Keyword Arguments:
      out (Tensor, optional) -- the output tensor.
Example::
      >>> torch.special.i0e(torch.arange(5, dtype=torch.float32))
      tensor([1.0000, 0.4658, 0.3085, 0.2430, 0.2070])
torch.special.i1(input, *, out=None) -> Tensor
Computes the first order modified Bessel function of the first kind
   (as defined below) for each element of "input".
  \text{out}_{i} = \frac{(\text{input}_{i})}{2} *
  \sum_{k=0}^{\infty} \frac{(\text{input}_{i}^2/4)^k}{(k!) *
  (k+1)!}

Parameters:
      input (Tensor) -- the input tensor.
Keyword Arguments:
      out (Tensor, optional) -- the output tensor.
Example::
      >>> torch.special.i1(torch.arange(5, dtype=torch.float32))
      tensor([0.0000, 0.5652, 1.5906, 3.9534, 9.7595])
torch.special.i1e(input, *, out=None) -> Tensor
Computes the exponentially scaled first order modified Bessel
   function of the first kind (as defined below) for each element of
   "input".