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 first 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
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