Shuffle dimensions of x according to a permutation and conjugate the result.
tf.raw_ops.ConjugateTranspose(
x, perm, name=None
)
The output y has the same rank as x. The shapes of x and y satisfy: y.shape[i] == x.shape[perm[i]] for i in [0, 1, ..., rank(x) - 1] y[i,j,k,...,s,t,u] == conj(x[perm[i], perm[j], perm[k],...,perm[s], perm[t], perm[u]])
| Args | |
|---|---|
x | A Tensor. |
perm | A Tensor. Must be one of the following types: int32, int64. |
name | A name for the operation (optional). |
| Returns | |
|---|---|
A Tensor. Has the same type as x. |
© 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/raw_ops/ConjugateTranspose