# tensorflow::ops::GatherNd

#include <array_ops.h>

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

## Summary

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.gatherindices 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.

Arguments:

• scope: A Scope object
• params: The tensor from which to gather values.
• indices: Index tensor.

Returns:

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

### Constructors and Destructors

GatherNd(const ::tensorflow::Scope & scope, ::tensorflow::Input params, ::tensorflow::Input indices)

### Public attributes

operation
Operation
output
::tensorflow::Output

### Public functions

node() const
::tensorflow::Node *
operator::tensorflow::Input() const
 
 
operator::tensorflow::Output() const
 
 

## Public attributes

### operation

Operation operation

### output

::tensorflow::Output output

## Public functions

### GatherNd

 GatherNd(
const ::tensorflow::Scope & scope,
::tensorflow::Input params,
::tensorflow::Input indices
)

### node

::tensorflow::Node * node() const

### operator::tensorflow::Input

 operator::tensorflow::Input() const

### operator::tensorflow::Output

 operator::tensorflow::Output() const
[{ "type": "thumb-down", "id": "missingTheInformationINeed", "label":"Missing the information I need" },{ "type": "thumb-down", "id": "tooComplicatedTooManySteps", "label":"Too complicated / too many steps" },{ "type": "thumb-down", "id": "outOfDate", "label":"Out of date" },{ "type": "thumb-down", "id": "samplesCodeIssue", "label":"Samples / code issue" },{ "type": "thumb-down", "id": "otherDown", "label":"Other" }]
[{ "type": "thumb-up", "id": "easyToUnderstand", "label":"Easy to understand" },{ "type": "thumb-up", "id": "solvedMyProblem", "label":"Solved my problem" },{ "type": "thumb-up", "id": "otherUp", "label":"Other" }]