Google I/O is a wrap! Catch up on TensorFlow sessions

# GatherNd

public final class GatherNd

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

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.

### Public Methods

 Output () Returns the symbolic handle of a tensor. static GatherNd ( Scope scope, Operand params, Operand indices) Factory method to create a class wrapping a new GatherNd operation. Output () Values from params gathered from indices given by indices, with shape indices.shape[:-1] + params.shape[indices.shape[-1]:].

## Public Methods

#### public Output <T> asOutput ()

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.

#### public static GatherNd <T> create ( Scope scope, Operand <T> params, Operand <U> indices)

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

##### Parameters
 scope current scope The tensor from which to gather values. Index tensor.
##### Returns
• a new instance of GatherNd

#### public Output <T> output ()

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

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[{ "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" }]