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.
|