torch.fmax

torch.fmax(input, other, *, out=None) → Tensor

计算 input 和 other 的逐元素最大值。

This is like torch.maximum() except it handles NaNs differently: if exactly one of the two elements being compared is a NaN then the non-NaN element is taken as the maximum. Only if both elements are NaN is NaN propagated.

This function is a wrapper around C++’s std::fmax and is similar to NumPy’s fmax function.

Supports broadcasting to a common shape, type promotion, and integer and floating-point inputs.

参数

• input (Tensor) – 输入张量。

• other (Tensor) – 第二个输入张量

关键字参数

out (Tensor, optional) – 输出张量。

示例

>>> a = torch.tensor([9.7, float('nan'), 3.1, float('nan')])
>>> b = torch.tensor([-2.2, 0.5, float('nan'), float('nan')])
>>> torch.fmax(a, b)
tensor([9.7000, 0.5000, 3.1000,    nan])