tf.linalg.tensor_diag_part
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Returns the diagonal part of the tensor.
tf.linalg.tensor_diag_part(
input, name=None
)
This operation returns a tensor with the diagonal part of the input. The diagonal part is computed as follows:
Assume input has dimensions [D1,..., Dk, D1,..., Dk], then the output is a tensor of rank k with dimensions [D1,..., Dk] where:
diagonal[i1,..., ik] = input[i1, ..., ik, i1,..., ik].
For a rank 2 tensor, linalg.diag_part and linalg.tensor_diag_part produce the same result. For rank 3 and higher, linalg.diag_part extracts the diagonal of each inner-most matrix in the tensor. An example where they differ is given below.
x = [[[[1111,1112],[1121,1122]],
[[1211,1212],[1221,1222]]],
[[[2111, 2112], [2121, 2122]],
[[2211, 2212], [2221, 2222]]]
]
tf.linalg.tensor_diag_part(x)
<tf.Tensor: shape=(2, 2), dtype=int32, numpy=
array([[1111, 1212],
[2121, 2222]], dtype=int32)>
tf.linalg.diag_part(x).shape
TensorShape([2, 2, 2])
| Args | |
|---|---|
input | A Tensor with rank 2k. |
name | A name for the operation (optional). |
| Returns | |
|---|---|
A Tensor containing diagonals of input. Has the same type as input, and rank k. |
© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.4/api_docs/python/tf/linalg/tensor_diag_part