Thank you for the answer.
Yes, I meant for both CPU and GPU, but for the manipulation of model parameters, I was looking for some pytorch method, that could manipulate the model parameters.
for others who are visiting this post:
A sample of manipulation from PySyft:
    params = model.named_parameters()
    dict_params = dict(params)
    with torch.no_grad():
        for name, param in dict_params.items():
            dict_params[name].set_(dict_params[name].data * scale)