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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.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`.

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 `
[]
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