torch_bernoulli: Bernoulli

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

Bernoulli

Description

Bernoulli

Usage

torch_bernoulli(self, p, generator = NULL)

Arguments

self	(Tensor) the input tensor of probability values for the Bernoulli distribution
p	(Number) a probability value. If p is passed than it's used instead of the values in self tensor.
generator	(torch.Generator, optional) a pseudorandom number generator for sampling

bernoulli(input, *, generator=NULL, out=NULL) -> Tensor

Draws binary random numbers (0 or 1) from a Bernoulli distribution.

The input tensor should be a tensor containing probabilities to be used for drawing the binary random number. Hence, all values in input have to be in the range: 0 \leq \mbox{input}_i \leq 1.

The \mbox{i}^{th} element of the output tensor will draw a value 1 according to the \mbox{i}^{th} probability value given in input.

\mbox{out}_{i} \sim \mathrm{Bernoulli}(p = \mbox{input}_{i})

The returned out tensor only has values 0 or 1 and is of the same shape as input.

out can have integral dtype, but input must have floating point dtype.

Examples

if (torch_is_installed()) {

a = torch_empty(c(3, 3))$uniform_(0, 1)  # generate a uniform random matrix with range c(0, 1)
a
torch_bernoulli(a)
a = torch_ones(c(3, 3)) # probability of drawing "1" is 1
torch_bernoulli(a)
a = torch_zeros(c(3, 3)) # probability of drawing "1" is 0
torch_bernoulli(a)
}

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