Gather slices from params
into a Tensor with shape specified by indices
.
tf.raw_ops.GatherNd(
params, indices, name=None
)
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 | |
---|---|
params
|
A Tensor . The tensor from which to gather values.
|
indices
|
A Tensor . Must be one of the following types: int16 , int32 , int64 .
Index tensor.
|
name
|
A name for the operation (optional). |
Returns | |
---|---|
A Tensor . Has the same type as params .
|