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Gather slices from params into a Tensor with shape specified by indices.
tf.compat.v1.gather_nd(
params, indices, name=None, batch_dims=0
)
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:
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']
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:
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']]
Examples with batched 'params' and 'indices':
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 | |
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params
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A Tensor. The tensor from which to gather values.
|
indices
|
A Tensor. Must be one of the following types: int32, int64.
Index tensor.
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name
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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 as params.
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