torch.random
torch.random.fork_rng(devices=None, enabled=True, _caller='fork_rng', _devices_kw='devices')
Forks the RNG, so that when you return, the RNG is reset to the
   state that it was previously in.
Parameters:
      * devices (iterable of CUDA IDs) -- CUDA devices for which
        to fork the RNG.  CPU RNG state is always forked.  By default,
        "fork_rng()" operates on all devices, but will emit a warning
        if your machine has a lot of devices, since this function will
        run very slowly in that case. If you explicitly specify
        devices, this warning will be suppressed
  * **enabled** (*bool*) -- if "False", the RNG is not forked.
    This is a convenience argument for easily disabling the
    context manager without having to delete it and unindent your
    Python code under it.

Return type:
      Generator
torch.random.get_rng_state()
Returns the random number generator state as a torch.ByteTensor.
Return type: