org.tensorflow.op.core

Class ScatterNd<U>

java.lang.Object

org.tensorflow.op.PrimitiveOp

org.tensorflow.op.core.ScatterNd<U>

Type Parameters:

U - data type for output() output

All Implemented Interfaces:

Op, Operand<U>

@Operator
public final class ScatterNd<U>
extends PrimitiveOp
implements Operand<U>

Scatter `updates` into a new tensor according to `indices`.

Creates a new tensor by applying sparse `updates` to individual values or slices within a tensor (initially zero for numeric, empty for string) of the given `shape` according to indices. This operator is the inverse of the `tf.gather_nd` operator which extracts values or slices from a given tensor.

This operation is similar to tensor_scatter_add, except that the tensor is zero-initialized. Calling `tf.scatter_nd(indices, values, shape)` is identical to `tensor_scatter_add(tf.zeros(shape, values.dtype), indices, values)`

If `indices` contains duplicates, then their updates are accumulated (summed).

WARNING: The order in which updates are applied is nondeterministic, so the output will be nondeterministic if `indices` contains duplicates -- because of some numerical approximation issues, numbers summed in different order may yield different results.

`indices` is an integer tensor containing indices into a new tensor of shape `shape`. The last dimension of `indices` can be at most the rank of `shape`:

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

The last dimension of `indices` corresponds to indices into elements (if `indices.shape[-1] = shape.rank`) or slices (if `indices.shape[-1] < shape.rank`) along dimension `indices.shape[-1]` of `shape`. `updates` is a tensor with shape

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

The simplest form of scatter is to insert individual elements in a tensor by index. For example, say we want to insert 4 scattered elements in a rank-1 tensor with 8 elements.

In Python, this scatter operation would look like this:

     indices = tf.constant([[4], [3], [1], [7]])
     updates = tf.constant([9, 10, 11, 12])
     shape = tf.constant([8])
     scatter = tf.scatter_nd(indices, updates, shape)
     with tf.Session() as sess:
       print(sess.run(scatter))
 

The resulting tensor would look like this:

[0, 11, 0, 10, 9, 0, 0, 12]

We can also, insert entire slices of a higher rank tensor all at once. For example, if we wanted to insert two slices in the first dimension of a rank-3 tensor with two matrices of new values.

In Python, this scatter operation would look like this:

     indices = tf.constant([[0], [2]])
     updates = tf.constant([[[5, 5, 5, 5], [6, 6, 6, 6],
                             [7, 7, 7, 7], [8, 8, 8, 8]],
                            [[5, 5, 5, 5], [6, 6, 6, 6],
                             [7, 7, 7, 7], [8, 8, 8, 8]]])
     shape = tf.constant([4, 4, 4])
     scatter = tf.scatter_nd(indices, updates, shape)
     with tf.Session() as sess:
       print(sess.run(scatter))
 

The resulting tensor would look like this:

[[[5, 5, 5, 5], [6, 6, 6, 6], [7, 7, 7, 7], [8, 8, 8, 8]], [[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]], [[5, 5, 5, 5], [6, 6, 6, 6], [7, 7, 7, 7], [8, 8, 8, 8]], [[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]]]

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, the index is ignored.

Field Summary

Fields inherited from class org.tensorflow.op.PrimitiveOp

operation

Method Summary

Modifier and Type	Method and Description
Output<U>	asOutput() Returns the symbolic handle of a tensor.
static <U,T extends Number> ScatterNd<U>	create(Scope scope, Operand<T> indices, Operand<U> updates, Operand<T> shape) Factory method to create a class wrapping a new ScatterNd operation.
Output<U>	output() A new tensor with the given shape and updates applied according to the indices.

Methods inherited from class org.tensorflow.op.PrimitiveOp

equals, hashCode, op, toString

Methods inherited from class java.lang.Object

clone, finalize, getClass, notify, notifyAll, wait, wait, wait

Method Detail

create

public static <U,T extends Number> ScatterNd<U> create(Scope scope,
                                                       Operand<T> indices,
                                                       Operand<U> updates,
                                                       Operand<T> shape)

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

Parameters:

scope - current scope

indices - Index tensor.

updates - Updates to scatter into output.

shape - 1-D. The shape of the resulting tensor.

Returns:

a new instance of ScatterNd

output

public Output<U> output()

A new tensor with the given shape and updates applied according to the indices.

asOutput

public Output<U> asOutput()

Description copied from interface: Operand

Returns the symbolic handle of a 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.

Specified by:

asOutput in interface Operand<U>

See Also:

OperationBuilder.addInput(Output)