Parameters:
      input (Tensor) -- the input tensor.
Keyword Arguments:
      out (Tensor, optional) -- the output tensor.
Example:
  >>> torch.special.erfinv(torch.tensor([0, 0.5, -1.]))
  tensor([ 0.0000,  0.4769,    -inf])

torch.special.exp2(input, *, out=None) -> Tensor
Computes the base two exponential function of "input".
  y_{i} = 2^{x_{i}}

Parameters:
      input (Tensor) -- the input tensor.
Keyword Arguments:
      out (Tensor, optional) -- the output tensor.
Example:
  >>> torch.special.exp2(torch.tensor([0, math.log2(2.), 3, 4]))
  tensor([ 1.,  2.,  8., 16.])

torch.special.expit(input, *, out=None) -> Tensor
Computes the expit (also known as the logistic sigmoid function) of
   the elements of "input".
  \text{out}_{i} = \frac{1}{1 + e^{-\text{input}_{i}}}

Parameters:
      input (Tensor) -- the input tensor.
Keyword Arguments:
      out (Tensor, optional) -- the output tensor.