torch.xlogy

torch.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) –

• other (Number or Tensor) –

Note

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

Keyword Arguments

out (Tensor, optional) – the output tensor.

Example:

>>> x = torch.zeros(5,)
>>> y = torch.tensor([-1, 0, 1, float('inf'), float('nan')])
>>> torch.xlogy(x, y)
tensor([0., 0., 0., 0., nan])
>>> x = torch.tensor([1, 2, 3])
>>> y = torch.tensor([3, 2, 1])
>>> torch.xlogy(x, y)
tensor([1.0986, 1.3863, 0.0000])
>>> torch.xlogy(x, 4)
tensor([1.3863, 2.7726, 4.1589])
>>> torch.xlogy(2, y)
tensor([2.1972, 1.3863, 0.0000])