Gather slices from params
into a Tensor with shape specified by indices
.
tf.gather_nd(
params,
indices,
batch_dims=0,
name=None
)
indices
is an 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 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]:]
Additionally both 'params' and 'indices' can have M leading batch dimensions that exactly match. In this case 'batch_dims' must be M.
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:
代码语言:javascript复制 indices = [[0, 0], [1, 1]]
params = [['a', 'b'], ['c', 'd']]
output = ['a', 'd']
Slice indexing into a matrix:
代码语言:javascript复制 indices = [[1], [0]]
params = [['a', 'b'], ['c', 'd']]
output = [['c', 'd'], ['a', 'b']]
Indexing into a 3-tensor:
代码语言:javascript复制 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']
The examples below are for the case when only indices have leading extra dimensions. If both 'params' and 'indices' have leading batch dimensions, use the 'batch_dims' parameter to run gather_nd in batch mode.
Batched indexing into a matrix:
代码语言:javascript复制 indices = [[[0, 0]], [[0, 1]]]
params = [['a', 'b'], ['c', 'd']]
output = [['a'], ['b']]
Batched slice indexing into a matrix:
代码语言:javascript复制 indices = [[[1]], [[0]]]
params = [['a', 'b'], ['c', 'd']]
output = [[['c', 'd']], [['a', 'b']]]
Batched indexing into a 3-tensor:
代码语言:javascript复制 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']]
Examples with batched 'params' and 'indices':
代码语言:javascript复制 batch_dims = 1
indices = [[1], [0]]
params = [[['a0', 'b0'], ['c0', 'd0']],
[['a1', 'b1'], ['c1', 'd1']]]
output = [['c0', 'd0'], ['a1', 'b1']]
batch_dims = 1
indices = [[[1]], [[0]]]
params = [[['a0', 'b0'], ['c0', 'd0']],
[['a1', 'b1'], ['c1', 'd1']]]
output = [[['c0', 'd0']], [['a1', 'b1']]]
batch_dims = 1
indices = [[[1, 0]], [[0, 1]]]
params = [[['a0', 'b0'], ['c0', 'd0']],
[['a1', 'b1'], ['c1', 'd1']]]
output = [['c0'], ['b1']]
See also tf.gather
.
Args:
params
: ATensor
. The tensor from which to gather values.indices
: ATensor
. Must be one of the following types:int32
,int64
. Index tensor.name
: A name for the operation (optional).batch_dims
: An integer or a scalar 'Tensor'. The number of batch dimensions.
Returns:
- A
Tensor
. Has the same type asparams
.
Compat aliases
tf.compat.v2.gather_nd