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 .

Args:

  • 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