torch_mean: Mean

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

Mean

Description

Mean

Usage

torch_mean(self, dim, keepdim = FALSE, dtype = NULL)

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.
dtype	the resulting data type.

mean(input) -> Tensor

Returns the mean value of all elements in the input tensor.

mean(input, dim, keepdim=False, out=NULL) -> Tensor

Returns the mean value of each row of the input tensor in the given dimension dim. If dim is a list of dimensions, reduce over all of them.

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).

Examples

if (torch_is_installed()) {

a = torch_randn(c(1, 3))
a
torch_mean(a)


a = torch_randn(c(4, 4))
a
torch_mean(a, 1)
torch_mean(a, 1, TRUE)
}

torch documentation built on Aug. 21, 2025, 5:50 p.m.