in one or more complex frequency terms which cannot be
     represented in a real output and so will always be ignored.
Note:
 The correct interpretation of the Hermitian input depends on the
 length of the original data, as given by "n". This is because
 each input shape could correspond to either an odd or even length
 signal. By default, the signal is assumed to be even length and
 odd signals will not round-trip properly. So, it is recommended
 to always pass the signal length "n".

Note:
 Supports torch.half and torch.chalf on CUDA with GPU Architecture
 SM53 or greater. However it only supports powers of 2 signal
 length in every transformed dimension. With default arguments,
 size of the transformed dimension should be (2^n + 1) as argument
 *n* defaults to even output size = 2 * (transformed_dim_size - 1)

Parameters:
      * input (Tensor) -- the input tensor representing a half-
        Hermitian signal