tntn

    >>> import autograd.numpy as np
    >>> from autograd import grad
    >>> def fn(x):
    ...   return np.power(np.power(x, 3), 1/3)
    ...
    >>> gradfn = grad(fn)
    >>> gradfn(0.0)
    /usr/local/lib/python3.6/dist-packages/autograd/numpy/numpy_vjps.py:59:RuntimeWarning: divide by zero encountered in double_scalars
    lambda ans, x, y : unbroadcast_f(x, lambda g: g * y * x ** anp.where(y, y - 1, 1.)),
    /usr/local/lib/python3.6/dist-packages/autograd/numpy/numpy_vjps.py:59: RuntimeWarning: invalid value encountered in double_scalars
     lambda ans, x, y : unbroadcast_f(x, lambda g: g * y * x ** anp.where(y, y - 1, 1.)),
    nan

    >>> import torch
    >>> x = torch.tensor(0.0, requires_grad=True)
    >>> y = ((x**3) ** (1/3))
    >>> y.backward()
    >>> x.grad
    tensor(nan)