Computes the element-wise maximum of input and other.
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.
>>> 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])
RetroSearch is an open source project built by @garambo | Open a GitHub Issue
Search and Browse the WWW like it's 1997 | Search results from DuckDuckGo
HTML:
3.2
| Encoding:
UTF-8
| Version:
0.7.4