mindspore.Tensor.bernoulli_
- Tensor.bernoulli_(p=0.5, *, generator=None)[source]
- Fills each location of self with an independent sample from Bernoulli(p). - Parameters
- p (Union[number.Number, Tensor], optional) – p should either be a scalar or tensor containing probabilities to be used for drawing the binary random number, between - 0and- 1. If it is a tensor, p must be floating point. Default:- 0.5.
- Keyword Arguments
- generator ( - mindspore.Generator, optional) – a pseudorandom number generator. Default:- None, uses the default pseudorandom number generator.
- Returns
- The input tensor. 
 - Supported Platforms:
- Ascend
 - Examples - >>> from mindspore import Tensor >>> x = Tensor([[2, 3, 4], [1, 2, 3]]) >>> p = 0.1 >>> print(x.bernoulli_(p).shape) (2, 3)