torch.amax — PyTorch 2.7 documentation (original) (raw)
torch.amax(input, dim, keepdim=False, *, out=None) → Tensor¶
Returns the maximum value of each slice of the input
tensor in the given dimension(s) dim
.
Note
The difference between max
/min
and amax
/amin
is:
amax
/amin
supports reducing on multiple dimensions,amax
/amin
does not return indices,amax
/amin
evenly distributes gradient between equal values, whilemax(dim)
/min(dim)
propagates gradient only to a single index in the source tensor.
If keepdim
is True
, the output tensor is of the same size as input
except in the dimension(s) dim
where it is of size 1. Otherwise, dim
is squeezed (see torch.squeeze()), resulting in the output tensor having 1 (or len(dim)
) fewer dimension(s).
Parameters
- input (Tensor) – the input tensor.
- dim (int or tuple of ints) – the dimension or dimensions to reduce.
- keepdim (bool) – whether the output tensor has
dim
retained or not.
Keyword Arguments
out (Tensor, optional) – the output tensor.
Example:
a = torch.randn(4, 4) a tensor([[ 0.8177, 1.4878, -0.2491, 0.9130], [-0.7158, 1.1775, 2.0992, 0.4817], [-0.0053, 0.0164, -1.3738, -0.0507], [ 1.9700, 1.1106, -1.0318, -1.0816]]) torch.amax(a, 1) tensor([1.4878, 2.0992, 0.0164, 1.9700])