


torch.special.xlog1py(x, y)
      tensor([0., 0., 0., 0., nan])
      >>> x = torch.tensor([1, 2, 3])
      >>> y = torch.tensor([3, 2, 1])
      >>> torch.special.xlog1py(x, y)
      tensor([1.3863, 2.1972, 2.0794])
      >>> torch.special.xlog1py(x, 4)
      tensor([1.6094, 3.2189, 4.8283])
      >>> torch.special.xlog1py(2, y)
      tensor([2.7726, 2.1972, 1.3863])



torch.special.xlogy(input, other, *, out=None) -> Tensor
Computes "input * log(other)" with the following cases.
  \text{out}_{i} = \begin{cases}     \text{NaN} & \text{if }
  \text{other}_{i} = \text{NaN} \\     0 & \text{if }
  \text{input}_{i} = 0.0 \\     \text{input}_{i} *
  \log{(\text{other}_{i})} & \text{otherwise} \end{cases}

Similar to SciPy's scipy.special.xlogy.
Parameters:
      * input (Number or Tensor) -- Multiplier
  * **other** (*Number** or **Tensor*) -- Argument

Note:
 At least one of "input" or "other" must be a tensor.

Keyword Arguments: