4]]specifies that the elements with indexes of[1,3]and[2,4]have non-default values.values- A 1-D NdArray of any type and shape[N], which supplies the values for each element in indices. For example, givenindices=[[1,3], [2,4]], the parametervalues=[18, 3.6]specifies that element[1,3]of the sparse NdArray has a value of18, and element[2,4]of the NdArray has a value of3.6.defaultValue- Scalar value to set for indices not specified inAbstractSparseNdArray.getIndices()dimensions- the dimensional space for the dense object represented by this sparse array.- Returns:
- the new Sparse Array
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create
public static ShortSparseNdArray create(ShortDataBuffer dataBuffer, DimensionalSpace dimensions)
Creates a new ShortSparseNdArray from a data buffer- Parameters:
dataBuffer- the databuffer containing the dense arraydimensions- the dimensional space for the sparse array- Returns:
- the new Sparse Array
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create
public static ShortSparseNdArray create(ShortDataBuffer dataBuffer, short defaultValue, DimensionalSpace dimensions)
Creates a new ShortSparseNdArray from a data buffer- Parameters:
dataBuffer- the databuffer containing the dense arraydefaultValue- Scalar value to set for indices not specified inAbstractSparseNdArray.getIndices()dimensions- the dimensional space for the sparse array- Returns:
- the new Sparse Array
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create
public static ShortSparseNdArray create(DimensionalSpace dimensions)
Creates a new empty ShortSparseNdArray from a data buffer- Parameters:
dimensions- the dimensions array- Returns:
- the new Sparse Array
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create
public static ShortSparseNdArray create(short defaultValue, DimensionalSpace dimensions)
Creates a new empty ShortSparseNdArray from a data buffer- Parameters:
defaultValue- Scalar value to set for indices not specified inAbstractSparseNdArray.getIndices()dimensions- the dimensions array- Returns:
- the new Sparse Array
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create
public static ShortSparseNdArray create(ShortDataBuffer buffer, Shape shape)
Creates a new empty ShortSparseNdArray from a short data buffer- Parameters:
buffer- the data buffershape- the shape of the sparse array.- Returns:
- the new Sparse Array
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create
public static ShortSparseNdArray create(ShortDataBuffer buffer, short defaultValue, Shape shape)
Creates a new empty ShortSparseNdArray from a short data buffer- Parameters:
buffer- the data bufferdefaultValue- Scalar value to set for indices not specified inAbstractSparseNdArray.getIndices()shape- the shape of the sparse array.- Returns:
- the new Sparse Array
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create
public static ShortSparseNdArray create(ShortNdArray src)
Creates a new ShortSparseNdArray from a ShortNdArray- Parameters:
src- the ShortNdArray- Returns:
- the new Sparse Array
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create
public static ShortSparseNdArray create(ShortNdArray src, short defaultValue)
Creates a new ShortSparseNdArray from a ShortNdArray- Parameters:
src- the ShortNdArraydefaultValue- Scalar value to set for indices not specified inAbstractSparseNdArray.getIndices()- Returns:
- the new Sparse Array
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createValues
public ShortNdArray createValues(Shape shape)
Creates a ShortNdArray of the specified shape- Specified by:
createValuesin classAbstractSparseNdArray<Short,ShortNdArray>- Parameters:
shape- the shape of the dense array.- Returns:
- a ShortNdArray of the specified shape
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slice
public ShortNdArray slice(long position, DimensionalSpace sliceDimensions)
- Specified by:
slicein classorg.tensorflow.ndarray.impl.AbstractNdArray<Short,ShortNdArray>
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getShort
public short getShort(long... coordinates)
Returns the short 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:
ShortNdArray matrix = NdArrays.ofShorts(shape(2, 2)); // matrix rank = 2 matrix.getShort(0, 1); // succeeds, returns 0.0f matrix.getShort(0); // throws IllegalRankException ShortNdArray scalar = matrix.get(0, 1); // scalar rank = 0 scalar.getShort(); // succeeds, returns 0.0f- Specified by:
getShortin interfaceShortNdArray- Parameters:
coordinates- coordinates of the scalar to resolve- Returns:
- value of that scalar
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setShort
public ShortNdArray setShort(short value, long... coordinates)
Assigns the short 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:
