GatherNd

public final class GatherNd

Gather slices from `params` into a Tensor with shape specified by `indices`.

`indices` is a K-dimensional integer tensor, best thought of as a (K-1)-dimensional tensor of indices into `params`, where each element defines a slice of `params`:

output[\\(i_0, ..., i_{K-2}\\)] = params[indices[\\(i_0, ..., i_{K-2}\\)]]

Whereas in tf.gather `indices` defines slices into the `axis` dimension of `params`, in tf.gather_nd, `indices` defines slices into the first `N` dimensions of `params`, where `N = indices.shape[-1]`.

The last dimension of `indices` can be at most the rank of `params`:

indices.shape[-1] <= params.rank

The last dimension of `indices` corresponds to elements (if `indices.shape[-1] == params.rank`) or slices (if `indices.shape[-1] < params.rank`) along dimension `indices.shape[-1]` of `params`. The output tensor has shape

indices.shape[:-1] + params.shape[indices.shape[-1]:]

Note that on CPU, if an out of bound index is found, an error is returned. On GPU, if an out of bound index is found, a 0 is stored in the corresponding output value.

Some examples below.

Simple indexing into a matrix:

indices = [[0, 0], [1, 1]]
     params = [['a', 'b'], ['c', 'd']]
     output = ['a', 'd']
 

Slice indexing into a matrix:

indices = [[1], [0]]
     params = [['a', 'b'], ['c', 'd']]
     output = [['c', 'd'], ['a', 'b']]
 

Indexing into a 3-tensor:

indices = [[1]]
     params = [[['a0', 'b0'], ['c0', 'd0']],
               [['a1', 'b1'], ['c1', 'd1']]]
     output = [[['a1', 'b1'], ['c1', 'd1']]]
 
 
     indices = [[0, 1], [1, 0]]
     params = [[['a0', 'b0'], ['c0', 'd0']],
               [['a1', 'b1'], ['c1', 'd1']]]
     output = [['c0', 'd0'], ['a1', 'b1']]
 
 
     indices = [[0, 0, 1], [1, 0, 1]]
     params = [[['a0', 'b0'], ['c0', 'd0']],
               [['a1', 'b1'], ['c1', 'd1']]]
     output = ['b0', 'b1']
 

Batched indexing into a matrix:

indices = [[[0, 0]], [[0, 1]]]
     params = [['a', 'b'], ['c', 'd']]
     output = [['a'], ['b']]
 

Batched slice indexing into a matrix:

indices = [[[1]], [[0]]]
     params = [['a', 'b'], ['c', 'd']]
     output = [[['c', 'd']], [['a', 'b']]]
 

Batched indexing into a 3-tensor:

indices = [[[1]], [[0]]]
     params = [[['a0', 'b0'], ['c0', 'd0']],
               [['a1', 'b1'], ['c1', 'd1']]]
     output = [[[['a1', 'b1'], ['c1', 'd1']]],
               [[['a0', 'b0'], ['c0', 'd0']]]]
 
     indices = [[[0, 1], [1, 0]], [[0, 0], [1, 1]]]
     params = [[['a0', 'b0'], ['c0', 'd0']],
               [['a1', 'b1'], ['c1', 'd1']]]
     output = [[['c0', 'd0'], ['a1', 'b1']],
               [['a0', 'b0'], ['c1', 'd1']]]
 
 
     indices = [[[0, 0, 1], [1, 0, 1]], [[0, 1, 1], [1, 1, 0]]]
     params = [[['a0', 'b0'], ['c0', 'd0']],
               [['a1', 'b1'], ['c1', 'd1']]]
     output = [['b0', 'b1'], ['d0', 'c1']]
 

See also tf.gather and `tf.batch_gather`.

Constants

String

OP_NAME

The name of this op, as known by TensorFlow core engine

Public Methods

Output<T>	asOutput() Returns the symbolic handle of the tensor.
static <T extends TType> GatherNd<T>	create(Scope scope, Operand<T> params, Operand<? extends TNumber> indices) Factory method to create a class wrapping a new GatherNd operation.
Output<T>	output() Values from `params` gathered from indices given by `indices`, with shape `indices.shape[:-1] + params.shape[indices.shape[-1]:]`.

Inherited Methods

From class org.tensorflow.op.RawOp

final boolean	equals(Object obj)
final int	hashCode()
Operation	op() Return this unit of computation as a single Operation.
final String	toString()

From class java.lang.Object

boolean	equals(Object arg0)
final Class<?>	getClass()
int	hashCode()
final void	notify()
final void	notifyAll()
String	toString()
final void	wait(long arg0, int arg1)
final void	wait(long arg0)
final void	wait()

From interface org.tensorflow.op.Op

abstract ExecutionEnvironment	env() Return the execution environment this op was created in.
abstract Operation	op() Return this unit of computation as a single Operation.

From interface org.tensorflow.Operand

abstract Output<T>	asOutput() Returns the symbolic handle of the tensor.
abstract T	asTensor() Returns the tensor at this operand.
abstract Shape	shape() Returns the (possibly partially known) shape of the tensor referred to by the Output of this operand.
abstract Class<T>	type() Returns the tensor type of this operand

From interface org.tensorflow.ndarray.Shaped

abstract int	rank()
abstract Shape	shape()
abstract long	size() Computes and returns the total size of this container, in number of values.

Constants

public static final String OP_NAME

The name of this op, as known by TensorFlow core engine

Constant Value: "GatherNd"

Public Methods

public Output<T> asOutput ()

Returns the symbolic handle of the tensor.

Inputs to TensorFlow operations are outputs of another TensorFlow operation. This method is used to obtain a symbolic handle that represents the computation of the input.

public static GatherNd<T> create (Scope scope, Operand<T> params, Operand<? extends TNumber> indices)

Factory method to create a class wrapping a new GatherNd operation.

Parameters

scope	current scope
params	The tensor from which to gather values.
indices	Index tensor.

Returns

• a new instance of GatherNd

public Output<T> output ()

Values from `params` gathered from indices given by `indices`, with shape `indices.shape[:-1] + params.shape[indices.shape[-1]:]`.