GaussianDropout multiplies the input with the noise sampled from a normal distribution with mean 1.0.
Because this is a regularization layer, it is only active during training time. During inference,
GaussianDropout passes through the input unmodified.
@noDerivative public let probability: Scalar
@noDerivative public let standardDeviation: Scalar
Creates a Gaussian dropout layer.
Preconditionprobability must be a value between 0 and 1 (inclusive).
public init(probability: Scalar)
The probability of a node dropping out.