ShortNdArray matrix = NdArrays.ofShorts(shape(2, 2)); // matrix rank = 2 matrix.setShort(10.0f, 0, 1); // succeeds matrix.setShort(10.0f, 0); // throws IllegalRankException ShortNdArray scalar = matrix.get(0, 1); // scalar rank = 0 scalar.setShort(10.0f); // succeeds- Specified by:
setShortin interfaceShortNdArray- Parameters:
value- value to assigncoordinates- coordinates of the scalar to assign- Returns:
- this array
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read
public ShortNdArray read(DataBuffer<Short> dst)
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.- Specified by:
readin interfaceNdArray<Short>- Specified by:
readin interfaceShortNdArray- Parameters:
dst- the destination buffer- Returns:
- this array
- See Also:
DataBuffer.size()
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read
public ShortNdArray read(ShortDataBuffer dst)
- Specified by:
readin interfaceShortNdArray
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write
public ShortNdArray write(ShortDataBuffer src)
- Specified by:
writein interfaceShortNdArray
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write
public ShortNdArray write(DataBuffer<Short> src)
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.- Specified by:
writein interfaceNdArray<Short>- Specified by:
writein interfaceShortNdArray- Parameters:
src- the source buffer- Returns:
- this array
- See Also:
DataBuffer.size()
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toDense
public ShortNdArray toDense()
Converts the sparse array to a dense array- Specified by:
toDensein classAbstractSparseNdArray<Short,ShortNdArray>- Returns:
- the dense array
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fromDense
public ShortNdArray fromDense(ShortNdArray src)
Populates this sparse array from a dense array- Parameters:
src- the dense array- Returns:
- this sparse array
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slice
public ShortNdArray slice(Index... indices)
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 aty=0for allx.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 });- Specified by:
slicein interfaceNdArray<Short>- Specified by:
slicein interfaceShortNdArray- Overrides:
slicein classAbstractSparseNdArray<Short,ShortNdArray>- Parameters:
indices- index selectors per dimensions, starting from dimension 0 of this array.- Returns:
- the element resulting of the index selection
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get
public ShortNdArray get(long... coordinates)
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 toarray.slice(at(x), at(y), at(z))- Specified by:
getin interfaceNdArray<Short>- Specified by:
getin interfaceShortNdArray- Overrides:
getin classAbstractSparseNdArray<Short,ShortNdArray>- Parameters:
coordinates- coordinates of the element to access, none will return this array- Returns:
- the element at this index
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setObject
public ShortNdArray setObject(Short value, long... coordinates)
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:
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,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); // succeedsfloatArray.setFloat(10.0f, 0);- Specified by:
setObjectin interfaceNdArray<Short>- Specified by:
setObjectin interfaceShortNdArray- Overrides:
setObjectin classAbstractSparseNdArray<Short,ShortNdArray>- Parameters:
value- the value to assigncoordinates- coordinates of the scalar to assign- Returns:
- this array
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set
public ShortNdArray set(NdArray<Short> src, long... coordinates)
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- Specified by:
setin interfaceNdArray<Short>- Specified by:
setin interfaceShortNdArray- Overrides:
setin classAbstractSparseNdArray<Short,ShortNdArray>- Parameters:
src- an array of the values to assigncoordinates- coordinates of the element to assign- Returns:
- this array
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copyTo
public ShortNdArray copyTo(NdArray<Short> dst)
Copy the content of this array to the destination array.The
Shaped.shape()of the destination array must be equal to the shape of this array, or an exception is thrown. After the copy, the content of both arrays can be altered independently, without affecting each other.- Specified by:
copyToin interfaceNdArray<Short>- Specified by:
copyToin interfaceShortNdArray- Overrides:
copyToin classAbstractSparseNdArray<Short,ShortNdArray>- Parameters:
dst- array to receive a copy of the content of this array- Returns:
- this array
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createDefaultArray
public ShortNdArray createDefaultArray()
Creates the NdArray with the default value as a scalar- Specified by:
createDefaultArrayin classAbstractSparseNdArray<Short,ShortNdArray>- Returns:
- the default NdArray of the default value as a scalar
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