e^{-t^2} dt
Parameters:
      input (Tensor) -- the input tensor.
Keyword Arguments:
      out (Tensor, optional) -- the output tensor.
Example:
  >>> torch.special.erfc(torch.tensor([0, -1., 10.]))
  tensor([ 1.0000, 1.8427,  0.0000])

torch.special.erfcx(input, *, out=None) -> Tensor
Computes the scaled complementary error function for each element
   of "input". The scaled complementary error function is defined as
   follows:
  \mathrm{erfcx}(x) = e^{x^2} \mathrm{erfc}(x)

Parameters:
      input (Tensor) -- the input tensor.
Keyword Arguments:
      out (Tensor, optional) -- the output tensor.
Example:
  >>> torch.special.erfcx(torch.tensor([0, -1., 10.]))
  tensor([ 1.0000, 5.0090, 0.0561])

torch.special.erfinv(input, *, out=None) -> Tensor
Computes the inverse error function of "input". The inverse error
   function is defined in the range (-1, 1) as:
  \mathrm{erfinv}(\mathrm{erf}(x)) = x

Parameters: