torch.amax

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, while max(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])