ScatterNdAdd

public final class ScatterNdAdd

Applies sparse addition to individual values or slices in a Variable.

`ref` is a `Tensor` with rank `P` and `indices` is a `Tensor` of rank `Q`.

`indices` must be integer tensor, containing indices into `ref`. It must be shape `[d_0, ..., d_{Q-2}, K]` where `0 < K <= P`.

The innermost dimension of `indices` (with length `K`) corresponds to indices into elements (if `K = P`) or slices (if `K < P`) along the `K`th dimension of `ref`.

`updates` is `Tensor` of rank `Q-1+P-K` with shape:

[d_0, ..., d_{Q-2, ref.shape[K], ..., ref.shape[P-1]]
 }

For example, say we want to add 4 scattered elements to a rank-1 tensor to 8 elements. In Python, that addition would look like this:

ref = tf.Variable([1, 2, 3, 4, 5, 6, 7, 8])
 indices = tf.constant([[4], [3], [1], [7]])
 updates = tf.constant([9, 10, 11, 12])
 add = tf.scatter_nd_add(ref, indices, updates)
 with tf.Session() as sess:
   print sess.run(add)
 

The resulting update to ref would look like this:

[1, 13, 3, 14, 14, 6, 7, 20]

See tf.scatter_nd for more details about how to make updates to slices.

Nested Classes

class

ScatterNdAdd.Options

Optional attributes for ScatterNdAdd

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> ScatterNdAdd<T>	create(Scope scope, Operand<T> ref, Operand<? extends TNumber> indices, Operand<T> updates, Options... options) Factory method to create a class wrapping a new ScatterNdAdd operation.
Output<T>	outputRef() Same as ref.
static ScatterNdAdd.Options	useLocking(Boolean useLocking)

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: "ScatterNdAdd"

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 ScatterNdAdd<T> create (Scope scope, Operand<T> ref, Operand<? extends TNumber> indices, Operand<T> updates, Options... options)

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

Parameters

scope	current scope
ref	A mutable Tensor. Should be from a Variable node.
indices	A Tensor. Must be one of the following types: int32, int64. A tensor of indices into ref.
updates	A Tensor. Must have the same type as ref. A tensor of updated values to add to ref.
options	carries optional attributes values

Returns

• a new instance of ScatterNdAdd

public Output<T> outputRef ()

Same as ref. Returned as a convenience for operations that want to use the updated values after the update is done.

public static ScatterNdAdd.Options useLocking (Boolean useLocking)

Parameters

useLocking	An optional bool. Defaults to True. If True, the assignment will be protected by a lock; otherwise the behavior is undefined, but may exhibit less contention.