torch / torch
torch.bernoulli¶
-
torch.
bernoulli
(input, *, generator=None, out=None) → 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 ininput
have to be in the range: .The element of the output tensor will draw a value according to the probability value given in
input
.The returned
out
tensor only has values 0 or 1 and is of the same shape asinput
.out
can have integraldtype
, butinput
must have floating pointdtype
.- Parameters
input (Tensor) – the input tensor of probability values for the Bernoulli distribution
- Keyword Arguments
generator (
torch.Generator
, optional) – a pseudorandom number generator for samplingout (Tensor, optional) – the output tensor.
Example:
>>> a = torch.empty(3, 3).uniform_(0, 1) # generate a uniform random matrix with range [0, 1] >>> a tensor([[ 0.1737, 0.0950, 0.3609], [ 0.7148, 0.0289, 0.2676], [ 0.9456, 0.8937, 0.7202]]) >>> torch.bernoulli(a) tensor([[ 1., 0., 0.], [ 0., 0., 0.], [ 1., 1., 1.]]) >>> a = torch.ones(3, 3) # probability of drawing "1" is 1 >>> torch.bernoulli(a) tensor([[ 1., 1., 1.], [ 1., 1., 1.], [ 1., 1., 1.]]) >>> a = torch.zeros(3, 3) # probability of drawing "1" is 0 >>> torch.bernoulli(a) tensor([[ 0., 0., 0.], [ 0., 0., 0.], [ 0., 0., 0.]])
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