TensorFlow 1 version | View source on GitHub |
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:
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 | |
|---|---|
params | A Tensor. The tensor from which to gather values. |
indices | A Tensor. 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 as params. |
TensorFlow 1 version
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