torch_amin: Amin

In torch: Tensors and Neural Networks with 'GPU' Acceleration

Amin

Description

Amin

Usage

torch_amin(self, dim = list(), keepdim = FALSE)

Arguments

self	(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.

amin(input, dim, keepdim=FALSE, *, out=None) -> Tensor

Returns the minimum 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 tensors are of the same size as input except in the dimension(s) dim where they are of size 1. Otherwise, dims are squeezed (see torch_squeeze()), resulting in the output tensors having fewer dimensions than input.

Examples

if (torch_is_installed()) {

a <- torch_randn(c(4, 4))
a
torch_amin(a, 1)
}

torch documentation built on May 29, 2024, 9:54 a.m.