torch_pow: Pow

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

Pow

Description

Pow

Usage

torch_pow(self, exponent)

Arguments

self	(float) the scalar base value for the power operation
exponent	(float or tensor) the exponent value

pow(input, exponent, out=NULL) -> Tensor

Takes the power of each element in input with exponent and returns a tensor with the result.

exponent can be either a single float number or a Tensor with the same number of elements as input.

When exponent is a scalar value, the operation applied is:

\mbox{out}_i = x_i^{\mbox{exponent}}

When exponent is a tensor, the operation applied is:

\mbox{out}_i = x_i^{\mbox{exponent}_i}

When exponent is a tensor, the shapes of input and exponent must be broadcastable .

pow(self, exponent, out=NULL) -> Tensor

self is a scalar float value, and exponent is a tensor. The returned tensor out is of the same shape as exponent

The operation applied is:

\mbox{out}_i = \mbox{self} ^ {\mbox{exponent}_i}

Examples

if (torch_is_installed()) {

a = torch_randn(c(4))
a
torch_pow(a, 2)
exp <- torch_arange(1, 5)
a <- torch_arange(1, 5)
a
exp
torch_pow(a, exp)


exp <- torch_arange(1, 5)
base <- 2
torch_pow(base, exp)
}

torch documentation built on June 7, 2023, 6:19 p.m.