Bernoulli
Source:R/gen-namespace-docs.R, R/gen-namespace-examples.R, R/gen-namespace.R
torch_bernoulli.RdBernoulli
Arguments
- self
(Tensor) the input tensor of probability values for the Bernoulli distribution
- p
(Number) a probability value. If
pis passed than it's used instead of the values inselftensor.- 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_tensor
#> 0 0 0
#> 0 0 0
#> 0 0 0
#> [ CPUFloatType{3,3} ]